It's bugging me, so I've been looking into it more. This is about the median dropping in subsequent years, not game importance anymore.
Normal Man City test
2024: 144, 3.5 star, Aston Villa 134 2025: 126, 2 star, Aston Villa 144 2026: 102, 1 star, Arsenal 113, Aston Villa 133.5 2027: 94.5, 0.5 star, Arsenal 124.5, Aston Villa 124 2028: 119.5, 3 star, Arsenal 122.5, Aston Villa 121 2029: 112, 2 star, Arsenal 103, Aston Villa 126 2030: 103.5, 2 star, Arsenal 120, Aston Villa 125 2031: 120.5, 2.5 star, Arsenal 123, Aston Villa 134
Average: 115.25, Aston Villa 130.1875
Normal Aston Villa test
2024: 136.5, 5 star, Man City 132 2025: 129, 3 star, Man City 138 2026: 90, 0.5 star, Man City 121 2027: 99.5, 3 star, Man City 140 2028: 120, 3 star, Man City 120 2029: 110.5, 3 star, Man City 122 2030: 106.5, 1.5 star, Man City 123 2031: 113.5, 2.5 star, Man City 135
Average: 113.1875, Man City 128.875
Forest Green (league 2) non-player: 70, 91.5 Forest Green player: 52 (note: was 0.5 star)
Overall this is a relief, because it seems to be the case that the median of all non-player teams doesn't decline or go all over the place in subsequent years. That median variation of -/+ ~10 is normal if you're unfamiliar.
It's only the player team that is affected. And this seems to be consistent across different division levels/club quality.
It's not about existing youth players affecting things, I tested that, and the AI's median remaining unaffected which I found out later is further proof of this.
I thought maybe what's causing it is the manager itself, specifically either the reputation or the player & youngster knowledge of the human manager. But changing those attributes didn't seem to make a difference.
I think that the median being normal in the first year might be a clue as to what's causing it.
So does this mean I can set all the aforementioned attributes to 1 in this template? Or does it mean those attributes were lowered to 1 and other attributes were raised? Please let me know if there are any templates with a lower CA. Expand Yes, you'll be fine with players that have '1' in those attributes.
I recommend using my genie scout rating file, it will find you the most CA-efficient players.
keithb said: its been funny to see him say other people's work is wrong and then have to retract multiple times. Expand You keep saying this so I assume you must actually believe it to be true. I feel like I have to address it even though it's unsubstantiated, because people aren't going to be digging up my posts to check for themselves and they might just assume you're half correct.
I have never said the work of HarvestGreen or EBFM is wrong, except on some niche aspects. For Instance, I think EBFM is wrong specifically about youth facilities making a minor contribution to PA, probably because he used average instead of median as measurement. And I think he is wrong on his 'draft hypothesis' for youth recruitment (though even he wasn't 100% on this theory). But apart from these two things, I don't think I disagree about anything EBFM presented.
With HarvestGreen I think I've only ever disagreed on certain things open to interpretation. For instance I favor a different training schedule to him, but this is because he weights attributes differently in his thinking, i.e. just how negatively should 'decisions' growth be weighted.
I've pushed back against people on a few things. One was about player fitness. Another was about player personality attributes being random or not.
There are more I've forgotten, but the player personality one is one I ended up conceding on. It turned out player personality attributes are not just random, and that wasn't someone's 'work' it was just a claim made that I subsequently tested and changed my mind on. But I really can't think of anything more substantial than that I've had to retract.
White Europe said: Ok great 👍, thanks for answer, just wondered if I want to use other style than gegenpress, or just create my own tiki taka tactic is those ratings still helpful? Or they just to support meta gegenpress tactics? Expand Whatever tactic you use, the ratings will work well.
The values are necessarily quite a bit airy fairy anyway. The main thing it's doing is that it's prioritizing key attributes that are universally good such as pace, acc, dribbling, work rate, pressure, and so forth. But then when it comes to something like 'long shots' say, maybe that deserves a 1% weighting or maybe it's 11%.. but this is only going to move the overall needle a fraction of a percent anyway. But then if you add up all these little errors together, that might end up being an error of ~3%.
A simple change you could do to tailor it more to other tactics I guess is to simply reduce the pace/acc weighting by ~10-20%. I think that was the gist of the main difference I saw in HarvestGreen's findings of tactic differences.
keithb said: Again, what? Your replies are incoherent. Half a year? Obsessed? Still going on? You either waffle on with stuff that makes no sense, or in this instance throw a few words out at me.
I was merely questioning why it's taken you this long to determine several things we knew Long time ago. I have noticed multiple times you've declared other people's work and findings wrong, only to later retract and say you made a mistake. You're cosplaying being an elite tester for football manager, but you're sloppy at best.
I only came on to see if strikerless was still meta in 26. But the forum is so full of your posts I had a peek for a laugh. I see above you've mentioned certain attributes are more important for different positions. Is this true? Expand If you look at your posts page, your last post before the one in this thread was in February saying to me:
keithb said: What a load of shit😂. Do you think we're five years old?! Exposing the truths about football manager has nothing to do with your username.
Clearly you're desperate to be someone in the community, but all you're mainly doing is regurgitating other people's work. Well done. Bravo. You're a nobody. But at least you've got that username, really sticking it to SI!! Expand And then if you scroll down, there's a few more that are replies to me or about me. Two of them about being upset about my username are from October last year.
What you claim about me in relation to other people's work is simply wrong. Example at hand: Who else is attempting to update FM Genie Scout ratings values, in a way that merges HarvestGreen's findings with positional weighting of attributes?
White Europe said: Guys im new to gennie scout so i have a question: I have a guy for DM position with 70 rating in general for DM position and 69 for volante role which im using in my tactic and a guy with 68 general rating for DM position but 71 for Volante role: so which rating is more important general or role?? I hope this make sense Expand Always use the position rating, not the role rating. You can find evidence on this forum that where certain roles will say they don't need acc/pace, they still need it just as much as roles that do have them listed as requirements. Essentially, roles seem misleading and cosmetic.
I suppose it's possible that there are still variations in terms of tactical role. I.e. if you set DL to 'dribble more' maybe it benefits from better dribbling more. But I will say that in trying to adjust one of Knap's top tactics myself along these lines (to suit/fit better a certain set of attributes), I couldn't get better results, so I doubt it matters here either. HarvestGreen has found different attribute results for different tactics used, but the differences weren't that big.
I continued testing game importance at the 5 year mark and got these additional results:
England normal ('very important' ) samples:
119 120.5 113.5 106 118.5
England 'unimportant' samples:
140 143.5 140.5
2nd 'very important' samples:
105.5 111 101
At this point I stopped because there is something extra going on here that is more notable in itself. Still, I think we can pretty much wrap up the game importance thing, as ~140 PA median for Man City (or almost any club really) is about as high as it gets.
But now the matter of these highly variable medians. I have a feeling I already knew this years ago but I have forgotten about it, as I was recalling recently how I would savescum a whole year in advance to see the newgen results instead of reloading just before newgen day, in recent versions, and I couldn't remember why. Now I see it's no doubt because certain things are being set a few months earlier than intake day with the new 'Youth Preview' system.
Honestly I'm still hazy right now on it and I can't really be bothered digging deep into it, but I know this doesn't affect any data I've presented, except this multi-year attempt thing.
It's not to do with facilities, reputation, club coefficients, etc. changing - I double checked all those to make sure. What it does seem to correlate strongly with is your youth intake quality star rating. Yes, this star rating is relative to your existing squad, but it seems also nonetheless to be reflecting the differences in your median PA.
If median PA can vary for even a top club by as much as ~30% randomly, then does knowing the newgen factors even matter at this point? In a way this is a point even I don't want to admit, but it's one reason FM was losing its lustre for me even before FM26, they ruined the fun of newgens. On the other hand, the factors still work, and the year-to-year randomness doesn't mean inherent randomness - it's a dampener for sure, but still means you have a reasonably predictable and consistent system. To illustrate the difference:
Before:
Man City - 140, 143, 135, 146, 148 Arsenal - 136, 129, 138, 139, 139
Now (nation-based year-to-year randomness):
Man City - 140, 110, 115, 130, 145 Arsenal - 136, 107, 110, 119, 142
Inherent randomness (~30%):
Man City - 140, 110, 115, 130, 160 Arsenal - 158, 181, 132, 105, 116
That's if nation-based year-to-year randomness is what is actually going on here. As I said, I'm quite hazy on it right now. I'll probably try and get to the bottom of it sometime down the track. I know this all seems to put things in the wrong direction of progress, and people generally don't like that, but better to acknowledge the setbacks/problems than keep them on the down low and end up fooling myself/others about it.
keithb said: What are you on about?? You seem to be discovering a lot of things years after most people knew that already. Whats next? the sun is hot? Expand Oh I didn't realize you're the guy who is obsessed with me. It's been half a year and you're still going on like this. I wanted to communicate to others the points I made anyway.
BaZuKa said: Ok this new file is Giga Broken Season 3 almost won everything with a low-tier club from Portugal Expand The first line sunk me for a moment there. It's good to hear it's working well for you, I don't actually know how well in reality these files are going to go.
I keep forgetting to mention things. I used HarvestGreen's 6 > 18 attribute data mainly this time, as using 1-20 overvalues things like pressure and work rate. I figure in cases where pressure or work rate is very low, you can either just filter out those players or train/tutor them up a bit if you do buy them. And getting '20' is less likely as well as more CA-inefficient, so that's another reason I favor the 6>18 measure.
keithb said: Haaland is clear in FM 24. Surely it hasn't taken this much research to determine that? Mbappe is the best lw. Glad we've been finally able to clear up that FM genie scout default ratings are way off. Expand
Just piggybacking off this to say that I haven't used the player names/clubs to calibrate my values. There's a good reason for this, and that is that in-game player ratings don't correspond exactly to actual performance.
You can see evidence of this in this OmegaLuke video, where technicals give substantially higher player ratings than physicals, even though physicals actually won all the games. Orion's coefficients, which use in-game player ratings to deduce the best attributes, I've found are outdone by HarvestGreen's data which assesses according to goals scored or games won.
So this is why I don't try and align the values to fit player ratings or the best players, as that would achieve the opposite of what I want to achieve, which is show players who punch above their weight in a way the in-game AI doesn't recognize.
But I think there is some value in comparing the results afterwards, just to make sure one isn't completely off-track. Regardless of rating, we know Haaland gets goals, so if he's not up there then there's something amiss.
Additionally I think it's notable how the starting data closely aligns with physicals matter and technicals don't. If you plug in HarvestGreen's data, it just so happens that the top players start in the top clubs in the game. That sounds as straightforward 2+2=4, except realize that this means that SI knows exactly how the attributes are skewed and disingenuous. If they believed what they tell you about how the game works, then we should see these initial players at top clubs failing to perform. In fact, I think perhaps this in-game rating bias towards technicals is to try and stop AI managers simply buying up completely lopsided physical beasts as the game goes on.
I can think of a reasonable counter-argument or two to the above, but there is also some circumstantial evidence as I see it. If you use Genie Scout default ratings, 7 out of 9 top players (one of each position) are white. If you use HarvestGreen's data it changes to 7 out of 9 being black. Either SI still has a racism problem where black people are portrayed as mentally/technically poor physical beasts, or this is intentional. Or both.
