I had another go with Luton, doing the player selections more seriously this time and no age limit (I used 26 age limit last time). With a £200k budget per player, I got 14th this time
Still couldn't survive relegation with just free transfers only though
I used filters for pace, acc and jump. This seems important, the only wiggle room is probably 14-15 pace/acc, no less, and jump probably needs to be a minimum of ~10 on every player.
LightningFlik said: My favourite tactic. Is there a concern that your low-CA teams actually aren't good enough to finish fourth on their merits but through the strength of the tactics? I don't want to tell you or any of the other hardworking testers your business but it might be more instructive not to use a tactic that could see even the worst team finish in the top half.
Now it makes sense why that team wasn't comparable in terms of rating to the team who finished fourth in my save. Expand Without a doubt, if I didn't use that tactic or something akin to it, the team would have most likely ended up relegated.
Tactic is actually somewhat more important than attributes. If you take default Luton, no buying high pace/acc players or anything, then using that Knap tactic will get them to ~9th.
This isn't something that bothers me though (aside from gameplay perspective), because if you have a park the bus tactic or whatnot you lose almost every game regardless of what players you have. The best defensive strategy in FM is to go on the offensive. "You can have any colour you want, as long as it's black".
debelizec19 said: Dear @GeorgeFloydOverdosed first thank you for dedicated research work. My question is for inaccurate result in GS. When you say it is inaccurate, do you think that potential attributes are incorrect when allocating values to certain attributes? What I'm trying to ask, lets say we have player with current value for pace 13 and acc 13 and in GS we can see that his max value for those attribures are 17. Does it mean that with proper trainig we will achive those max values for pace and acc or it will be even 20 if we will use training for maximize pace and acc. Hope I'm clear with my question Expand Yes, that's precisely what I have in mind. And also it doesn't tell you the chance of reaching their PA, if you don't have paid version.
So it's inaccuracy (progress rate) on top of inaccuracy (potential rating) on top of inaccuracy (current rating).
CA-PA gap is both a very important factor in progress rate and an indicator of how much your player has room to grow. Because pace/acc is most important, and you can redistribute mental/technical into it if you really need to, high PA becomes less important than the starting distribution (current rating) of your attributes in my opinion.
Out of interest, do you and others run these tests using the same tactics? If you're getting conflicting reports of what attributes matter, it might come down to player roles, which is what the game tells us. Expand No, different tactics are used, and I had forgot in my own mind this factor when I was writing all that.
HarvestGreen has given results for different tactics, even comparing and contrasting the top AI tactics. There were quite a few significant differences, but overall I think it was like ~20% difference max and pace/acc were still king.
I doubt that tactics explain even half the difference between all these attribute tests.
I myself always use Knap's EF 424 IF HP V2 P101 AC tactic. My reasoning is that's popular and it's one of the most successful tactics, so why bother tailoring to say a more defensive tactic. I have been considering trying an 'underdog' tactic out for a change for my low pace/acc testing though, to see if it makes it more viable. I'll report later on how that goes.
Rain said: @GeorgeFloydOverdosed So if you are starting a save with a small club in a small league with little reputation I'm wondering what the best play is. Do you just go for the best players you can get according to current GS rating at the start or would you look for the best potential ratings? Expand
Use current rating + take into account or filter CA-PA gap. Genie Scout potential rating will give you a rough idea how good they can become, but it will be inaccurate.
LightningFlik said: Yeah, precisely. It would have been lovely if the weighted formula produced similar ratings for your artificial player and a real-world example but the real team is clearly regarded as much better.
If you're seeing a certain synergy between some attributes or significant performance gains/drop-off after crossing attribute thresholds, it would suggest that the actual formula is more complicated than just summing up weighted values. It sounds obvious but I wouldn't put it past Sports Interactive given how many corners they've cut.
I think Harvest Green in one of his spreadsheets had a formula which changed weights depending on how high or low the values were; I might try to implement that and compare the players that way. Expand I think what you possibly have in mind is the precise formula for CA which FM Scout did an article on, and EBFM tried to work out but even he couldn't fully figure it out. It is true that essentially the more all over the place your attributes are, the more/less CA it costs.
You may also have in mind, or at least I'll point out, HarvestGreen's synergies he found between certain attributes (invented example: say finishing + composure to be worth more than either separately). He also hypothesizes that for many attributes, the number is proficiency as well as tendency and that that may explain a few things.
For the moment, I'm putting CA aside and just considering what attributes and their numbers are actually required to succeed - an attribute floor to then build on.
Most simply put, yes the way attributes are being calculated is complex. Messy even. I've dug deep into this, finding everything I could about what SI staff have said in regards to how attributes work under the hood and analyzing how things worked in the old CM games. Turned out most of the stuff the SI staff said was rubbish, so I ended up triangulating between the data from HarvestGreen, Orion, and my own 1 CA testing. But even Orion's data I ended up factoring out, and now I'm seeing that what remains isn't the whole truth either.
To communicate this, I have to step back and present the bigger picture to you. Either take my word for it that these results are all substantially different, or go and take a look at the data yourself:
1) ykykyk05251's FM21/FM22 tests that purportedly used mass testing using AI doing knockout tournaments over 40 million matches and then pitting it against human picks in 100,000 matches to determine even ideal positional attributes. Supposedly dribbling is more important than pace for ST, stamina is most important for DL/DR, and decisions is 40% weight for every position.
2) Zippo's tests which seem to have been ongoing for a few years and claims that composure is pointless above 8 and concentration + determination combined is less important than stamina.
3) HarvestGreen's data which says that decisions is ~0% benefit and that concentration is more important than stamina (at both 10 > 18 and 10 > 1).
4) Orion's data that different positions favor different things, but stamina doesn't feature in the top 8 for DL/DR.
5) My 1 CA testing which shows you can win the Premier League with a team of 1 CA players with it mostly just being about having high pace/acc/drib/jump, but also some positional quirks like high concentration for DC/DL/DR but unnecessary on other positions.
6) My 15 pace/acc template, where having a bunch of mental/technical stats at ~13 is strictly necessary to come ~4-5th instead of relegated. And I find that Orion's positional adjustments, or even my own ones like concentration on only DC/DL/DR doesn't work here.
Now is everyone lying, or making serious errors here? I don't think it's either. I think that the process changes at different levels of attributes, in ways that are too difficult to predict and require brute force testing to deduce.
A hypothetical example as how this plays out in the match engine:
AML with 18 pace/acc > exceeds DC's 16 acc (speed rate) and 15 agility (direction change speed) > no further calculations, AML 'escapes' and ends up scoring against GK's reflexes
AML with 16 pace/acc > matched by DC's 16 acc and 15 agil > AML 14 balance challenged by DC 12 strength > DC outmuscle failed > AML decision (8) continue dribble (13 proficiency/tendency) > DC decision (13) slide in with both feet (tackling 13, bravery 14, aggression 15, dirtiness 15) > AML escape (14 balance, 18 agility) or AML deposed of ball (14 balance, 9 agility)
From this hypothetical we can see how when pace/acc 18+, a lot of those technicals/mentals like tackling and bravery become pointless, but if you lower the pace/acc to 16 then the reverse starts becoming true. If you lower pace/acc to 10, probably another process plays out. And yet of course exceedingly high pace/acc is always your best bet.
Then of course there are things like 'pooled' and compensatory attributes to further complicate the process, where it seems to be ok if your ST has 1 finishing, so long as someone else in your team has 7 finishing. Stamina seems necessary to preserve low pace/acc, but with 20 pace/acc you have so much to spare that you can get away with a team of 1 stamina (that's how I'm reading stamina's results anyway).
So returning to Genie Scout ratings, for newly promoted team 15 pace/acc with good mentals/technicals is what works, but what also would work if you could get it is 18+ pace/acc team with limited mentals/technicals. So how do you value mentals/technicals? Something inbetween? Then no one wins, as the 16 pace/acc thing I explain. Different set of values for each? Too much work and I think everyone likes just one simple rating set, plus I think one set is feasible. Like a good knife, it needs to be sharp but have some flex to it, so that even if you *can* have those 18 pace/acc players but miscalculate things and end up with a team of duds/injuries/etc then you'll still survive relegation at least.
captain3 said: In my GS I can't filter by division since all the players belong to "Jupiter Pro League". Does anyone have this problem? Expand
Yeah, I don't how many FM versions it's had this problem, but it's like that now for the FM24 version. This and the long load time and lack of full weighting customization are making me consider FMRTE again.
LightningFlik said: This is surprising to me. I looked at how effective a player like this would be using your blended weights and they don't appear to be anywhere near good enough to achieve a top-four finish.
I created a player using the same attribute values you listed (see screenshot) and calculated his rating at all outfield positions (I gave him 17 jumping reach when calculating centre-back rating). Here's what I got:
| Position | Rating | |----|---------| | FB | 74.4% | | CB | 76.98% | | WB | 73.97% | | DM | 67.56% | | W | 65.42% | | MC | 68.73% | | AM | 69.26% | | ST | 62.37% |
Don't give too much thought to the actual values because my weights are arbitrary but here's the rating of Newcastle's best XI on May 4th, 2025 in my current save (the season is over, they've finished in 4th place):
| Player | Position | Rating | |----|--------|--------| | Nick Pope | GK | 75.65% | | Ferdi Kadıoğlu | DL | 85.35% | | Gianluca Mancini | DC | 77.97% | | Sven Botman | DC | 78.32% | | Tino Livramento | DR | 78.93% | | Alexander Isak | ML | 79.31% | | Joe Willock | MC | 74.17% | | Sandro Tonali | MC | 76.27% | | Joelinton | MR | 74.78% | | Bryan Mbeumo | ST | 69.2% | | Anthony Gordon | ST | 68.2% |
The low-CA player you posted is at least 3-4% worse off than this real team that finished 4th in my game (in 5th place was an even stronger Manchester United). If I make Newcastle play with a defensive midfielder, it picks Tonali and Willock who score 74% each.
If you holidayed with a tactic which isn't considered overpowered, I see this as a bit of an indictment of the weights we've been talking about.
Of course, if you've crunched the numbers yourself and actually find your team is considered much stronger than your closest competition (ideally without the use of Genie Scout thumbing the scale mysteriously) then I'll hold my hands up. This has left me confused though.
EDIT: It strikes me that this might be what you meant when you wrote this:
DOUBLE EDIT: Ignore the CA in the Lewdandowski screenshot. Ignore everything except the ability values and the overall rating. I took the real player and modified his attributes just to see what the formula would spit out. Expand I only semi-understand what you are saying, so forgive me if I'm wrong in assuming that what you are essentially pointing out is that the team of players I said achieve 4th, are not in line with the 'Blended' ratings file I posted, and that your own Newcastle result of 4th (same position) yet with players with significantly higher % rating is further evidence that the Blended file is out of whack.
If that is what you mean, then you are correct. The 'Blended' ratings file is only at best an a guesstimate of what will win you the Premier league. The 15 pace/acc team template is concrete and precise about what achieves ~4th-5th.
Here's the problems though if one is to simply ditch the guesstimates and go with just what is found through brute force trial and error:
1) Attributes have to be realistically achievable. No newly promoted team is going to have a full roster of 18+ pace/acc players, in fact they'll likely have none. Optimals for certain positions won't even exist. And of what is available, you have to set a purchase value limit on it (say £1mil/player for newly promoted team?).
2) The most optimal configuration is the most inflexible. If one uses a 17 pace/acc template as the basis, a single player dipping to 16 could be the difference between 5th and relegation. If one uses my 15 pace/acc template, dips anywhere have the same consequences. I've actually been doing a realistic test of Luton, giving them the best players according to that new 15 pace/acc template that cost less than £500k and they survived relegation but not by much (in my view this is actually pretty good as it shows it's at least viable realistically). When I tried doing it with free transfers only before that, they were relegated.
3) Aiming for avoiding relegation, 4th/5th, or 1st. Long term success or short term best. With the 15 pace/acc template, the idea is that 1st season you come 4th-5th (or at least survive relegation), and then you train up that 15 pace/acc to 18 pace/acc to come 1st through the high pace/acc alone. If you just go with 16 pace/acc players regardless of mentals/technicals, you will get relegated. If you go with old players with better stats and cheap but no future, you will finish mid-high in 1st season but won't win your 2nd season.
4) Genie Scout is particularly bad in dealing with inflexibility. If your players absolutely need at least 14 pace/acc, even 100% pace/acc weight isn't going to guarantee that, only extra filtering for that will. But if you're going to filter anyway, then you may as well set pace/acc to its actual weight rather than just trying to ensure 14+ pace/acc bubbles to the top. But then also sometimes we just won't bother with filters.. so realistically we actually really do need flexibility.
Now let's distill this to the main dilemma. My Genie Scout rating files and HarvestGreen's results (and training) have a heavy physical focus. The idea is to get to that threshold of ~17-18 pace/acc ASAP so no one can catch you and you win everything. But my thinking is, given you need to survive at least the first season or two without that, you have to first work out a way of getting lower pace/acc players to work for you. And it turns out it is possible, but it may be unrealistic or too inflexible. And you kind of have to go one way or the other, because if you pacemaxx (especially with full rest training) you will never get those mentals/technicals back, and more importantly it also turns out that simply taking my template and upping the pace/acc to 16 doesn't make it do much better.
I'm still mulling over this. The Luton result shows that low pace/acc is viable, but not as much I'd hoped. I've got a few ideas, and hopefully at least one of them will sure things up.
I thought I could speed up the process by predicting which attributes matter and which don't, but it turns out I have to throw all my preconceptions out the window and just resort to good ol' trial and error.
A team of these (hiddens ~8-13; DC jump 17) achieves 4th-5th in the Premier League:
I wonder how many people even here actually realize that you can't win the Premier League unless you have all your players at 18+ pace/acc even when you're complimenting it with a few of the key attributes such as dribbling and concentration.