LightningFlik said: Sorry to pile on with demands @GeorgeFloydOverdosed, but can you provide these weights as raw data? That is, I don't think Genie Scout runs on Linux but I'd be interested in seeing what you've come up with.
(No rush, whenever you have time). Expand OpticFawn said: Yes please, I want to use on personal tool pls Expand Here are the values for FM24 blended.
I forgot to say that 'sweeper' position is intended to be my attempt at a tutor rating, and for Target Striker I've simply upped jumping reach to 100, as high pace/acc ST is simply better than a slow target man and I'm not sure if heading or whatnot affects the target man's performance (jumping reach certainly matters).
I haven't done FM26 versions yet and it'll be a while before I do, I recommend just using the FM26 ratings file I did before and replacing the GK ratings with the new values in FM24 Blended. You could use these new files in FM26, but it would be a bit off (still much better than FM Genie Scout default).
I'm increasingly unsatisfied with the result as I've ran into further issues, but I've decided to just put these out there otherwise it'll never get done and it does seem to work better despite the issues.
I've had a dilemma about merging in some of my own findings. One example is that in my 1 CA player testing I found that concentration matters on CB/DL/DR, not other positions. Another is that extra finishing on CBs made no difference to goals scored, which means it's low weight on CBs for a reason. These findings are a part of my previous ratings file, so I wanted to include them again here. But I also figured that my data isn't as strongly evidenced as HarvestGreen's, and some of my conclusions could just simply be wrong. On the other hand, there were a number of different examples which can't all be wrong and it makes sense that different positions benefit from certain attributes to different degrees, so I don't think it's best just to use HarvestGreen's data flatly amongst all players. In the end I decided to just apply a simple -/+25% to a few attributes that I was quite sure had pronounced positional differences. I.e. dribbling 32 > 40, vision 5 > 7. So nothing too drastic, but this leaves me feeling like it is too arbitrary a change and yet it also doesn't go far enough probably. The only reassurance I have is that the actual results seem to be better, which you can see a sample of below.
Another issue I've had is with the new GK data. Initially I just plugged in HarvestGreen's new figures. But looking at the results, I get the impression something isn't quite right with the new data. And if you look at HarvestGreen's old GK data, which only had conceded goals as a measure but was also measuring 10>20 instead of 1>20, you can see there are contradictions. From my own 1 CA player tests, I found that acc & pace seemed best value around ~5-8 rather than 20. And if you look at actual players in the database, a bunch of the best have acc of just 8-10. So I think this is mainly a case of missing the data that shows where ~6-14 is sufficient, which we know some attributes such as work rate are like. So I made some appropriate adjustments. Definitely an improvement on my old ratings file here.
Here are some example results. Two important differences that stand out to me are that the GKs are significantly more correct in the new version (Pickford shouldn't be behind Forster!) and there are no longer 2 japanese players from Celtic in the top 10 ST list (they do have high acc/pace, but this seems an appropriate change). And clearly with Kane as no. 1 ST, FM Genie Scout default ratings are way off.
New (blended):
Pickford 69.53% Pope 67.67% Ramsdale 67.43% Steele 65.41%
Old:
Pope 69.74% Forster 65.89% Pickford 65.13% Ramsdale 65.00%
HarvestGreen (new GK data):
Pope 75.44% Pickford 73.89% Ramsdale 72.98% Butland 72.85%
jimmysthebestcop said: Extremely interesting. I havent even bought or played the demo of Fm26 I am staying away from it as it is a flaming dumpster of poop and I cant reward SI with my money. Maybe I will jump back in fm27. Is it different in fm26? No idea.
I would be interested in your results over a 10-20 year span. At least in Fm24 and all previous versions if Game Importance wasnt set to very high in a decent Youth nation you couldnt produce NewGens even if your were #1 club in the world.
Singapore could never have good players because there youth rating is bad. Czech would be a good test as their youth rating is 90-100+ while game importance is not set to very important.
I dont think this is an issue for most players since most people play in a big nation, build a nation saves arent that popular in the community. So most people wont notice it.
I am honestly probably not explaining myself well. I just know in fm24 and prior when doing build a nation saves even if you changed youth rating to 100 the nation couldnt ever produce wonder kids even when getting league to top 5 and all the clubs in the top 50 if Game Importance wasnt set to very important.
I dont know if there is some kind of time factor and that is why you need to sim 10-20 seasons or what tbh. Expand I should have mentioned that I used FM24. I guess some will say then what's the point of doing an updated test if you're not going to even use the most recent edition, but for me FM26 just has to be foregone.
I actually completely forgot to do one thing I wanted to do this time, which was to test what it looks like 5-10 years into the future.
I wanted to do USA initially, to address your claim about the MLS exactly, but found newgen intake works a bit differently and I couldn't be bothered trying to work it out. So my plan after that was to choose a nation with low game importance but high youth rating, but there aren't really any that are loadable - and singapore was one of the best options that was left. But this is also why I did Man City, because I had in mind (and generally what people play with) is clubs with top facilities in top nations, and England is no.1 for that.
As I was writing this I was doing my testing, and I was about to say that I've been wrong about game importance all these years, as 5 years in, the Man City (unimportant England) median had slipped to 117.5 PA (155 peak) which is outside of the range one would expect for the 131.166 PA averaged median I had got for the initial year. But then I did the control test (normal England), and that was 122 PA median, and 115.5 PA on the second sample.
This is bringing back what I experienced regarding game importance back when I initially tested it in FM19. No one has so far pointed out that I said game importance has no effect, yet later claim it has a minor effect, but I want to clarify this. As you can see, game importance has a minor effect that is only sometimes apparent. When I started testing it, I used average PA as a measure and so it was invisible to me and I thought it had no effect. Once I cottoned on to median PA being more accurate, I observed that questionable minor effect. In multi-year tests I thought I had borne out its effect, only to be confounded again in the same way this time. So I had to conclude whether a handful of PA difference, some of the time, constituted something real or an illusion. I concluded it was illusory, although the bunching up around the median effect is obviously real. It's a bit difficult to explain this fully if you haven't tried this kind of testing yourself, but basically it's very easy to be hoodwinked by limited samples and the inherent randomness. If I test a club and get 139, 134, 140, 137 then it's very tempting to say this club is a ~137.5 PA club. But then I would get 153 and 145 if I took 2 more samples. So this is why when I saw game importance raising PA by at most ~10% and inconsistently, I put it down to randomness.
I will continue this testing a bit, to clarify results at the 5 year and 10 year mark, as it does require at least 3 (preferably 5) samples to give any reliable indication.
So my take on the valuation of free CA is roughly this:
We know it has always has some value, because high CA-PA gap = faster training = higher pace/acc faster.
Therefore a zero CA cost attribute such as 'pressure' that has a significant effect on win rate, is even more valuable than an equivalent attribute that costs CA, say dribbling. But by how much exactly? 2 points of pace and acceleration each perhaps? I prefer to go on the safe side and guesstimate 1-2 points of just pace say (I think about what gets 'sacrificed' to stay within PA limit at the end of ~4 years of training).
But then you have positions such as DM where you can easily max out pace/acc to 20 without hitting the PA cap, at least if you're in a good division (which I think most players are in, or plan to end up in).
So I figure the bonus for DM should be reduced, and conversely the bonus for a CA-tight position such as AML should be increased.
But this leads to the peculiar consequence that positions that benefit most from high pace/acc, such as AML, value them least. Not to mention the fact that lowering the immediate gains (from high pace/acc) for expected future gains that may never even eventuate. And then there are also inherent variables whose expected ranges exceed the capacity of this predictive method. For instance, even assuming everyone uses meta training, one player might go from 15>17 pace, another will go from 14>20.
So in the end what I decided is, I will have a set of values for youth/optimization, a set of values for age26+/team selection/pure performance (which will be very closely aligned with HarvestGreen's findings), and then a blend of the two - which will be the file I recommend to use as switching between files is tedious. Is a 50/50 blend the best? Probably not, but it's the best I can do so far. I have checked in genie scout the actual results of these new values, and it seems to be working as it should - the best players are those from Man City, Barcelona, Real Madrid, etc. as you'd expect. I've looked for outliers that have changed positions the most, and overall I'd say the margin of error could be something like -/+3% genie scout rating, which I think is satisfactory.
Here's an example to give you an idea about things:
Default Genie Scout - Kane 91.47%, Haaland 90.95%, Mbappe 88.30% Orion's Coefficients (not my file) - Haaland 88.01%, Mbappe 86.31%, Kane 81.63% My existing file - Mbappe 77.59%, Haaland 77.25%, Kane 67.35% New file (youth/optimization) - Mbappe 79.73%, Haaland 75.69%, Kane 65.64% New file (age26+/pure performance) - Haaland 95.34%, Mbappe 93.59%, Kane 82.21% New file (blended) - Mbappe 85.33%, Haaland 83.74%, Kane 72.46%
Ignore the numbers themselves, it's about how relative they are to each other
suwit13 said: Hello, I've been using your player rating coeff on Genie Scout and it's been working very well.
Recently, harvestgreen22 released a new test for GK attributes. Can you convert the data to your player rating coeff? @GeorgeFloydOverdosed Expand I've actually been working on this recently
Initially I was just going to redo the GK, but then I realized I want to take a new approach to the whole thing.
I've ended up not entirely satisfied with the new approach, basically I think it's definitely better but even more arbitrary in a way. It's mostly to do with balancing CA weighting vs. raw performance, and the problematic question is if an attribute gives a slight boost to win rate but on the other hand also only has very low CA weight (or zero CA weight, like personality attributes), do you give that some kind of bonus and if so to what degree? Basically, how much is free CA even worth exactly. So I've come up with a take on this, that also integrates training results with good accuracy (i.e. if meta training is expected to lower passing by 1 over 4 years, I adjust the passing value slightly accordingly - this is more pronounced for pace/acc which will increase by ~4 in youth over 4 years!).
It's largely done now, just have to finish off some positions I don't use like WBL/MC/AMC and also create a FM26 adjusted version before I post it. Will be soon.
jimmysthebestcop said: I wish I was mistaken all of the Build a Nation players know about Game Importance superseding NewGen settings. Go watch a ton of of SecondYellowCard Build a Nation setup videos and read his discords where his followers test all of the NewGen stuff for the lowest nations.
I can tell you my last 3 build a nation saves were hungary before I knew about game importance, Andorra and Faroe Islands. Hungary even after 60 years where I gave every club billions and billions to max out their facilities could never produce a NewGen that was as good as IRL national club member. The way you give clubs billions is by buying their horrendous youth players for 10 million each as the board never turns down 10 million offers. So you are buying 30+ players per club eventually. Giving clubs 300 million each season. Expand Coincidentally it was a recent video by SecondYellowCard where he tested the DoF role that got me thinking that youth recruitment might work similarly. Turns out it likely doesn't, but that's what led me to investigate the 'place of birth' thing.