So for instance if I decrease stamina from '13' to '8', my team goes from 4th/5th to bottom half. You might think (as I did), just increase pace/acc to 16 to compensate. But actually in this case doing that does hardly anything. In fact, even if you increase them to 17, you still won't win, but you'll come a close 2nd.
Now if you have perfect hidden attributes then you can have 17.. 16.. even 15 pace/acc, you can win the Premier League no problem, but we're talking about what is realistic here.
Some things to note:
- 17 jump on DC (or some other player perhaps?) is necessary, big difference between 15 and 17 here. - Surprisingly it does not appear that Jumping Reach is an all-or-nothing attribute. There is a clear and important benefit to all players having moderate instead of low Jumping Reach. - Agility, work rate and composure are the least crucial of the remaining attributes, hence why I have lowered them to 10-11 with no adverse consequence for my team position - A lot of attributes are set at '8' because that's what you can roughly expect your minimums to be for a player once you're in the Premier League (even if it's a newgen you signed 3 years ago in League 2 say). This is to make the template as accurate to reality as possible, and yes '8' makes a difference to '1'. Of course players will often have a '3' in something, but you can either train this up or compensate for it in other ways and sometimes it just doesn't matter (i.e. set piece attributes). - Some essential attributes are at '8', but only because the required amount wasn't higher than '8'. This includes vision, finishing, strength for instance.
Now I have tried using HarvestGreen, Orion, my own, etc. data to try and optimize for positional differences. But everything I tried just made the result worse, even gentle adjustments. So I am now faced with 2 options, after being satisfied I've whittled it down to the essential attributes as a whole:
a) Do dozens or hundreds of positional trial and error changes, or b) Give up on it and just go forward with what I have so far
The more I think about it, the more I am convinced to choose (b). I can always return to positional refinement later. Keep in mind I've already tested a lot of different things, and I know from my 1 CA testing that certain attributes are simply universal (i.e. pace, acc, drib is as essential for DC as it is for AMR).
I want to say a few things about 'cities' and whatnot before I forget them.
Singapore has no set local region, yet it produced newgens born in 'Singapore(city)'. No newgens had birth cities other than 'Singapore', even though there are 54 in the database. All other cities had 0 attraction and 'not set' inhabitants range, suggesting that one or both of these settings are required to make it active. Based on other results, I believe only 'inhabitants range' matters here, and that actually 'not set' doesn't inactivate, it only makes those cities very low probability (this part remains questionable). Note that Singapore clubs have all sorts of different Singaporean cities set as their city.
In Slovenia, no cities have a local region set, however attraction and inhabitants range are. Results showed a diversity of birth cities, in frequency corresponding roughly to inhabitants range. Again there is some doubt over the role of 'attraction'. I ended up being content to rule it out as a factor, but further testing may reveal this is mistaken. I actually suspect that why 'attraction' appears potentially correlated at times, is simply because (a) high inhabitants cities tend to be more attractive, and (b) a large city surrounded by towns is obviously likely to be designated as more 'attractive' than a large city without surrounding towns.
Some tests:
Normal (England) - 49 players born in London. Bristol City 122 PA median.
London '1-1000' inhabitants, all others 'not set' - Bristol City 119.5 PA median, 2nd sample 126 PA. Resulted in much greater diversity of city of birth, but did not prevent 'not set' cities from producing players.
London '20,000,001+' inhabitants, all others '1-1000' - 71 players born in London. Bristol city 121 PA median.
London high pop, no local regions - 64 players born in London. Bristol City 127.5 pa median.
Poland-England switch - Bristol City 101.5 PA median. Man City 120 PA (142.5 normal). Lech 133 PA.
France-England switch - Paris SG 159.5 median.
So you can see here that cities & local regions don't affect PA, and also that the number of players being 'born in' certain cities can be influenced but probably not as much or easily as you'd think. The nation ID, or unique division ID, by contrast does matter significantly.
Further implications:
Since newgen production is probabilistic based on just 'inhabitants range' and is initiated by the club (club creates 16 players, not drawn from some regional 'pool' ), then there is no competing for players going on.
Once you start thinking about it, it becomes obvious why you would expect this all to be the case:
- If newgens were 'drafted' or 'poached' from a regional pool, no doubt the game would at least on rare occasion come up with errors, where some clubs wouldn't get their 16th player while another would end up with 17 and shenanigans of that nature. Yet I have never heard of since an error in all the years of FM. - If the above was happening, it sounds like it would be computationally expensive. It would be the first corner to be cut for game optimization. - The best player production cities in the real world also tend to have the greatest club numbers: Buenos Aires, Argentina; Montevideo, Uruguay; London, England. Aside from making club competition for players within cities a difficult thing to pull off in the game correctly for the programmer, the fact is that in Buenos Aires in the game you have 8 clubs in the Argentine Premier Division including Boca and River Plate. - If 'inhabitants range' and/or 'attraction' were used as an absolute measure for newgen quality and/or number, then Mumbai India (20 attraction, 20000001+ inhabitants) would be a goldmine for newgens, yet it isn't (in the game, and in real life). - Local regions serve a purpose in the editor for setting division boundaries where coordinates do not suffice; i.e. a team located in Wales, may actually play in England in real life. Coords fail here, but 'local region' can put the club's city in the right division.
The other part of this is, where exactly does this leave Youth Recruitment?
Youth recruitment still works as a factor, as a pecking order within a division. In fact, youth recruitment makes more sense now, given that I had known before that there is overlap between divisions (i.e. Premier League 140 > 100 median say, Championship 115 > 80 median) instead of Premier League 140 > 100, Championship 99 > 80.
There are other hints in the database that youth recruitment is just relative (i.e. pecking order) rather than absolute. In Turkey players in the top league have YR of 2 to 8. In Jamaica, 8 clubs in Div 1 have YR 20. Tiny nations can have YR 2-3 (San Marino) to YR 20 (Turks & Caicos Islands). This is neither absolute in terms of quality or number of production nor geographic distance.
The fact that it bears no relation to geography in my view is further evidence that there is no underlying 'draft' or 'pool' system going on, as you would expect 'youth recruitment' to be the extent of the club's tendrils into surrounding cities or coordinates of distance.
So there is nothing so sophisticated going on with Youth Recruitment, but it is drawing the better players to drop into unique divisions from somewhere, and that appears to be the national pool, by which I mean a number of hidden factors & values rather than a hidden pool of players within the game. It's clear that each nation or unique division has at least one hidden quality setting that is very significant (see 'Poland-England switch' above for example).
Kamas1 said: What do you thinks about use FM24 Blended (recommended) in FM26? Expand It would be kind of ok because pace/acc dominate and that didn't change, but a few attributes have changed up to 3x and some of them are moderately important not just minor. It wouldn't be as simple as making the attribute 21 > 63 (3x), as that's not how my calculations work and why I haven't done a FM26 version yet.