I haven't been able to find this discord you mention yet, but I've done some testing of game importance anyway, not only to draw a conclusion here but because it's good to retest things once every few years to see if the mechanic has changed and also I'd like further clarity/precision on the distribution effect I mentioned. I retested recently the hidden nation factor thing I assert is the case, and I can confirm it still exists.
England very important (default) Man City average (3 samples):
median 142.166 average 135.375 range 68.333-172.333
england-wide stats:
range 30-179 10th best player = 157.333 PA
England unimportant Man City average (3 samples):
median 131.666 average 132.687 range 78.666-162
england-wide stats:
range 34-170.33 10th best player = 153.666 PA
Conclusions
Game importance has no strong effect on PA. Previously I had said it bunches up the PA around the median and ends up affecting the PA to the tune of ~10%, and this is what we see. But as I tried to communicate in qualifying that 'it's not directly comparable to the other PA factors so it's hard to pin down a precise figure', it's not a simple flat 10% - in Singapore's case, the effect was 0% or even negative. In England's case, it was an 8% difference, for both Man City and (to a similar degree) the nation as a whole.
The main takeaway from game importance as I see it is that because it bunches up PA around the median, it does actually dampen your wonderkid chances just enough to make one not want to dismiss it entirely, but it's not that significant or consistently applicable as other factors such as junior coaching are. 160 PA instead of 170 PA, in some cases.
I haven't done a deep analysis of it, but just my general impression is that its not that Game Importance is shifting up or down the general quality of the newgens either, and this is somewhat indicated by the low difference in the average as well (2% difference for the Man City samples). I think it's simply bunching up the distribution closer to the median.
I hope this also serves as an illustration of why I use the median instead of the average. The median is pretty stable and therefore predictable unlike the average. While the median can be predicted with strong likelihood of being within a range of -/+ 5 PA or thereabouts with enough samples, the average will end up with an uncertainty range of ~10 PA or more even if you collect many samples.
I included height in the singapore samples as I thought it was interesting to observe; I wondered if its distribution has some correlation, or something in common, with the PA distribution.
Here's my rough mockup of what the 'place of birth' selection actually looks like.
This whole thing appears to be purely cosmetic, so don't try and work out how to get better newgens with it. There is no actual competing for newgens, or even newgen generation in these cities, going on.
There are three clubs: Ljubljana, Kamnik, and Maribor.
The rectangle is area the club can draw newgens from.
It is not that newgens are generated at each city and a few of them get picked up, it is that the club generates precisely 16 newgens. There 'place of birth' is probabilistic based on distance from club and 'inhabitants range' of the city. The circles are just to convey the idea of decreasing probability the further you go out from the club location.
Notice how Ljubljana and Maribor each draw ~4 players from their own city, but Kamnik only draws 2 and takes many more from nearby the nearby capital of Ljubljana. This is because Kamnik has low inhabitants range, and Ljubljana is high probability because of proximity + high inhabitants.
I do not think city 'attraction' affects it, I have tested it but the results are not 100% clear but clear enough to rule it out I think. From memory, 'inhabitants range' is also relative to 'inhabitants range' of other cities. That is to say, if Ljubjlana only had 10,000 people, it would still be top dog if all other cities are 1000< pop, but also it would be less commonly the place of birth than if it had 20mil people and others 1000< pop. There are some further nuances that reveal themselves when you try to break it with extremes like this, but since the mechanic is cosmetic, I won't go further into that.
Lastly there is the matter of exceptions. As you can see, sometimes there can be instances outside the rectangle. I don't know what exactly is going on here, I suspect it has something to do with youth recruitment perhaps. Maybe it's even just a randomness factor they've put in to try and better reflect reality.
The most important factor in PA for newgens aka youth intake is your nations' "GAME IMPORTANCE" if it is not set to "Very Important" you will never have any good NewGens even if you played 1000 years. You have the RNG of finding 1 random Star like how some random Asian Island gets 1 star every 50 years or whatever.
I've done a load of build a nation saves and testing. It is pretty easy to test. Max out everything but set game importance to the lowest level and the NewGens will be awful even with everything else Maxxed out.
This is the actual problem with USA in FM as the game importance is set to the lowest setting while everything else is pretty on par with the Big 10 in Europe.
USA in FM cannot generate any USA players for a top 20 National Team. All of the USA National Team NewGens (once the real players retire) will all spawn over seas at other clubs. Because it uses the nations game importance of where the player is spawned at.
USA cannot even spawn MLS caliber players!!!!!!!! USA will literally spawn garbage NewGens in USA.The entire national team will be spawned at overseas club intake.
Game Importance supersedes all other youth settings and mechanics. I am not even sure if SI is aware of it lmao.
If you are playing a top league in a top country you really wont notice anything. Expand Hear me out, I believe you are largely mistaken on this.
From memory, game importance does have a modest effect on the distribution (low game importance = PA more bunched up around median), but it doesn't change the median or rule out very high PA players occurring entirely. Don't take my word for it, you can see EBFM's test results. Two problems with EBFM's data here is that he didn't look at the distribution as a whole, and he uses average instead of median. I think I've neglected to say before that this is (likely) why EBFM came to a different conclusion about youth facilities, where he found a very slight but consistent increase to PA. This is because he used the average, which isn't reliable with FM's system, and I guess it's possible something is going on here but I'd think if there is it'd probably be that the CA boost from YF is roughly added to the PA (i.e. 36 CA > 40 CA = 120 PA > 124 PA).
I would say that game importance is equivalent to a ~10% PA factor, it's not directly comparable to the other PA factors so it's hard to pin down a precise figure.
That said I haven't tested it in a long time, and it's possible your testing was qualitatively different to what I did. You said you maxed out all other factors. I guess it's possible low game importance has a more pronounced effect in such conditions. But what I do know is that with the default game settings we play with, game importance is almost a negligible factor.
Part of it could also be that because nations do in fact appear to have different (and significant) values set under the hood, it's easy to confuse that with game importance, cities, etc.
I've been doing more testing that I've been sitting on for a while now as I reflect on how to best communicate it. Basically I noticed how newgens have unique 'place of birth' that usually isn't even the club's city, so I thought this might be a clue that would allow me to deduce the hidden nation mechanics.
EBFM got as far as thinking it's probably a national pool & draft process going on. What I've found is that seemingly can't be true. From testing before, I already knew that city, local region, etc. all had zero influence on PA. But now I also know that the whole city system is essentially purely cosmetic. There is a sophisticated mechanic that assigns the place of birth, but it does not affect the newgen PA.
Why this matters:
- There isn't some more sophisticated behind the scenes stuff going on like HoYDs/U18s staff poaching from other cities in the local region or such. This doesn't mean that 'Youth Recruitment' doesn't do anything, it just means that it acts independently with its own mechanism; it doesn't interact with some underlying hidden process regarding cities and pre-newgens floating around the place and whatnot.
- There aren't 'player pools' in cities, therefore there is no player scarcity in regards to 'youth recruitment' in congested areas.
- The PA comes from the club location (nation), not the birth city location.
- 'Local region' doesn't seem to have any effect on...anything. I think it probably simply serves a 'boundary' purpose for editing, i.e. a team coordinates is in south England but is part of a northern local region so it gets counted in the north division.
Teasing out those implications takes some thought itself, but there is more (though less significant) that is difficult to explain without bamboozling someone who hasn't been looking at it for several hours as I have. For instance:
- Newgens come from the city location, not the club location, but they adopt the nationality of the club. This is confusing, and purely cosmetic, but I can illustrate its probable intended purpose with an example: Suppose an American Samoa club is added to USA competition. The club is 'based in' USA for economic travel reasons say, but the youths coming through are born in 'Pago Pago' because it's an American Samoa club.
- You cannot tell whether players are generated first at cities or at clubs, because they are the same thing - the club generates them as having come from cities.
- There is a map coordinate geometry to city/'place of birth' selection, likely a rectangle with decreasing selection probability towards the edges. But there are nuances and even exceptions.
Of course I would have to furnish all the different examples I found to prove my findings, in addition to explaining these abstractions.
Unfortunately it didn't get me any closer to uncovering the hidden nation factor, but what it has shown me is that the newgen recruitment process is probably a lot more simple than previously thought, in regards to PA, and it reinforces that unique nation ID is a key component while staff, cities, whatnot isn't.
LightningFlik said: Idea for an experiment (which I'd run if I had a more performant PC, but I'm at the mercy of you kind strangers): what if you assembled a squad of players, who were capable of winning the league, but then randomly shuffled each player's set of attributes amongst each other?
For example, your LB has your MC's attributes, your ST has your RB's attributes, your DM has your ST's attributes and so on (leaving goalkeepers alone). Naturally each player's role analysis would be in the toilet but if experiments have revealed that tactics are less impactful than attributes alone, it might also follow that the sum talent of your team is more important than who plays where (assuming you're 1. using a tactic that makes sense and 2. players aren't playing out of position, just wildly out of role). Expand I've tried this, and found that it doesn't work because as soon as the DM's performance as 'ST' becomes better than DM, he becomes DM+ST.
What can work is you can game it slightly, since FM's role calculations aren't perfect (i.e. overweights technicals/mentals).
Digging deeper, there are certain attributes that do appear to be pooled as a team, or are primarily about order of priority. Obvious example would be finishing, where I found you can win the Premier League with 1 CA players and a ST with 1 finishing, it's just that the bulk of the goalscoring gets shifted to the other position that has the highest finishing. Not sure if it's also being pooled in this case, but having some finishing on at least one player seems beneficial (HarvestGreen's testing show it's a minor-moderate contributing factor).
Can't remember what attributes seemed pooled and which aren't, but overall I'd say the pooled attributes don't contribute much anyway. High pace/acc on all players (except GK) is kind of essential to win.
You might also think that since we're favoring a high pace/acc/drib team, a team of selfish players in an abstract sense, then we should adjust our tactic towards one that gels with that. Either knap's tactic is already tailored towards this perfectly, or this theory just doesn't work in practice, because I've tried a whole bunch of adjustments with this idea and nothing did any better.
I suppose the other thing to mention is that some positions are more cost-efficient than others, and quite significantly so. AMR/AML is the most costly, DM the least. So if had a low PA team, you might favor some sort of tactic with 3 DMs and no AMR/AML. But personally, I just stick with the top knap tactic, which does use AMR/AML (in FM24).
Mark said: What is the DM as AMl exploit? Expand I'm referring to the method that has been done successfully with a 1 CA team before, where strikerless tactic with 6 DM/MC are used because the CA cost for that position is the lowest.
Couldn't really come up with a good single phrase to describe it
After aligning attributes more closely with HarvestGreen's win % findings and making a bunch of other minor adjustments to various things, season win rate with the 1 CA players is now at 70% (5/7 wins). Previously it was 10%<.
Honestly, I just wanted to share the results. But here are some further thoughts I have derived so far from the testing process:
It shows that HarvestGreen's data is accurate, but also that it works in 20/6/1 attribute scenarios rather than just scenarios where all other attributes are held at 10. In other words, high variability/oscillation of attributes doesn't seem to alter the impact of an individual attribute.