So I would stick with the old FM26 file I posted for now.
Alternatively you could look at HarvestGreen's differences for FM26, and give a +10 bonus for each +1x for attributes that have 10 weighting or more. I.e. 3x would be 12 > 32, 1.5x would be 25 > 30. That would make things roughly more appropriate for FM26.
I will eventually create a FM26 version, but it will be with my new method that I'm currently working on.
Rain said: Are there certain positions that are more important than others and if so what are they? Thanks Expand Although I haven't tested this, I think the tactic is more important than the positions. Or put another way, the best tactic determines what positions you require.
But there is definitely also a difference in CA required for positions, or what positions are easier to fill.
Starting with the easiest/cheapest: DM, ST, DL/DR, GK, DC, AML/AMR
In terms of what position can have the largest variation in impact, I would say it's DL/DR (has a lot of cheap yet highly impactful attributes, which you should try and take advantage of), then DC (expensive and rarer attributes but crucial, things like pace/acc, dribbling and jumping reach), then AML/AMR (mainly just needs high pace/acc which is very costly, but also has some cheap beneficial extras such as jumping reach and defensive attributes but these are also hard to find).
The DM requires very little CA, and ST can be whittled down to pace/acc with jump reach, dribbling semi-optional, and finishing almost completely optional. GK doesn't have freebies, is only 20% impact of outfield player according to HarvestGreen, and either already has the required agility/reflexes/aerial reach or they don't.
Is this 20% scale still the case? If so then I think it's not a coincidence that mental/physical/technical/goalkeeper attributes are internally stored as values 1-100 and personality attributes are 1-20.
If Genie Scout doesn't normalise these values then it's multiplying the personality weights against values that are one-fifth those of M/P/T/G attributes. Expand If you clear everything and make 'professionalism' 100 weight, players with 20 professionalism will have 20% rating. Here's someone else who discovered this and he lists the affected attributes. If you don't use it alone in your weights, you'll find it is a negative modifier on the rating.
But if you take the 'blended' ratings and do -21 to professionalism, +21 to pace, the rating will only change from 72.4% to 70.8% say. If you do -14 dribbling, +14 professionalism, it might go from 65.3% to 66.0%. So overall it seems to be working as its supposed to, but imperfectly.
I thought of the feet thing, and position proficiency. The Mbappe-Salah case rules this out specifically, as they are both the same, apart from a slight foot difference that should be a mere fraction of 1%. I would guess that what is going on, if you haven't made a mistake/change in your own calculations (i.e. perhaps you left out something like -27 for injury proneness), is that the personality attributes, injury proneness, natural fitness, etc. are exacerbating each other's minor errors in being combined, creating a large overall error. That's just a guess though.
You may be on to something in saying that it could be to do with attributes being 100 vs personality being 20. Could be why Genie Scout is doing it this complicated way in the first place.
LightningFlik said: Apologies if I've missed this somewhere @GeorgeFloydOverdosed, but at what point (if any) do we start to penalise a player for having reduced competency in a position for which they're being rated (e.g. I think Vini has 16/20 for Striker but is considered to be the second best in the world by your blended metric)?
I will have more dumb questions later as soon as I organise them.
EDIT: I might as well ask this one now, while it's fresh. When you rated players according to various weights and formulae in this post, where did the player data come from?
I ask because I tried recreating the calculations manually (using, for example, the Genie weights you attached via screenshot earlier) and got a completely different order of players when looking for the best strikers in the world.
I created a new game in FM 24, July 3rd 2023, and got the following when calculating using your Fast Striker weights:
1. Erling Haaland 2. Mohamed Salah 3. Kylian Mbappé 4. Lautaro Martínez 5. Marcus Rashford 6. Victor Osimhen 7. Robert Lewandowski 8. Lionel Messi 9. Randal Kolo Muani 10. Romelu Lukaku
I did get it working when using HarvestGreen's new GK weights but either we're using different data for strikers or I'm incorrectly guessing how Genie Scout calculates ratings via weights (it is the sum of all attributes multiplied by their respective weights, right?) Expand So it turned out the Genie Scout thing was mostly a false alarm
If you isolate personality/negative attributes, it does weird things, but in standard use +21 professionalism is in fact equivalent to +21 pace or +21 tackling. It's not 100% exact though, it can change the results ~2-3%, probably because it's doing this unusual non-linear thing.
It is concerning though that you find Salah to be ahead of Mbappe. That's a 7.5% difference. Not sure what's going on with that.
The Genie Scout problem has thrown a spanner in the works at the moment that I need to work out first, but here's what I've been working on for the next version:
So I know that you can win the Premier League consistently with 1 CA players so long as they all have just about 20 pace/acc. But of course this isn't realistic to have.
On the other hand, what is realistic is that you can take a bunch of ~12-14 pace/acc players and get them to 16-18 pace/acc with ~4 years of meta training. 16-17 pace/acc for all outfield positions is the minimum you need to win the Premier league. So winning in the end, isn't really an all too difficult challenge anymore, and it gets easier if it's Championship or lower level.
Now if you take a look at starting top Premier league players in the game, you'll see quite a few with 14 pace/acc, which got me thinking. First, it means it's probably possible to have mentals/technicals be enough to make up for the low pace/acc, to the extent of 14 pace/acc. Second, that elevating mentals/technicals just enough to allow for 15 or lower pace/acc should be the name of the game now.
As it turns out, it's difficult to make even 15 pace/acc viable, but it is possible, even with a whole bunch of attributes left at '1' and others at a reasonable '13' it would win the league. But when I was initially testing it, I left the players with perfect 0 CA cost stats.
I realized I had to make it fully realistic, reducing all those 0 CA stats to ~13 as well, which reduced performance quite a lot. At the moment I'm getting results of ~7th, but the conclusion I've come to is that for the Premier League, that's good enough for a first season. The idea would be, tailor the Genie Scout ratings to get these 15 pace/acc 13 other guys for a 1st season mid-table finish (if newly promoted team) and then reach 16-18 pace/acc through training/purchases the following year for a guaranteed win.
Here's an example (DL/DR) of where I'm at so far (a team of players like this achieved 7th):
The plan is to keep reducing each attribute one by one until I whittle it down to the essentials. Then I can test some positional variety (maybe only DC/DL/DR need higher concentration) and then make some final adjustments for CA weight and pull things a little closer to HarvestGreen's findings on mentals/technicals just to be safe (some attributes I discard initially might have a small beneficial effect I didn't notice anyway). Training will also be taken into account, to the extent its still relevant. I am also testing in the Championship, as I feel it's important to be able to win that.
This will be more transparent, less arbitrary, and closely aligned to real results in a real and popular league.
LightningFlik said: Apologies if I've missed this somewhere @GeorgeFloydOverdosed, but at what point (if any) do we start to penalise a player for having reduced competency in a position for which they're being rated (e.g. I think Vini has 16/20 for Striker but is considered to be the second best in the world by your blended metric)?