I changed so many things at once that I can't confirm as much as I'd like to right now, but what I can say is that all players had '1' in the following attributes: Decisions, Technique, First Touch, Flair, Leadership, Teamwork. All outfield players also had '1' Bravery, Off The Ball, Corners, Crossing, Free Kicks, Long Shots, Long Throws, Penalty Taking, Tackling. All players also had '1' consistency, but this was just for demonstrative purposes as 1 CA cannot go below 1 CA.
Mucking around with the Knap EF 424 IF HP V2 P101 AC tactic didn't seem to do anything beneficial, at best I got the same results. I guess it's also the right place here to point out that I have used only the default Knap tactic and Blue set pieces routines, default Man City club & staff (only players changed), one-shot whole season loads (no savescumming individual matches), and no DM-as-AML positional exploits (though I have in the end, made certain players dual position such as DR/L and AMR/L which has 0 CA cost).
TheBucket said: I'll try to respond in sequence, and sorry for the wall of nothing, I was overthinking what kind of message would resonate and just ended up copping out, I apologize for that.
Of course, it's your experience and your interpretation of why your works and contributions seemed to get drowned out. I don't think its strictly because of a benign username or the manner you present that information that gives you any authority or respect on these subjects. I think anyone that scrolls these forums for 5 minutes will realize you do add immense value to this community and maybe the shift you experienced was a culture shift in how forums operate here, but also people recognizing your hard work and what you told people was leading to better outcomes in how they tested and played. This cuts against my point that the username matters, but I just want to be honest.
1) I do think the quality of content here is very solid, its understandable for even the guy who plays this game a few hours a week, and that's where I agree with your point of if this was more of a formal site it wouldn't thrive. It has its place, and its a great place for more uses than just asking questions that 90% of people here know the answer to.
2) I don't think I'll be the last one who asks about your username and I still stand by the idea you should abandon it, simply because it doesn't represent truth in the way we can both access it.
I appreciate the examples you give and its not my intention to remove politics from places I deem they don't belong, there's a harsh debate that people can have about if claims or statements of fact that are unpopular should be platformed, regardless of harm. My conflict is that this community is a haven for exactly what you said, unfortunate truths of how the game we want to love so much is filled with flaws and cannot be enjoyed the way you used to once that is figured out. Here's the conflict, we ran tests to find out what was true about this game. We understand this game is flawed as shit, pace abusing and strikerless tactics are how you win, and it sucks and most of us have stomached that. We found out something that sucked at expense of truth, so isn't truth the most important thing? That's why when I see your username in a place that values truth above comfort, they are values going in literally opposite directions. The history of this claim that George Floyd overdosed was so hate mongering racists would have a stronger reason to go against the BLM movement. Have your opinions on how that movement panned out and the actual motives behind you (I will probably agree with you), but you cannot tell me with all available evidence, your username leads us closer to the truth, than to a comfort statement. I understand the concept of your username, there are truth statements people need to investigate, no matter how badly it makes me or anyone observing it feel. At the end though, the truth should overcome that comfort. That's why if someone asks me "hey bro how do I get better at FM", I don't tell them to to run a formation that fits your players, or to train weak foots and create balanced players in training. I would expect the same with how you represent yourself, if your username represents a fundamental mistruth, that is for comfort. Expand A man drinks 3 beers and then drives home. He ends up misjudging a turn in the darkness and dies by crashing into a tree. What killed him? The alcohol? 'Blunt trauma'? Noncompliance with the road rules? The tree? What if the government planted that tree there, in a way that constituted gross negligance? If it is the alcohol, does his death make the 3 beers constitute an 'overdose' for him?
Personally I think what 'killed' Mr. Floyd is in the realm of uncertainty. But it was striking to me how in this case where one could nonetheless normally say something like 'I reckon he was drunk', you were condemned as a heretic in past ages would be for questioning the narrative that a knee is what killed him.
Perhaps what inspired me to use the phrase specifically is the analogous nature to how I was treated on the SI forums. You claim something about an uncertain matter, in this case the game's mechanics, and you get harassed by zealots who want to exercise power over you. You see how 'Hitler 2.0' or 'F_U_Miles' just wouldn't capture quite the same intimations.
So that is the meaning behind it, but the practical use of it is obviously that it also prevents direct attribution of my findings by SI sycophants who want to have their cake and eat it too. To me it is amusing to see the debate play out when it does of if my data can even be mentioned given my username, and it also drives something of a wedge then therefore between following SI's orders and making sense of the game. Of course what can be done about this is to simply take the data and strip my name from it. I've made no effort to 'gate' anything, and although I personally do think I have made some substantial findings of my own, EBFM and HarvestGreen have largely captured the limelight and lion's share of the $0 prize pool with their more thorough and extensive findings in their respective areas of investigation. Overall I figure that aside from mere temporary satisfaction of vanity, an upside of posting info is that the mere dissemination of it will hasten SI's demise even if it is not attributed to me.
Now vanity and retribution and amusement may not sound akin to the goal of truth to you, no doubt, but I think you are being a bit too grave about this matter. This does, after all, concern a video game. On a deeper level, I simply just enjoy uncovering the game mechanics, because the game itself became quite boring and tedious for me a few years ago. Sharing discoveries requires different motivations from that. You are driven by your own distinct values and motivations to certain goals, seemingly community through a shared virtue of truth (or is it the other way around?), and I don't object to that per se, except to say that that's not what I'm here for.. or perhaps more accurately, I do not have it as my narrow focus that overrides everything else. That is not to say I am right and you are wrong, an analogy I can come up with of this is that you strongly feel eating should be aligned with bodily health and you do not think I should have my display picture as a delicious cake while giving out effective diet tips. You can imagine this cause celibre playing out on a weight loss forum.
Cptbull said: By coincidence I have been doing that throughout my years of FM. Often cancelling already preset friendlies by assistant manager when starting a new save, just to squeeze that extra moral boost.
I have however never looked at the pitch quality when selecting an opponent. Do you think there is a real correlation there? Expand I was going to say that I've never tested it, but that pitch quality is supposed to have some minor effect on injury risk.
But I asked chatgpt for an SI staff source, and it said that pitch quality doesn't effect injuries. So perhaps I'm mistaken on this one. Closest I could get is that pitch condition affects the match engine.
The issue is not just that the username is provocative. It is that it makes the community look less serious, less evidence-driven, and more tolerant of political bait. Keeping the name creates friction for everyone else, while changing it costs almost nothing and preserves the person’s actual FM contributions. Expand What do I want to say here..
Let's start with what is most pertinent to FM and players of the game.
A few years ago, I donned my sunday best and presented facts about the game on the SI forums in a neutral manner under a bland username. I was pointing out how 'game importance' and 'youth facilities' don't actually effect newgen PA. This was when no one else had discovered this, or at least weren't pointing it out.
The response I got was the same response still being meted out today, which is to be drowned out by mods making 70% of the replies saying you can't say 2+2=4 unless you have a PhD in mathematics, that you need to send your workings to them privately for verification before you can reply to them or others, and that the thread is now closed for the divisiveness and ill-will your claims have engendered and for the sheer arrogance of ignoring the moderators by failing to reply to them.
I preferred your first post rather than the AI slop you replaced it with, but nonetheless I will contend with the heart of what you say. You claim essentially that the content pertaining to FM here would be diluted, perhaps even eviscerated, by the encroachment of politics and no doubt other forms of generalized discussion.
1) I think the quality of the content on this forum is doing just fine, don't you? Certainly a hell of a lot better than what we see on the much larger SI forums that follow the framework for discussion you advocate for. You will always end up with endless posts of 'so what's the best one to use?' and people who want to quibble about usernames and whatnot. I think if you delete all this and turn it into a kind of academic journal, it would flounder, and so I'm glad this place is the way it is right now.
2) FM is inherently political, and therefore some discussion of politics is warranted even if you believe that discussion should be strictly relevant to the game itself. Remember when Brexit got added as a compulsory and frustrating element of the game before Brexit even happened in real life, because Miles wanted to inflict some kind of collective punishment for his fellow countrymen voting for it? What about when he added coming out as homosexual as in-game event? What about when he removed the capital of Israel from the game because he is a radical leftist? What about when FM had 'nation attribute templates' where black people were typecast as stupid and violent, and the response was to deny its existence while quietly doing away with regional variety altogether. And now we have of course the whole women's football thing. Once you go down the path of censoring references to politics, even if there's a fair case to be made for it, you'll find yourself inescapably shutting down discussion on whole swathes of the game, and inevitably it descends from preventing the 'off-topic' and 'hatred' to removing the 'unconstructive' or 'provocative', as one sees now to a comic extent in the 'official FM26 feedback' thread.
Interesting regarding friendlies in pre-season. On older versions I cluttered the schedule with as many pre-season friendlies as possible to get tactical familiarity as high as possible before the season started... Which this site and EBFM-videos has shown me to be useless... Expand I'm glad someone noticed, as I know my posts in this thread were particularly painful to try and skim read. I think I need to redo a summary of all this at some point.
I can add a piece of extra info that I know now. It seems to me that the 'running start' morale impact of pre-season friendly wins have a substantial impact on the chance of winning the competitive season. In other words, it seems best to schedule friendlies against the weakest teams possible, and have enough of them to get your morale up to perfect ideally (balanced against fitness considerations). I suppose it's best to only do home games (win chance boost+pitch control), or otherwise at least pick teams that have stadiums with perfect pitches to minimize injuries. I think two other implications here is not to worry about overconfidence from winning the pre-season friendlies, and fill up any mid-season gaps with a friendly against a weak team.
Normal Man City test
2024: 144, 3.5 star, Aston Villa 134
2025: 126, 2 star, Aston Villa 144
2026: 102, 1 star, Arsenal 113, Aston Villa 133.5
2027: 94.5, 0.5 star, Arsenal 124.5, Aston Villa 124
2028: 119.5, 3 star, Arsenal 122.5, Aston Villa 121
2029: 112, 2 star, Arsenal 103, Aston Villa 126
2030: 103.5, 2 star, Arsenal 120, Aston Villa 125
2031: 120.5, 2.5 star, Arsenal 123, Aston Villa 134
Average: 115.25, Aston Villa 130.1875
Normal Aston Villa test
2024: 136.5, 5 star, Man City 132
2025: 129, 3 star, Man City 138
2026: 90, 0.5 star, Man City 121
2027: 99.5, 3 star, Man City 140
2028: 120, 3 star, Man City 120
2029: 110.5, 3 star, Man City 122
2030: 106.5, 1.5 star, Man City 123
2031: 113.5, 2.5 star, Man City 135
Average: 113.1875, Man City 128.875
Forest Green (league 2) non-player: 70, 91.5
Forest Green player: 52 (note: was 0.5 star)
Exeter (league 2) non-player: 107, 108
Exeter player: 80, 79
Overall this is a relief, because it seems to be the case that the median of all non-player teams doesn't decline or go all over the place in subsequent years. That median variation of -/+ ~10 is normal if you're unfamiliar.
It's only the player team that is affected. And this seems to be consistent across different division levels/club quality.
It's not about existing youth players affecting things, I tested that, and the AI's median remaining unaffected which I found out later is further proof of this.
I thought maybe what's causing it is the manager itself, specifically either the reputation or the player & youngster knowledge of the human manager. But changing those attributes didn't seem to make a difference.
I think that the median being normal in the first year might be a clue as to what's causing it.
(templates:115 CA average)
So does this mean I can set all the aforementioned attributes to 1 in this template?
Or does it mean those attributes were lowered to 1 and other attributes were raised?
Please let me know if there are any templates with a lower CA.
Yes, you'll be fine with players that have '1' in those attributes.
I recommend using my genie scout rating file, it will find you the most CA-efficient players.
You keep saying this so I assume you must actually believe it to be true. I feel like I have to address it even though it's unsubstantiated, because people aren't going to be digging up my posts to check for themselves and they might just assume you're half correct.
I have never said the work of HarvestGreen or EBFM is wrong, except on some niche aspects. For Instance, I think EBFM is wrong specifically about youth facilities making a minor contribution to PA, probably because he used average instead of median as measurement. And I think he is wrong on his 'draft hypothesis' for youth recruitment (though even he wasn't 100% on this theory). But apart from these two things, I don't think I disagree about anything EBFM presented.
With HarvestGreen I think I've only ever disagreed on certain things open to interpretation. For instance I favor a different training schedule to him, but this is because he weights attributes differently in his thinking, i.e. just how negatively should 'decisions' growth be weighted.
I've pushed back against people on a few things. One was about player fitness. Another was about player personality attributes being random or not.
There are more I've forgotten, but the player personality one is one I ended up conceding on. It turned out player personality attributes are not just random, and that wasn't someone's 'work' it was just a claim made that I subsequently tested and changed my mind on. But I really can't think of anything more substantial than that I've had to retract.
White Europe said: Ok great 👍, thanks for answer, just wondered if I want to use other style than gegenpress, or just create my own tiki taka tactic is those ratings still helpful? Or they just to support meta gegenpress tactics?
Whatever tactic you use, the ratings will work well.
The values are necessarily quite a bit airy fairy anyway. The main thing it's doing is that it's prioritizing key attributes that are universally good such as pace, acc, dribbling, work rate, pressure, and so forth. But then when it comes to something like 'long shots' say, maybe that deserves a 1% weighting or maybe it's 11%.. but this is only going to move the overall needle a fraction of a percent anyway. But then if you add up all these little errors together, that might end up being an error of ~3%.
A simple change you could do to tailor it more to other tactics I guess is to simply reduce the pace/acc weighting by ~10-20%. I think that was the gist of the main difference I saw in HarvestGreen's findings of tactic differences.
I was merely questioning why it's taken you this long to determine several things we knew Long time ago. I have noticed multiple times you've declared other people's work and findings wrong, only to later retract and say you made a mistake. You're cosplaying being an elite tester for football manager, but you're sloppy at best.
I only came on to see if strikerless was still meta in 26. But the forum is so full of your posts I had a peek for a laugh. I see above you've mentioned certain attributes are more important for different positions. Is this true?
If you look at your posts page, your last post before the one in this thread was in February saying to me:
keithb said: What a load of shit😂. Do you think we're five years old?! Exposing the truths about football manager has nothing to do with your username.
Clearly you're desperate to be someone in the community, but all you're mainly doing is regurgitating other people's work. Well done. Bravo. You're a nobody. But at least you've got that username, really sticking it to SI!!
And then if you scroll down, there's a few more that are replies to me or about me. Two of them about being upset about my username are from October last year.
What you claim about me in relation to other people's work is simply wrong. Example at hand: Who else is attempting to update FM Genie Scout ratings values, in a way that merges HarvestGreen's findings with positional weighting of attributes?
White Europe said: Guys im new to gennie scout so i have a question:
I have a guy for DM position with 70 rating in general for DM position and 69 for volante role which im using in my tactic and a guy with 68 general rating for DM position but 71 for Volante role: so which rating is more important general or role?? I hope this make sense
Always use the position rating, not the role rating. You can find evidence on this forum that where certain roles will say they don't need acc/pace, they still need it just as much as roles that do have them listed as requirements. Essentially, roles seem misleading and cosmetic.
I suppose it's possible that there are still variations in terms of tactical role. I.e. if you set DL to 'dribble more' maybe it benefits from better dribbling more. But I will say that in trying to adjust one of Knap's top tactics myself along these lines (to suit/fit better a certain set of attributes), I couldn't get better results, so I doubt it matters here either. HarvestGreen has found different attribute results for different tactics used, but the differences weren't that big.
England normal ('very important' ) samples:
119
120.5
113.5
106
118.5
England 'unimportant' samples:
140
143.5
140.5
2nd 'very important' samples:
105.5
111
101
At this point I stopped because there is something extra going on here that is more notable in itself. Still, I think we can pretty much wrap up the game importance thing, as ~140 PA median for Man City (or almost any club really) is about as high as it gets.
But now the matter of these highly variable medians. I have a feeling I already knew this years ago but I have forgotten about it, as I was recalling recently how I would savescum a whole year in advance to see the newgen results instead of reloading just before newgen day, in recent versions, and I couldn't remember why. Now I see it's no doubt because certain things are being set a few months earlier than intake day with the new 'Youth Preview' system.
Honestly I'm still hazy right now on it and I can't really be bothered digging deep into it, but I know this doesn't affect any data I've presented, except this multi-year attempt thing.
It's not to do with facilities, reputation, club coefficients, etc. changing - I double checked all those to make sure. What it does seem to correlate strongly with is your youth intake quality star rating. Yes, this star rating is relative to your existing squad, but it seems also nonetheless to be reflecting the differences in your median PA.
If median PA can vary for even a top club by as much as ~30% randomly, then does knowing the newgen factors even matter at this point? In a way this is a point even I don't want to admit, but it's one reason FM was losing its lustre for me even before FM26, they ruined the fun of newgens. On the other hand, the factors still work, and the year-to-year randomness doesn't mean inherent randomness - it's a dampener for sure, but still means you have a reasonably predictable and consistent system. To illustrate the difference:
Before:
Man City - 140, 143, 135, 146, 148
Arsenal - 136, 129, 138, 139, 139
Now (nation-based year-to-year randomness):
Man City - 140, 110, 115, 130, 145
Arsenal - 136, 107, 110, 119, 142
Inherent randomness (~30%):
Man City - 140, 110, 115, 130, 160
Arsenal - 158, 181, 132, 105, 116
That's if nation-based year-to-year randomness is what is actually going on here. As I said, I'm quite hazy on it right now. I'll probably try and get to the bottom of it sometime down the track. I know this all seems to put things in the wrong direction of progress, and people generally don't like that, but better to acknowledge the setbacks/problems than keep them on the down low and end up fooling myself/others about it.
Oh I didn't realize you're the guy who is obsessed with me. It's been half a year and you're still going on like this. I wanted to communicate to others the points I made anyway.
BaZuKa said: Ok this new file is Giga Broken
Season 3 almost won everything with a low-tier club from Portugal
The first line sunk me for a moment there. It's good to hear it's working well for you, I don't actually know how well in reality these files are going to go.
I keep forgetting to mention things. I used HarvestGreen's 6 > 18 attribute data mainly this time, as using 1-20 overvalues things like pressure and work rate. I figure in cases where pressure or work rate is very low, you can either just filter out those players or train/tutor them up a bit if you do buy them. And getting '20' is less likely as well as more CA-inefficient, so that's another reason I favor the 6>18 measure.
Just piggybacking off this to say that I haven't used the player names/clubs to calibrate my values. There's a good reason for this, and that is that in-game player ratings don't correspond exactly to actual performance.
You can see evidence of this in this OmegaLuke video, where technicals give substantially higher player ratings than physicals, even though physicals actually won all the games. Orion's coefficients, which use in-game player ratings to deduce the best attributes, I've found are outdone by HarvestGreen's data which assesses according to goals scored or games won.
So this is why I don't try and align the values to fit player ratings or the best players, as that would achieve the opposite of what I want to achieve, which is show players who punch above their weight in a way the in-game AI doesn't recognize.
But I think there is some value in comparing the results afterwards, just to make sure one isn't completely off-track. Regardless of rating, we know Haaland gets goals, so if he's not up there then there's something amiss.
Additionally I think it's notable how the starting data closely aligns with physicals matter and technicals don't. If you plug in HarvestGreen's data, it just so happens that the top players start in the top clubs in the game. That sounds as straightforward 2+2=4, except realize that this means that SI knows exactly how the attributes are skewed and disingenuous. If they believed what they tell you about how the game works, then we should see these initial players at top clubs failing to perform. In fact, I think perhaps this in-game rating bias towards technicals is to try and stop AI managers simply buying up completely lopsided physical beasts as the game goes on.
I can think of a reasonable counter-argument or two to the above, but there is also some circumstantial evidence as I see it. If you use Genie Scout default ratings, 7 out of 9 top players (one of each position) are white. If you use HarvestGreen's data it changes to 7 out of 9 being black. Either SI still has a racism problem where black people are portrayed as mentally/technically poor physical beasts, or this is intentional. Or both.
LightningFlik said: Sorry to pile on with demands @GeorgeFloydOverdosed, but can you provide these weights as raw data? That is, I don't think Genie Scout runs on Linux but I'd be interested in seeing what you've come up with.
(No rush, whenever you have time).
OpticFawn said: Yes please, I want to use on personal tool pls
Here are the values for FM24 blended.
I forgot to say that 'sweeper' position is intended to be my attempt at a tutor rating, and for Target Striker I've simply upped jumping reach to 100, as high pace/acc ST is simply better than a slow target man and I'm not sure if heading or whatnot affects the target man's performance (jumping reach certainly matters).
https://files.catbox.moe/owbw3u.grf
FM24 Age 26+/Pure performance:
https://files.catbox.moe/8wskjk.grf
FM24 Blended (recommended):
https://files.catbox.moe/f8hmj7.grf
I haven't done FM26 versions yet and it'll be a while before I do, I recommend just using the FM26 ratings file I did before and replacing the GK ratings with the new values in FM24 Blended. You could use these new files in FM26, but it would be a bit off (still much better than FM Genie Scout default).
I'm increasingly unsatisfied with the result as I've ran into further issues, but I've decided to just put these out there otherwise it'll never get done and it does seem to work better despite the issues.
I've had a dilemma about merging in some of my own findings. One example is that in my 1 CA player testing I found that concentration matters on CB/DL/DR, not other positions. Another is that extra finishing on CBs made no difference to goals scored, which means it's low weight on CBs for a reason. These findings are a part of my previous ratings file, so I wanted to include them again here. But I also figured that my data isn't as strongly evidenced as HarvestGreen's, and some of my conclusions could just simply be wrong. On the other hand, there were a number of different examples which can't all be wrong and it makes sense that different positions benefit from certain attributes to different degrees, so I don't think it's best just to use HarvestGreen's data flatly amongst all players. In the end I decided to just apply a simple -/+25% to a few attributes that I was quite sure had pronounced positional differences. I.e. dribbling 32 > 40, vision 5 > 7. So nothing too drastic, but this leaves me feeling like it is too arbitrary a change and yet it also doesn't go far enough probably. The only reassurance I have is that the actual results seem to be better, which you can see a sample of below.