I will have more dumb questions later as soon as I organise them.
EDIT: I might as well ask this one now, while it's fresh. When you rated players according to various weights and formulae in this post, where did the player data come from?
I ask because I tried recreating the calculations manually (using, for example, the Genie weights you attached via screenshot earlier) and got a completely different order of players when looking for the best strikers in the world.
I created a new game in FM 24, July 3rd 2023, and got the following when calculating using your Fast Striker weights:
1. Erling Haaland 2. Mohamed Salah 3. Kylian Mbappé 4. Lautaro Martínez 5. Marcus Rashford 6. Victor Osimhen 7. Robert Lewandowski 8. Lionel Messi 9. Randal Kolo Muani 10. Romelu Lukaku
I did get it working when using HarvestGreen's new GK weights but either we're using different data for strikers or I'm incorrectly guessing how Genie Scout calculates ratings via weights (it is the sum of all attributes multiplied by their respective weights, right?) Expand If I recall correctly, 18 position competency is same as 20. If it is 16, you do need to take that difference into account. Genie Scout does adjust rating using position proficiency, but it's probably somewhat inaccurate.
Your second question perplexed me for a while, but I think I get what's happening now. You are using the same start date/vanilla game data, but your manual calculation (WITHOUT using Genie Scout) does not match my Genie Scout results.
I haven't done the math on it myself, but this could indeed be a Genie Scout problem. If I clear the rating data and just make it acc 100 for ST, then I end up with a player with 16 acc equal to one with 17 acc (both are 20 position proficiency). I found 2 more examples, and it's clear that the extra footedness is making the extra contribution.
But that would only be a small part of the difference here.
It turns out Genie Scout isn't weighting all attributes equally. This has always been at the back of my mind, but I figured we've got what we've got and ended up neglecting this even as I got more seriously into it. Thankfully it turns out to only affect the personality attributes and ones with negative values.
Personality attributes are valued at 20% of physical/mental/technical. This unfortunately means attributes like 'pressure' will have to be hard-capped at 20%. EDIT: It is unfortunately more complicated than this.
Negative attributes like injury proneness work strangely. '100' acc, '-100' injury makes 65% go to 22%, so a 65% reduction.
There is also an up to 6% discrepancy occurring. I thought maybe Genie Scout is assessing values non-linearly, but even when controlling with identical weighted attributes/proficiency/feet, I get 3 STs that are 74.00%, 73.00%, 72.00%. And it seems like all possible correlates are ruled out too, as far as I can tell, which suggests it might be just a bug. Overall it seems like it would add ~2% margin-of-error to the results, which is moderately significant.
This is all a genie scout problem, so I would think your own calculated player rankings are correct and you should use them.
tl;dr for anyone using the Genie Scout files, it turns out personality is just not working in a way I can understand in Genie Scout, and I don't have a solution right now. I'll probably take a few days to work this out.
keithb said: Stamina is definitely ahead of those. Its very important for midfield and full backs. I thought you had done some kind of values by position? Anticipation might also be ahead.
I just asked a question. You said your tests got other results? Expand No. I could win the premier league with a team of 1 CA players that have 1 stamina. And the reason stamina was left at 1 was because I found increasing it had no statistically significant effect, at least not any greater than 10 or so other attributes.
That does not mean that stamina does nothing, but it demonstrates that stamina is far from essential, even for DL/DR. HarvestGreen's data shows 6 > 18 stamina is +8.1% win rate, which is less than concentration (+8.6%), which was the last attribute I included on my toplist.
It's one thing to posit challenges based on your own intuition, nothing wrong with that. And even arrogance has preservation of dignity as is its virtue. But where is the dignity in insulting me only to piss up into your own face in front of everyone?
Kma said: @GeorgeFloydOverdosed Please do you have in-game filters for the vanilla game ? I don't use GS and other fm lab files Expand I did before. They're somewhere, but I recommend just filtering for some key attributes, say this (for adult player):
pace/acc 12 drib 8 concentration 8 (on DC/DL/DR only) work rate 6
at this point do you think this is the best one? Expand I definitely recommend the new ones over the old file. It's an improvement in spite of the flaws.
If i understand it right, with this new file the attributes of acceleration and speed are not as valued, also taking into account the issue of training and possible growth. However, I am using the fm match lab training file, will it have an impact on the development of speed and acceleration and therefore will this have an effect on this ratings?
I hope you can understand my question Expand Not that familiar with FM Match Labs, but I think they change everything up to balance things right? So it will make the ratings less accurate, but not by that much. The main things being considered are performance and CA cost, and the training bonuses/penalties I've treated as the strawberry on top.
Honestly, I'm thinking of doing another redo from scratch that will use a more grounded method that I can present more clearly and transparently.
keithb said: You dont think stamina is important for a full back? Definitely ahead of jumping, balance and strength. I would also include work rate.
Later on you go on to say you had to accept harvest green was correct about some things. Had you previously said he was wrong?
Sorry im obsessed again but your attributes for full back seem wrong. Expand Concentration 25 was the last on that list. Stamina is 17. I missed work rate, which is 31. Balance and Jumping Reach have 2 weight, stamina is 6 weight, so it's apples and oranges.
No I did not previously say HarvestGreen was wrong, I simply meant that in assessing the performance of balance & strength I trust his results because I know other attributes he gives values for are pretty precisely correct. Part of it is that his own results has changed, due to him using a new method, but mainly it is that I have taken 6 > 18 results as the basis instead of 1 > 18 results (since it is unlikely we would sign players with 1 strength, or otherwise be unable to train them to ~6).
keithb said: I will say again multiple times you have boldly declared other's work and findings to be wrong, only at a later date to retract and say you were wrong. Once is fine, maybe even twice. But you were prolific. Expand Instead of providing a single example demonstrating the above claim, you are instead trying to ask me now 'what about this one.. i-is that a time you said HarvestGreen was wrong??'
LightningFlik said: Sorry if this seems like a dumb question but what do you mean by "max required"? Do you mean that the positive impact from an attribute is capped at this value? Expand Yes, benefit tails off greatly or is statistically insignificant above that value.
rfsm said: Using the blended file for the GS ratings and can someone explain me why Martim is better than Baio?
Based on the physical side always assumed it would be the other way around. Expand Assuming you're assessing for DR position, then the main attributes for DR are pace, acc, drib, jump, bal, injury, str, concentration.
So at a glance they look fairly even, trading 3 points of pace/acc for ~13 points of ~30% valued other attributes. Not to mention Martim is doing it with 8% less CA cost, but this isn't part of the rating, just one of the goals.
I agree with you though that at a glance, it wasn't obvious that Martim was as good as Baio, but the math seems to check out.
Keep in mind that 'blended' devalues pace/acc a bit compared to other attributes, because it's imbued with the expectation that over ~4 years of training, pace/acc will grow but technicals/mentals will stagnate/decline. But even if you use the 'performance' file, they will probably still be near even given the math above.