Another issue I've had is with the new GK data. Initially I just plugged in HarvestGreen's new figures. But looking at the results, I get the impression something isn't quite right with the new data. And if you look at HarvestGreen's old GK data, which only had conceded goals as a measure but was also measuring 10>20 instead of 1>20, you can see there are contradictions. From my own 1 CA player tests, I found that acc & pace seemed best value around ~5-8 rather than 20. And if you look at actual players in the database, a bunch of the best have acc of just 8-10. So I think this is mainly a case of missing the data that shows where ~6-14 is sufficient, which we know some attributes such as work rate are like. So I made some appropriate adjustments. Definitely an improvement on my old ratings file here.
Here are some example results. Two important differences that stand out to me are that the GKs are significantly more correct in the new version (Pickford shouldn't be behind Forster!) and there are no longer 2 japanese players from Celtic in the top 10 ST list (they do have high acc/pace, but this seems an appropriate change). And clearly with Kane as no. 1 ST, FM Genie Scout default ratings are way off.
New (blended):
Pickford 69.53%
Pope 67.67%
Ramsdale 67.43%
Steele 65.41%
Old:
Pope 69.74%
Forster 65.89%
Pickford 65.13%
Ramsdale 65.00%
HarvestGreen (new GK data):
Pope 75.44%
Pickford 73.89%
Ramsdale 72.98%
Butland 72.85%
Actual England selected:
Pickford
Pope
Ramsdale
HarvestGreen data:
Haaland 95.34% (Man City)
Mbappe 93.59% (PSG)
Osimhen 93.39% (Napoli)
Vinicius 92.70% (R.Madrid)
Thuram 90.54% (Inter)
Nunez 89.32% (Liverpool)
Isak 88.71% (Newcastle)
Moffi 88.48% (Nice)
Martinez 88.32% (Inter)
Jesus 88.28% (Arsenal)
New (performance):
Haaland 95.25% (Man City)
Mbappe 93.68% (PSG)
Osimhen 93.65% (Napoli)
Vinicius 92.47% (R.Madrid)
Thuram 90.43% (Inter)
Nunez 89.29% (Liverpool)
Moffi 88.57% (Nice)
Isak 88.52% (Newcastle)
Lukaku 87.99% (Roma)
Maritnez 87.51% (Inter)
New (blended):
Mbappe 84.94% (PSG)
Vinicius 83.95% (R.Madrid)
Haaland 82.94% (Man City)
Osimhen 82.80% (Napoli)
Thuram 80.15% (Inter)
Nunez 80.14% (Liverpool)
Jesus 79.15% (Arsenal)
Isak 79.09% (Newcastle)
Messi 78.83% (Inter Miami)
Martinez 78.65% (Inter)
Old:
Mbappe 77.59% (PSG)
Haaland 77.25% (Man City)
Salah 76.89% (Liverpool)
Vinicius 76.86% (R.Madrid)
Martinez 75.23% (Inter)
Son 73.80% (Tottenham)
Furuhashi 73.10% (Celtic)
Nunez 73.08% (Liverpool)
Maeda 72.92% (Celtic)
Osimhen 72.65% (Napoli)
Default Genie Scout:
Kane 91.47%
Haaland 90.95%
Messi 90.03%
Lewandowski 88.43%
Mbappe 88.30%
Benzema 87.21%
Salah 86.97%
Son 86.51%
Martinez 85.91%
Vinicius 85.71%
I would be interested in your results over a 10-20 year span. At least in Fm24 and all previous versions if Game Importance wasnt set to very high in a decent Youth nation you couldnt produce NewGens even if your were #1 club in the world.
Singapore could never have good players because there youth rating is bad. Czech would be a good test as their youth rating is 90-100+ while game importance is not set to very important.
sortitoutsi even has always listed game importance for finding newgens in their charts.
https://sortitoutsi.net/football-manager-2026-youth-ratings
I dont think this is an issue for most players since most people play in a big nation, build a nation saves arent that popular in the community. So most people wont notice it.
I am honestly probably not explaining myself well. I just know in fm24 and prior when doing build a nation saves even if you changed youth rating to 100 the nation couldnt ever produce wonder kids even when getting league to top 5 and all the clubs in the top 50 if Game Importance wasnt set to very important.
I dont know if there is some kind of time factor and that is why you need to sim 10-20 seasons or what tbh.
I should have mentioned that I used FM24. I guess some will say then what's the point of doing an updated test if you're not going to even use the most recent edition, but for me FM26 just has to be foregone.
I actually completely forgot to do one thing I wanted to do this time, which was to test what it looks like 5-10 years into the future.
I wanted to do USA initially, to address your claim about the MLS exactly, but found newgen intake works a bit differently and I couldn't be bothered trying to work it out. So my plan after that was to choose a nation with low game importance but high youth rating, but there aren't really any that are loadable - and singapore was one of the best options that was left. But this is also why I did Man City, because I had in mind (and generally what people play with) is clubs with top facilities in top nations, and England is no.1 for that.
As I was writing this I was doing my testing, and I was about to say that I've been wrong about game importance all these years, as 5 years in, the Man City (unimportant England) median had slipped to 117.5 PA (155 peak) which is outside of the range one would expect for the 131.166 PA averaged median I had got for the initial year. But then I did the control test (normal England), and that was 122 PA median, and 115.5 PA on the second sample.
This is bringing back what I experienced regarding game importance back when I initially tested it in FM19. No one has so far pointed out that I said game importance has no effect, yet later claim it has a minor effect, but I want to clarify this. As you can see, game importance has a minor effect that is only sometimes apparent. When I started testing it, I used average PA as a measure and so it was invisible to me and I thought it had no effect. Once I cottoned on to median PA being more accurate, I observed that questionable minor effect. In multi-year tests I thought I had borne out its effect, only to be confounded again in the same way this time. So I had to conclude whether a handful of PA difference, some of the time, constituted something real or an illusion. I concluded it was illusory, although the bunching up around the median effect is obviously real. It's a bit difficult to explain this fully if you haven't tried this kind of testing yourself, but basically it's very easy to be hoodwinked by limited samples and the inherent randomness. If I test a club and get 139, 134, 140, 137 then it's very tempting to say this club is a ~137.5 PA club. But then I would get 153 and 145 if I took 2 more samples. So this is why when I saw game importance raising PA by at most ~10% and inconsistently, I put it down to randomness.
I will continue this testing a bit, to clarify results at the 5 year and 10 year mark, as it does require at least 3 (preferably 5) samples to give any reliable indication.
We know it has always has some value, because high CA-PA gap = faster training = higher pace/acc faster.
Therefore a zero CA cost attribute such as 'pressure' that has a significant effect on win rate, is even more valuable than an equivalent attribute that costs CA, say dribbling. But by how much exactly? 2 points of pace and acceleration each perhaps? I prefer to go on the safe side and guesstimate 1-2 points of just pace say (I think about what gets 'sacrificed' to stay within PA limit at the end of ~4 years of training).
But then you have positions such as DM where you can easily max out pace/acc to 20 without hitting the PA cap, at least if you're in a good division (which I think most players are in, or plan to end up in).
So I figure the bonus for DM should be reduced, and conversely the bonus for a CA-tight position such as AML should be increased.
But this leads to the peculiar consequence that positions that benefit most from high pace/acc, such as AML, value them least. Not to mention the fact that lowering the immediate gains (from high pace/acc) for expected future gains that may never even eventuate. And then there are also inherent variables whose expected ranges exceed the capacity of this predictive method. For instance, even assuming everyone uses meta training, one player might go from 15>17 pace, another will go from 14>20.
So in the end what I decided is, I will have a set of values for youth/optimization, a set of values for age26+/team selection/pure performance (which will be very closely aligned with HarvestGreen's findings), and then a blend of the two - which will be the file I recommend to use as switching between files is tedious. Is a 50/50 blend the best? Probably not, but it's the best I can do so far. I have checked in genie scout the actual results of these new values, and it seems to be working as it should - the best players are those from Man City, Barcelona, Real Madrid, etc. as you'd expect. I've looked for outliers that have changed positions the most, and overall I'd say the margin of error could be something like -/+3% genie scout rating, which I think is satisfactory.
Here's an example to give you an idea about things:
Default Genie Scout - Kane 91.47%, Haaland 90.95%, Mbappe 88.30%
Orion's Coefficients (not my file) - Haaland 88.01%, Mbappe 86.31%, Kane 81.63%
My existing file - Mbappe 77.59%, Haaland 77.25%, Kane 67.35%
New file (youth/optimization) - Mbappe 79.73%, Haaland 75.69%, Kane 65.64%
New file (age26+/pure performance) - Haaland 95.34%, Mbappe 93.59%, Kane 82.21%
New file (blended) - Mbappe 85.33%, Haaland 83.74%, Kane 72.46%
Ignore the numbers themselves, it's about how relative they are to each other
Recently, harvestgreen22 released a new test for GK attributes. Can you convert the data to your player rating coeff? @GeorgeFloydOverdosed
I've actually been working on this recently
Initially I was just going to redo the GK, but then I realized I want to take a new approach to the whole thing.
I've ended up not entirely satisfied with the new approach, basically I think it's definitely better but even more arbitrary in a way. It's mostly to do with balancing CA weighting vs. raw performance, and the problematic question is if an attribute gives a slight boost to win rate but on the other hand also only has very low CA weight (or zero CA weight, like personality attributes), do you give that some kind of bonus and if so to what degree? Basically, how much is free CA even worth exactly. So I've come up with a take on this, that also integrates training results with good accuracy (i.e. if meta training is expected to lower passing by 1 over 4 years, I adjust the passing value slightly accordingly - this is more pronounced for pace/acc which will increase by ~4 in youth over 4 years!).
It's largely done now, just have to finish off some positions I don't use like WBL/MC/AMC and also create a FM26 adjusted version before I post it. Will be soon.
I can tell you my last 3 build a nation saves were hungary before I knew about game importance, Andorra and Faroe Islands. Hungary even after 60 years where I gave every club billions and billions to max out their facilities could never produce a NewGen that was as good as IRL national club member. The way you give clubs billions is by buying their horrendous youth players for 10 million each as the board never turns down 10 million offers. So you are buying 30+ players per club eventually. Giving clubs 300 million each season.
Coincidentally it was a recent video by SecondYellowCard where he tested the DoF role that got me thinking that youth recruitment might work similarly. Turns out it likely doesn't, but that's what led me to investigate the 'place of birth' thing.
I haven't been able to find this discord you mention yet, but I've done some testing of game importance anyway, not only to draw a conclusion here but because it's good to retest things once every few years to see if the mechanic has changed and also I'd like further clarity/precision on the distribution effect I mentioned. I retested recently the hidden nation factor thing I assert is the case, and I can confirm it still exists.