I know I'm blathering too much, but I would also like to say that my old file values pace/acc more, but I simply had to accept what HarvestGreen's results are showing. Based on my 1 CA tests, I don't see evidence for balance and strength being worth ~30% weighting, but his results have always ended up being on the money so I decided to accept and include it.
Panneton0 said: I am currently trying a Youth Academy Challenge, which makes me unable to buy players, and only use my academy newgens.
With that in mind, I'm trying to put together the best way to approach the GS rating files you provided (I am on FM26 so I know they are not fully compatible, but I am wondering about the philosophy of it anyways, more than the actual scores). In this challenge, I only want to assess my own team a) probable best performers b) probable future best performers. But I don't need to find players who are "good even if low CA" because anyways I have a fixed roster and can't try to find a cheap hidden elite.
The "pure performance" file would provide me with an indication of probable best performers in my team. That part seems straightforward.
But is the "youth" file as relevant in that context? Wouldn't a player's potential, rated by the "pure performance" file, be a better prospect than a player with good "youth" rating? Do we know how GS rates "potential" of a player is computed? Is it simply considering a direct scaling of their current attributes as if linearly scaled up to their PA?
Sorry if these questions are unclear, I'm still trying to wrap my head around all this! Expand How GS computes potential is not known to me, and really I should have thought before to say bluntly that using GS 'potential' rating is probably too inaccurate with my files.
We've all used it for years, or at least I know I have, but just as with the rating values it's just not accurate enough anymore given what we know now. It would still give you a good indication of whether the player has room to grow or not, and that's a key thing, but we know that attribute distribution matters more than PA now. So I would look at current rating + PA + CA-to-PA gap + overall picture (i.e. injury 18 would rule a player out for me), and make a judgement based on that.
In your case I would still use the 'youth' file, as it optimizes for low CA (therefore can attain higher peak performance later) and takes into account the effect of training over ~4 years. If you're choosing youth to play first team games, then just switch to 'performance' for that temporarily to assess (or use 'blended' ).
If you just use the 'performance' file or similar, even if you intend to use this youth player in your first team straightaway then he will probably be subpar first team player at first (very few youth would have the pace/acc required immediately), and then a limited player later (high pace/acc, but low mentals/technicals that never grow).
tam1236 said: I have the same feeling from my long-time savescummings (actually just tests - I played whole, normal season after that). The general shape of your newgens is decided during a previous intake-day. It can bye modified by youth facilities etc, by random-generator in intake-day, but not so much (and maybe this is a mysterious hidden factor - for example you don't have facilities which you do have next year). And that's why first intake is much better - it is "half-blind-generated" in a different way maybe during generating profile when starting new game? I need two weeks to be 100% certain. Expand Yes, it's a good possibility that the game is simply giving it a running start for the first year.
Looking back at the original post of this thread, I realized this could all be a symptom perhaps of affiliate clubs. I had forgotten about this since it was over half a year ago, but I said that affiliate clubs reduced median PA for Man City by ~15-20, which is the same drop we see. And it would make sense that players from affiliates don't come through in the first year. But then again Aston Villa, Exeter and Forest Green shouldn't really suffer from this problem.
EDIT 2: It's not 'youth importance' of the club either. I've tested youth importance before and found it does nothing for PA, but I thought maybe there's a multi-year effect I somehow missed.
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.
Still couldn't survive relegation with just free transfers only though
I used filters for pace, acc and jump. This seems important, the only wiggle room is probably 14-15 pace/acc, no less, and jump probably needs to be a minimum of ~10 on every player.
Example of those that achieved 14th:
Now it makes sense why that team wasn't comparable in terms of rating to the team who finished fourth in my save.
Without a doubt, if I didn't use that tactic or something akin to it, the team would have most likely ended up relegated.
Tactic is actually somewhat more important than attributes. If you take default Luton, no buying high pace/acc players or anything, then using that Knap tactic will get them to ~9th.
This isn't something that bothers me though (aside from gameplay perspective), because if you have a park the bus tactic or whatnot you lose almost every game regardless of what players you have. The best defensive strategy in FM is to go on the offensive. "You can have any colour you want, as long as it's black".
My question is for inaccurate result in GS. When you say it is inaccurate, do you think that potential attributes are incorrect when allocating values to certain attributes? What I'm trying to ask, lets say we have player with current value for pace 13 and acc 13 and in GS we can see that his max value for those attribures are 17. Does it mean that with proper trainig we will achive those max values for pace and acc or it will be even 20 if we will use training for maximize pace and acc. Hope I'm clear with my question
Yes, that's precisely what I have in mind. And also it doesn't tell you the chance of reaching their PA, if you don't have paid version.
So it's inaccuracy (progress rate) on top of inaccuracy (potential rating) on top of inaccuracy (current rating).
CA-PA gap is both a very important factor in progress rate and an indicator of how much your player has room to grow. Because pace/acc is most important, and you can redistribute mental/technical into it if you really need to, high PA becomes less important than the starting distribution (current rating) of your attributes in my opinion.
LightningFlik said: Messy, messy, messy.
Out of interest, do you and others run these tests using the same tactics? If you're getting conflicting reports of what attributes matter, it might come down to player roles, which is what the game tells us.
No, different tactics are used, and I had forgot in my own mind this factor when I was writing all that.
HarvestGreen has given results for different tactics, even comparing and contrasting the top AI tactics. There were quite a few significant differences, but overall I think it was like ~20% difference max and pace/acc were still king.
I doubt that tactics explain even half the difference between all these attribute tests.
I myself always use Knap's EF 424 IF HP V2 P101 AC tactic. My reasoning is that's popular and it's one of the most successful tactics, so why bother tailoring to say a more defensive tactic. I have been considering trying an 'underdog' tactic out for a change for my low pace/acc testing though, to see if it makes it more viable. I'll report later on how that goes.
Use current rating + take into account or filter CA-PA gap. Genie Scout potential rating will give you a rough idea how good they can become, but it will be inaccurate.
If you're seeing a certain synergy between some attributes or significant performance gains/drop-off after crossing attribute thresholds, it would suggest that the actual formula is more complicated than just summing up weighted values. It sounds obvious but I wouldn't put it past Sports Interactive given how many corners they've cut.
I think Harvest Green in one of his spreadsheets had a formula which changed weights depending on how high or low the values were; I might try to implement that and compare the players that way.
I think what you possibly have in mind is the precise formula for CA which FM Scout did an article on, and EBFM tried to work out but even he couldn't fully figure it out. It is true that essentially the more all over the place your attributes are, the more/less CA it costs.
You may also have in mind, or at least I'll point out, HarvestGreen's synergies he found between certain attributes (invented example: say finishing + composure to be worth more than either separately). He also hypothesizes that for many attributes, the number is proficiency as well as tendency and that that may explain a few things.
For the moment, I'm putting CA aside and just considering what attributes and their numbers are actually required to succeed - an attribute floor to then build on.