'Game Importance' Test results
Singapore unimportant (default) LC sailors:
Sample 1
75,68,57,51,49,49,48,42,42,39,37,36,32,31,31,20
median 42
average 44.1875
range 20-75
height 1.59-1.90, 1.73 median
singapore-wide stats:
range 17-80
10 best player = 73 PA
Sample 2
74,73,71,68,60,54,53,52,51,41,37,35,34,34,30,21
median 51.5
average 49.25
range 21-74
height 1.63-1.87, 1.715 median
singapore-wide stats:
range 15-86
10th best player = 74 PA
Sample 3
89,67,64,64,62,61,59,50,50,48,46,39,34,32,29,20
median 50
average 50.875
range 20-89
height 1.63-1.92, 1.725 median
singapore-wide stats:
range 13-89
10th best player = 69 PA
Singapore very important LC sailors:
Sample 1
59,53,50,48,47,46,45,44,43,39,38,36,32,31,21,21
median 43.5
average 40.8125
range 21-59
singapore-wide stats:
range 12-80
10th best player = 74 PA
Sample 2
78,70,66,66,61,60,60,53,48,46,41,39,38,37,20,17
median 51.5
average 50
range 17-78
height 1.64-1.92, 1.725 median
singapore-wide stats:
range 10-80
10th best player = 70 PA
Sample 3
53,52,48,48,48,47,44,44,44,44,43,31,31,22,20,20
median 44
average 39.9375
range 20-53
height 1.63-1.93, 1.785 median
singapore-wide stats:
range 8-115
10th best player = 71 PA
Singapore unimportant (default) LC sailors average (3 samples):
median 47.833
average 48.104
range 20.333-79.333
singapore-wide stats:
range 15-85
10th best player = 72 PA
Singapore very important LC sailors average (3 samples):
median 46.333
average 43.583
range 19.333-63.333
singapore-wide stats:
range 10-91.666
10th best player = 71.666 PA
England very important (default) Man City:
Sample 1
167,162,160,152,146,144,143,142,137,136,133,128,117,94,83,83
median 139.5
average 139.1875
range 83-167
england-wide stats:
range 30-179
10th best player = 157 PA
Sample 2
172,167,157,155,148,147,146,142,141,134,115,98,97,96,77,64
median 141.5
average 134.75
range 64-172
england-wide stats:
range 30-178
10th best player = 157 PA
Sample 3
178,167,165,160,157,155,148,147,144,142,141,104,89,85,75,58
median 145.5
average 132.1875
range 58-178
england-wide stats:
range 30-180
10th best player = 158 PA
England unimportant Man City:
Sample 1
167,157,149,148,146,145,140,137,117,111,104,98,97,90,85,81
median 127
average 135.75
range 81-167
england-wide stats:
range 34-175
10th best player = 154 PA
Sample 2
160,157,148,148,148,138,136,133,123,122,101,101,92,88,87,75
median 128
average 122.3125
range 75-160
england-wide stats:
range 34-168
10th best player = 154 PA
Sample 3
159,156,153,151,150,150,141,140,140,140,138,116,110,95,93,80
median 140
average 132
range 80-159
england-wide stats:
range 34-168
10th best player = 153 PA
England very important (default) Man City average (3 samples):
median 142.166
average 135.375
range 68.333-172.333
england-wide stats:
range 30-179
10th best player = 157.333 PA
England unimportant Man City average (3 samples):
median 131.666
average 132.687
range 78.666-162
england-wide stats:
range 34-170.33
10th best player = 153.666 PA
Conclusions
Game importance has no strong effect on PA. Previously I had said it bunches up the PA around the median and ends up affecting the PA to the tune of ~10%, and this is what we see. But as I tried to communicate in qualifying that 'it's not directly comparable to the other PA factors so it's hard to pin down a precise figure', it's not a simple flat 10% - in Singapore's case, the effect was 0% or even negative. In England's case, it was an 8% difference, for both Man City and (to a similar degree) the nation as a whole.
The main takeaway from game importance as I see it is that because it bunches up PA around the median, it does actually dampen your wonderkid chances just enough to make one not want to dismiss it entirely, but it's not that significant or consistently applicable as other factors such as junior coaching are. 160 PA instead of 170 PA, in some cases.
I haven't done a deep analysis of it, but just my general impression is that its not that Game Importance is shifting up or down the general quality of the newgens either, and this is somewhat indicated by the low difference in the average as well (2% difference for the Man City samples). I think it's simply bunching up the distribution closer to the median.
I hope this also serves as an illustration of why I use the median instead of the average. The median is pretty stable and therefore predictable unlike the average. While the median can be predicted with strong likelihood of being within a range of -/+ 5 PA or thereabouts with enough samples, the average will end up with an uncertainty range of ~10 PA or more even if you collect many samples.
I included height in the singapore samples as I thought it was interesting to observe; I wondered if its distribution has some correlation, or something in common, with the PA distribution.
This whole thing appears to be purely cosmetic, so don't try and work out how to get better newgens with it. There is no actual competing for newgens, or even newgen generation in these cities, going on.
There are three clubs: Ljubljana, Kamnik, and Maribor.
The rectangle is area the club can draw newgens from.
It is not that newgens are generated at each city and a few of them get picked up, it is that the club generates precisely 16 newgens. There 'place of birth' is probabilistic based on distance from club and 'inhabitants range' of the city. The circles are just to convey the idea of decreasing probability the further you go out from the club location.
Notice how Ljubljana and Maribor each draw ~4 players from their own city, but Kamnik only draws 2 and takes many more from nearby the nearby capital of Ljubljana. This is because Kamnik has low inhabitants range, and Ljubljana is high probability because of proximity + high inhabitants.
I do not think city 'attraction' affects it, I have tested it but the results are not 100% clear but clear enough to rule it out I think. From memory, 'inhabitants range' is also relative to 'inhabitants range' of other cities. That is to say, if Ljubjlana only had 10,000 people, it would still be top dog if all other cities are 1000< pop, but also it would be less commonly the place of birth than if it had 20mil people and others 1000< pop. There are some further nuances that reveal themselves when you try to break it with extremes like this, but since the mechanic is cosmetic, I won't go further into that.
Lastly there is the matter of exceptions. As you can see, sometimes there can be instances outside the rectangle. I don't know what exactly is going on here, I suspect it has something to do with youth recruitment perhaps. Maybe it's even just a randomness factor they've put in to try and better reflect reality.
The most important factor in PA for newgens aka youth intake is your nations' "GAME IMPORTANCE" if it is not set to "Very Important" you will never have any good NewGens even if you played 1000 years. You have the RNG of finding 1 random Star like how some random Asian Island gets 1 star every 50 years or whatever.
I've done a load of build a nation saves and testing. It is pretty easy to test. Max out everything but set game importance to the lowest level and the NewGens will be awful even with everything else Maxxed out.
This is the actual problem with USA in FM as the game importance is set to the lowest setting while everything else is pretty on par with the Big 10 in Europe.
USA in FM cannot generate any USA players for a top 20 National Team. All of the USA National Team NewGens (once the real players retire) will all spawn over seas at other clubs. Because it uses the nations game importance of where the player is spawned at.
USA cannot even spawn MLS caliber players!!!!!!!! USA will literally spawn garbage NewGens in USA.The entire national team will be spawned at overseas club intake.
Game Importance supersedes all other youth settings and mechanics. I am not even sure if SI is aware of it lmao.
If you are playing a top league in a top country you really wont notice anything.
Hear me out, I believe you are largely mistaken on this.
From memory, game importance does have a modest effect on the distribution (low game importance = PA more bunched up around median), but it doesn't change the median or rule out very high PA players occurring entirely. Don't take my word for it, you can see EBFM's test results. Two problems with EBFM's data here is that he didn't look at the distribution as a whole, and he uses average instead of median. I think I've neglected to say before that this is (likely) why EBFM came to a different conclusion about youth facilities, where he found a very slight but consistent increase to PA. This is because he used the average, which isn't reliable with FM's system, and I guess it's possible something is going on here but I'd think if there is it'd probably be that the CA boost from YF is roughly added to the PA (i.e. 36 CA > 40 CA = 120 PA > 124 PA).
I would say that game importance is equivalent to a ~10% PA factor, it's not directly comparable to the other PA factors so it's hard to pin down a precise figure.
That said I haven't tested it in a long time, and it's possible your testing was qualitatively different to what I did. You said you maxed out all other factors. I guess it's possible low game importance has a more pronounced effect in such conditions. But what I do know is that with the default game settings we play with, game importance is almost a negligible factor.
Part of it could also be that because nations do in fact appear to have different (and significant) values set under the hood, it's easy to confuse that with game importance, cities, etc.
I've been doing more testing that I've been sitting on for a while now as I reflect on how to best communicate it. Basically I noticed how newgens have unique 'place of birth' that usually isn't even the club's city, so I thought this might be a clue that would allow me to deduce the hidden nation mechanics.
EBFM got as far as thinking it's probably a national pool & draft process going on. What I've found is that seemingly can't be true. From testing before, I already knew that city, local region, etc. all had zero influence on PA. But now I also know that the whole city system is essentially purely cosmetic. There is a sophisticated mechanic that assigns the place of birth, but it does not affect the newgen PA.
Why this matters:
- There isn't some more sophisticated behind the scenes stuff going on like HoYDs/U18s staff poaching from other cities in the local region or such. This doesn't mean that 'Youth Recruitment' doesn't do anything, it just means that it acts independently with its own mechanism; it doesn't interact with some underlying hidden process regarding cities and pre-newgens floating around the place and whatnot.
- There aren't 'player pools' in cities, therefore there is no player scarcity in regards to 'youth recruitment' in congested areas.
- The PA comes from the club location (nation), not the birth city location.
- 'Local region' doesn't seem to have any effect on...anything. I think it probably simply serves a 'boundary' purpose for editing, i.e. a team coordinates is in south England but is part of a northern local region so it gets counted in the north division.
Teasing out those implications takes some thought itself, but there is more (though less significant) that is difficult to explain without bamboozling someone who hasn't been looking at it for several hours as I have. For instance:
- Newgens come from the city location, not the club location, but they adopt the nationality of the club. This is confusing, and purely cosmetic, but I can illustrate its probable intended purpose with an example: Suppose an American Samoa club is added to USA competition. The club is 'based in' USA for economic travel reasons say, but the youths coming through are born in 'Pago Pago' because it's an American Samoa club.
- You cannot tell whether players are generated first at cities or at clubs, because they are the same thing - the club generates them as having come from cities.
- There is a map coordinate geometry to city/'place of birth' selection, likely a rectangle with decreasing selection probability towards the edges. But there are nuances and even exceptions.
Of course I would have to furnish all the different examples I found to prove my findings, in addition to explaining these abstractions.
Unfortunately it didn't get me any closer to uncovering the hidden nation factor, but what it has shown me is that the newgen recruitment process is probably a lot more simple than previously thought, in regards to PA, and it reinforces that unique nation ID is a key component while staff, cities, whatnot isn't.
For example, your LB has your MC's attributes, your ST has your RB's attributes, your DM has your ST's attributes and so on (leaving goalkeepers alone). Naturally each player's role analysis would be in the toilet but if experiments have revealed that tactics are less impactful than attributes alone, it might also follow that the sum talent of your team is more important than who plays where (assuming you're 1. using a tactic that makes sense and 2. players aren't playing out of position, just wildly out of role).
I've tried this, and found that it doesn't work because as soon as the DM's performance as 'ST' becomes better than DM, he becomes DM+ST.
What can work is you can game it slightly, since FM's role calculations aren't perfect (i.e. overweights technicals/mentals).
Digging deeper, there are certain attributes that do appear to be pooled as a team, or are primarily about order of priority. Obvious example would be finishing, where I found you can win the Premier League with 1 CA players and a ST with 1 finishing, it's just that the bulk of the goalscoring gets shifted to the other position that has the highest finishing. Not sure if it's also being pooled in this case, but having some finishing on at least one player seems beneficial (HarvestGreen's testing show it's a minor-moderate contributing factor).
Can't remember what attributes seemed pooled and which aren't, but overall I'd say the pooled attributes don't contribute much anyway. High pace/acc on all players (except GK) is kind of essential to win.
You might also think that since we're favoring a high pace/acc/drib team, a team of selfish players in an abstract sense, then we should adjust our tactic towards one that gels with that. Either knap's tactic is already tailored towards this perfectly, or this theory just doesn't work in practice, because I've tried a whole bunch of adjustments with this idea and nothing did any better.
I suppose the other thing to mention is that some positions are more cost-efficient than others, and quite significantly so. AMR/AML is the most costly, DM the least. So if had a low PA team, you might favor some sort of tactic with 3 DMs and no AMR/AML. But personally, I just stick with the top knap tactic, which does use AMR/AML (in FM24).
I'm referring to the method that has been done successfully with a 1 CA team before, where strikerless tactic with 6 DM/MC are used because the CA cost for that position is the lowest.
Couldn't really come up with a good single phrase to describe it
Results:
2nd 93pts
1st 99pts
1st 84pts
3rd 73pts
1st 96pts
1st 84pts
1st 91pts
Honestly, I just wanted to share the results. But here are some further thoughts I have derived so far from the testing process:
It shows that HarvestGreen's data is accurate, but also that it works in 20/6/1 attribute scenarios rather than just scenarios where all other attributes are held at 10. In other words, high variability/oscillation of attributes doesn't seem to alter the impact of an individual attribute.
I changed so many things at once that I can't confirm as much as I'd like to right now, but what I can say is that all players had '1' in the following attributes: Decisions, Technique, First Touch, Flair, Leadership, Teamwork. All outfield players also had '1' Bravery, Off The Ball, Corners, Crossing, Free Kicks, Long Shots, Long Throws, Penalty Taking, Tackling. All players also had '1' consistency, but this was just for demonstrative purposes as 1 CA cannot go below 1 CA.
Mucking around with the Knap EF 424 IF HP V2 P101 AC tactic didn't seem to do anything beneficial, at best I got the same results. I guess it's also the right place here to point out that I have used only the default Knap tactic and Blue set pieces routines, default Man City club & staff (only players changed), one-shot whole season loads (no savescumming individual matches), and no DM-as-AML positional exploits (though I have in the end, made certain players dual position such as DR/L and AMR/L which has 0 CA cost).
Of course, it's your experience and your interpretation of why your works and contributions seemed to get drowned out. I don't think its strictly because of a benign username or the manner you present that information that gives you any authority or respect on these subjects. I think anyone that scrolls these forums for 5 minutes will realize you do add immense value to this community and maybe the shift you experienced was a culture shift in how forums operate here, but also people recognizing your hard work and what you told people was leading to better outcomes in how they tested and played. This cuts against my point that the username matters, but I just want to be honest.
1) I do think the quality of content here is very solid, its understandable for even the guy who plays this game a few hours a week, and that's where I agree with your point of if this was more of a formal site it wouldn't thrive. It has its place, and its a great place for more uses than just asking questions that 90% of people here know the answer to.
2) I don't think I'll be the last one who asks about your username and I still stand by the idea you should abandon it, simply because it doesn't represent truth in the way we can both access it.
I appreciate the examples you give and its not my intention to remove politics from places I deem they don't belong, there's a harsh debate that people can have about if claims or statements of fact that are unpopular should be platformed, regardless of harm. My conflict is that this community is a haven for exactly what you said, unfortunate truths of how the game we want to love so much is filled with flaws and cannot be enjoyed the way you used to once that is figured out. Here's the conflict, we ran tests to find out what was true about this game. We understand this game is flawed as shit, pace abusing and strikerless tactics are how you win, and it sucks and most of us have stomached that. We found out something that sucked at expense of truth, so isn't truth the most important thing? That's why when I see your username in a place that values truth above comfort, they are values going in literally opposite directions. The history of this claim that George Floyd overdosed was so hate mongering racists would have a stronger reason to go against the BLM movement. Have your opinions on how that movement panned out and the actual motives behind you (I will probably agree with you), but you cannot tell me with all available evidence, your username leads us closer to the truth, than to a comfort statement. I understand the concept of your username, there are truth statements people need to investigate, no matter how badly it makes me or anyone observing it feel. At the end though, the truth should overcome that comfort. That's why if someone asks me "hey bro how do I get better at FM", I don't tell them to to run a formation that fits your players, or to train weak foots and create balanced players in training. I would expect the same with how you represent yourself, if your username represents a fundamental mistruth, that is for comfort.
A man drinks 3 beers and then drives home. He ends up misjudging a turn in the darkness and dies by crashing into a tree. What killed him? The alcohol? 'Blunt trauma'? Noncompliance with the road rules? The tree? What if the government planted that tree there, in a way that constituted gross negligance? If it is the alcohol, does his death make the 3 beers constitute an 'overdose' for him?
Personally I think what 'killed' Mr. Floyd is in the realm of uncertainty. But it was striking to me how in this case where one could nonetheless normally say something like 'I reckon he was drunk', you were condemned as a heretic in past ages would be for questioning the narrative that a knee is what killed him.
Perhaps what inspired me to use the phrase specifically is the analogous nature to how I was treated on the SI forums. You claim something about an uncertain matter, in this case the game's mechanics, and you get harassed by zealots who want to exercise power over you. You see how 'Hitler 2.0' or 'F_U_Miles' just wouldn't capture quite the same intimations.
So that is the meaning behind it, but the practical use of it is obviously that it also prevents direct attribution of my findings by SI sycophants who want to have their cake and eat it too. To me it is amusing to see the debate play out when it does of if my data can even be mentioned given my username, and it also drives something of a wedge then therefore between following SI's orders and making sense of the game. Of course what can be done about this is to simply take the data and strip my name from it. I've made no effort to 'gate' anything, and although I personally do think I have made some substantial findings of my own, EBFM and HarvestGreen have largely captured the limelight and lion's share of the $0 prize pool with their more thorough and extensive findings in their respective areas of investigation. Overall I figure that aside from mere temporary satisfaction of vanity, an upside of posting info is that the mere dissemination of it will hasten SI's demise even if it is not attributed to me.
Now vanity and retribution and amusement may not sound akin to the goal of truth to you, no doubt, but I think you are being a bit too grave about this matter. This does, after all, concern a video game. On a deeper level, I simply just enjoy uncovering the game mechanics, because the game itself became quite boring and tedious for me a few years ago. Sharing discoveries requires different motivations from that. You are driven by your own distinct values and motivations to certain goals, seemingly community through a shared virtue of truth (or is it the other way around?), and I don't object to that per se, except to say that that's not what I'm here for.. or perhaps more accurately, I do not have it as my narrow focus that overrides everything else. That is not to say I am right and you are wrong, an analogy I can come up with of this is that you strongly feel eating should be aligned with bodily health and you do not think I should have my display picture as a delicious cake while giving out effective diet tips. You can imagine this cause celibre playing out on a weight loss forum.
I have however never looked at the pitch quality when selecting an opponent. Do you think there is a real correlation there?
I was going to say that I've never tested it, but that pitch quality is supposed to have some minor effect on injury risk.
But I asked chatgpt for an SI staff source, and it said that pitch quality doesn't effect injuries. So perhaps I'm mistaken on this one. Closest I could get is that pitch condition affects the match engine.
TheBucket said: TLDR for my comment above
The issue is not just that the username is provocative. It is that it makes the community look less serious, less evidence-driven, and more tolerant of political bait. Keeping the name creates friction for everyone else, while changing it costs almost nothing and preserves the person’s actual FM contributions.
What do I want to say here..
Let's start with what is most pertinent to FM and players of the game.
A few years ago, I donned my sunday best and presented facts about the game on the SI forums in a neutral manner under a bland username. I was pointing out how 'game importance' and 'youth facilities' don't actually effect newgen PA. This was when no one else had discovered this, or at least weren't pointing it out.
The response I got was the same response still being meted out today, which is to be drowned out by mods making 70% of the replies saying you can't say 2+2=4 unless you have a PhD in mathematics, that you need to send your workings to them privately for verification before you can reply to them or others, and that the thread is now closed for the divisiveness and ill-will your claims have engendered and for the sheer arrogance of ignoring the moderators by failing to reply to them.
I preferred your first post rather than the AI slop you replaced it with, but nonetheless I will contend with the heart of what you say. You claim essentially that the content pertaining to FM here would be diluted, perhaps even eviscerated, by the encroachment of politics and no doubt other forms of generalized discussion.
1) I think the quality of the content on this forum is doing just fine, don't you? Certainly a hell of a lot better than what we see on the much larger SI forums that follow the framework for discussion you advocate for. You will always end up with endless posts of 'so what's the best one to use?' and people who want to quibble about usernames and whatnot. I think if you delete all this and turn it into a kind of academic journal, it would flounder, and so I'm glad this place is the way it is right now.
2) FM is inherently political, and therefore some discussion of politics is warranted even if you believe that discussion should be strictly relevant to the game itself. Remember when Brexit got added as a compulsory and frustrating element of the game before Brexit even happened in real life, because Miles wanted to inflict some kind of collective punishment for his fellow countrymen voting for it? What about when he added coming out as homosexual as in-game event? What about when he removed the capital of Israel from the game because he is a radical leftist? What about when FM had 'nation attribute templates' where black people were typecast as stupid and violent, and the response was to deny its existence while quietly doing away with regional variety altogether. And now we have of course the whole women's football thing. Once you go down the path of censoring references to politics, even if there's a fair case to be made for it, you'll find yourself inescapably shutting down discussion on whole swathes of the game, and inevitably it descends from preventing the 'off-topic' and 'hatred' to removing the 'unconstructive' or 'provocative', as one sees now to a comic extent in the 'official FM26 feedback' thread.
Interesting regarding friendlies in pre-season. On older versions I cluttered the schedule with as many pre-season friendlies as possible to get tactical familiarity as high as possible before the season started... Which this site and EBFM-videos has shown me to be useless...
I'm glad someone noticed, as I know my posts in this thread were particularly painful to try and skim read. I think I need to redo a summary of all this at some point.
I can add a piece of extra info that I know now. It seems to me that the 'running start' morale impact of pre-season friendly wins have a substantial impact on the chance of winning the competitive season. In other words, it seems best to schedule friendlies against the weakest teams possible, and have enough of them to get your morale up to perfect ideally (balanced against fitness considerations). I suppose it's best to only do home games (win chance boost+pitch control), or otherwise at least pick teams that have stadiums with perfect pitches to minimize injuries. I think two other implications here is not to worry about overconfidence from winning the pre-season friendlies, and fill up any mid-season gaps with a friendly against a weak team.