Most simply put, yes the way attributes are being calculated is complex. Messy even. I've dug deep into this, finding everything I could about what SI staff have said in regards to how attributes work under the hood and analyzing how things worked in the old CM games. Turned out most of the stuff the SI staff said was rubbish, so I ended up triangulating between the data from HarvestGreen, Orion, and my own 1 CA testing. But even Orion's data I ended up factoring out, and now I'm seeing that what remains isn't the whole truth either.
To communicate this, I have to step back and present the bigger picture to you. Either take my word for it that these results are all substantially different, or go and take a look at the data yourself:
1) ykykyk05251's FM21/FM22 tests that purportedly used mass testing using AI doing knockout tournaments over 40 million matches and then pitting it against human picks in 100,000 matches to determine even ideal positional attributes. Supposedly dribbling is more important than pace for ST, stamina is most important for DL/DR, and decisions is 40% weight for every position.
2) Zippo's tests which seem to have been ongoing for a few years and claims that composure is pointless above 8 and concentration + determination combined is less important than stamina.
3) HarvestGreen's data which says that decisions is ~0% benefit and that concentration is more important than stamina (at both 10 > 18 and 10 > 1).
4) Orion's data that different positions favor different things, but stamina doesn't feature in the top 8 for DL/DR.
5) My 1 CA testing which shows you can win the Premier League with a team of 1 CA players with it mostly just being about having high pace/acc/drib/jump, but also some positional quirks like high concentration for DC/DL/DR but unnecessary on other positions.
6) My 15 pace/acc template, where having a bunch of mental/technical stats at ~13 is strictly necessary to come ~4-5th instead of relegated. And I find that Orion's positional adjustments, or even my own ones like concentration on only DC/DL/DR doesn't work here.
Now is everyone lying, or making serious errors here? I don't think it's either. I think that the process changes at different levels of attributes, in ways that are too difficult to predict and require brute force testing to deduce.
A hypothetical example as how this plays out in the match engine:
AML with 18 pace/acc > exceeds DC's 16 acc (speed rate) and 15 agility (direction change speed) > no further calculations, AML 'escapes' and ends up scoring against GK's reflexes
AML with 16 pace/acc > matched by DC's 16 acc and 15 agil > AML 14 balance challenged by DC 12 strength > DC outmuscle failed > AML decision (8) continue dribble (13 proficiency/tendency) > DC decision (13) slide in with both feet (tackling 13, bravery 14, aggression 15, dirtiness 15) > AML escape (14 balance, 18 agility) or AML deposed of ball (14 balance, 9 agility)
From this hypothetical we can see how when pace/acc 18+, a lot of those technicals/mentals like tackling and bravery become pointless, but if you lower the pace/acc to 16 then the reverse starts becoming true. If you lower pace/acc to 10, probably another process plays out. And yet of course exceedingly high pace/acc is always your best bet.
Then of course there are things like 'pooled' and compensatory attributes to further complicate the process, where it seems to be ok if your ST has 1 finishing, so long as someone else in your team has 7 finishing. Stamina seems necessary to preserve low pace/acc, but with 20 pace/acc you have so much to spare that you can get away with a team of 1 stamina (that's how I'm reading stamina's results anyway).
So returning to Genie Scout ratings, for newly promoted team 15 pace/acc with good mentals/technicals is what works, but what also would work if you could get it is 18+ pace/acc team with limited mentals/technicals. So how do you value mentals/technicals? Something inbetween? Then no one wins, as the 16 pace/acc thing I explain. Different set of values for each? Too much work and I think everyone likes just one simple rating set, plus I think one set is feasible. Like a good knife, it needs to be sharp but have some flex to it, so that even if you *can* have those 18 pace/acc players but miscalculate things and end up with a team of duds/injuries/etc then you'll still survive relegation at least.
Yeah, I don't how many FM versions it's had this problem, but it's like that now for the FM24 version. This and the long load time and lack of full weighting customization are making me consider FMRTE again.
LightningFlik said: This is surprising to me. I looked at how effective a player like this would be using your blended weights and they don't appear to be anywhere near good enough to achieve a top-four finish.
I created a player using the same attribute values you listed (see screenshot) and calculated his rating at all outfield positions (I gave him 17 jumping reach when calculating centre-back rating). Here's what I got:
| Position | Rating |
|----|---------|
| FB | 74.4% |
| CB | 76.98% |
| WB | 73.97% |
| DM | 67.56% |
| W | 65.42% |
| MC | 68.73% |
| AM | 69.26% |
| ST | 62.37% |
Don't give too much thought to the actual values because my weights are arbitrary but here's the rating of Newcastle's best XI on May 4th, 2025 in my current save (the season is over, they've finished in 4th place):
| Player | Position | Rating |
|----|--------|--------|
| Nick Pope | GK | 75.65% |
| Ferdi Kadıoğlu | DL | 85.35% |
| Gianluca Mancini | DC | 77.97% |
| Sven Botman | DC | 78.32% |
| Tino Livramento | DR | 78.93% |
| Alexander Isak | ML | 79.31% |
| Joe Willock | MC | 74.17% |
| Sandro Tonali | MC | 76.27% |
| Joelinton | MR | 74.78% |
| Bryan Mbeumo | ST | 69.2% |
| Anthony Gordon | ST | 68.2% |
The low-CA player you posted is at least 3-4% worse off than this real team that finished 4th in my game (in 5th place was an even stronger Manchester United). If I make Newcastle play with a defensive midfielder, it picks Tonali and Willock who score 74% each.
If you holidayed with a tactic which isn't considered overpowered, I see this as a bit of an indictment of the weights we've been talking about.
Of course, if you've crunched the numbers yourself and actually find your team is considered much stronger than your closest competition (ideally without the use of Genie Scout thumbing the scale mysteriously) then I'll hold my hands up. This has left me confused though.
EDIT: It strikes me that this might be what you meant when you wrote this:
DOUBLE EDIT: Ignore the CA in the Lewdandowski screenshot. Ignore everything except the ability values and the overall rating. I took the real player and modified his attributes just to see what the formula would spit out.
I only semi-understand what you are saying, so forgive me if I'm wrong in assuming that what you are essentially pointing out is that the team of players I said achieve 4th, are not in line with the 'Blended' ratings file I posted, and that your own Newcastle result of 4th (same position) yet with players with significantly higher % rating is further evidence that the Blended file is out of whack.
If that is what you mean, then you are correct. The 'Blended' ratings file is only at best an a guesstimate of what will win you the Premier league. The 15 pace/acc team template is concrete and precise about what achieves ~4th-5th.
Here's the problems though if one is to simply ditch the guesstimates and go with just what is found through brute force trial and error:
1) Attributes have to be realistically achievable. No newly promoted team is going to have a full roster of 18+ pace/acc players, in fact they'll likely have none. Optimals for certain positions won't even exist. And of what is available, you have to set a purchase value limit on it (say £1mil/player for newly promoted team?).
2) The most optimal configuration is the most inflexible. If one uses a 17 pace/acc template as the basis, a single player dipping to 16 could be the difference between 5th and relegation. If one uses my 15 pace/acc template, dips anywhere have the same consequences. I've actually been doing a realistic test of Luton, giving them the best players according to that new 15 pace/acc template that cost less than £500k and they survived relegation but not by much (in my view this is actually pretty good as it shows it's at least viable realistically). When I tried doing it with free transfers only before that, they were relegated.
3) Aiming for avoiding relegation, 4th/5th, or 1st. Long term success or short term best. With the 15 pace/acc template, the idea is that 1st season you come 4th-5th (or at least survive relegation), and then you train up that 15 pace/acc to 18 pace/acc to come 1st through the high pace/acc alone. If you just go with 16 pace/acc players regardless of mentals/technicals, you will get relegated. If you go with old players with better stats and cheap but no future, you will finish mid-high in 1st season but won't win your 2nd season.
4) Genie Scout is particularly bad in dealing with inflexibility. If your players absolutely need at least 14 pace/acc, even 100% pace/acc weight isn't going to guarantee that, only extra filtering for that will. But if you're going to filter anyway, then you may as well set pace/acc to its actual weight rather than just trying to ensure 14+ pace/acc bubbles to the top. But then also sometimes we just won't bother with filters.. so realistically we actually really do need flexibility.
Now let's distill this to the main dilemma. My Genie Scout rating files and HarvestGreen's results (and training) have a heavy physical focus. The idea is to get to that threshold of ~17-18 pace/acc ASAP so no one can catch you and you win everything. But my thinking is, given you need to survive at least the first season or two without that, you have to first work out a way of getting lower pace/acc players to work for you. And it turns out it is possible, but it may be unrealistic or too inflexible. And you kind of have to go one way or the other, because if you pacemaxx (especially with full rest training) you will never get those mentals/technicals back, and more importantly it also turns out that simply taking my template and upping the pace/acc to 16 doesn't make it do much better.
I'm still mulling over this. The Luton result shows that low pace/acc is viable, but not as much I'd hoped. I've got a few ideas, and hopefully at least one of them will sure things up.
A team of these (hiddens ~8-13; DC jump 17) achieves 4th-5th in the Premier League:
I wonder how many people even here actually realize that you can't win the Premier League unless you have all your players at 18+ pace/acc even when you're complimenting it with a few of the key attributes such as dribbling and concentration.
So for instance if I decrease stamina from '13' to '8', my team goes from 4th/5th to bottom half. You might think (as I did), just increase pace/acc to 16 to compensate. But actually in this case doing that does hardly anything. In fact, even if you increase them to 17, you still won't win, but you'll come a close 2nd.
Now if you have perfect hidden attributes then you can have 17.. 16.. even 15 pace/acc, you can win the Premier League no problem, but we're talking about what is realistic here.
Some things to note:
- 17 jump on DC (or some other player perhaps?) is necessary, big difference between 15 and 17 here.
- Surprisingly it does not appear that Jumping Reach is an all-or-nothing attribute. There is a clear and important benefit to all players having moderate instead of low Jumping Reach.
- Agility, work rate and composure are the least crucial of the remaining attributes, hence why I have lowered them to 10-11 with no adverse consequence for my team position
- A lot of attributes are set at '8' because that's what you can roughly expect your minimums to be for a player once you're in the Premier League (even if it's a newgen you signed 3 years ago in League 2 say). This is to make the template as accurate to reality as possible, and yes '8' makes a difference to '1'. Of course players will often have a '3' in something, but you can either train this up or compensate for it in other ways and sometimes it just doesn't matter (i.e. set piece attributes).
- Some essential attributes are at '8', but only because the required amount wasn't higher than '8'. This includes vision, finishing, strength for instance.
Now I have tried using HarvestGreen, Orion, my own, etc. data to try and optimize for positional differences. But everything I tried just made the result worse, even gentle adjustments. So I am now faced with 2 options, after being satisfied I've whittled it down to the essential attributes as a whole:
a) Do dozens or hundreds of positional trial and error changes, or
b) Give up on it and just go forward with what I have so far
The more I think about it, the more I am convinced to choose (b). I can always return to positional refinement later. Keep in mind I've already tested a lot of different things, and I know from my 1 CA testing that certain attributes are simply universal (i.e. pace, acc, drib is as essential for DC as it is for AMR).
Singapore has no set local region, yet it produced newgens born in 'Singapore(city)'. No newgens had birth cities other than 'Singapore', even though there are 54 in the database. All other cities had 0 attraction and 'not set' inhabitants range, suggesting that one or both of these settings are required to make it active. Based on other results, I believe only 'inhabitants range' matters here, and that actually 'not set' doesn't inactivate, it only makes those cities very low probability (this part remains questionable). Note that Singapore clubs have all sorts of different Singaporean cities set as their city.
In Slovenia, no cities have a local region set, however attraction and inhabitants range are. Results showed a diversity of birth cities, in frequency corresponding roughly to inhabitants range. Again there is some doubt over the role of 'attraction'. I ended up being content to rule it out as a factor, but further testing may reveal this is mistaken. I actually suspect that why 'attraction' appears potentially correlated at times, is simply because (a) high inhabitants cities tend to be more attractive, and (b) a large city surrounded by towns is obviously likely to be designated as more 'attractive' than a large city without surrounding towns.
Some tests:
Normal (England) - 49 players born in London. Bristol City 122 PA median.
London '1-1000' inhabitants, all others 'not set' - Bristol City 119.5 PA median, 2nd sample 126 PA. Resulted in much greater diversity of city of birth, but did not prevent 'not set' cities from producing players.
London '20,000,001+' inhabitants, all others '1-1000' - 71 players born in London. Bristol city 121 PA median.
London high pop, no local regions - 64 players born in London. Bristol City 127.5 pa median.
Poland-England switch - Bristol City 101.5 PA median. Man City 120 PA (142.5 normal). Lech 133 PA.
France-England switch - Paris SG 159.5 median.
So you can see here that cities & local regions don't affect PA, and also that the number of players being 'born in' certain cities can be influenced but probably not as much or easily as you'd think. The nation ID, or unique division ID, by contrast does matter significantly.
Further implications:
Since newgen production is probabilistic based on just 'inhabitants range' and is initiated by the club (club creates 16 players, not drawn from some regional 'pool' ), then there is no competing for players going on.
Once you start thinking about it, it becomes obvious why you would expect this all to be the case:
- If newgens were 'drafted' or 'poached' from a regional pool, no doubt the game would at least on rare occasion come up with errors, where some clubs wouldn't get their 16th player while another would end up with 17 and shenanigans of that nature. Yet I have never heard of since an error in all the years of FM.
- If the above was happening, it sounds like it would be computationally expensive. It would be the first corner to be cut for game optimization.
- The best player production cities in the real world also tend to have the greatest club numbers: Buenos Aires, Argentina; Montevideo, Uruguay; London, England. Aside from making club competition for players within cities a difficult thing to pull off in the game correctly for the programmer, the fact is that in Buenos Aires in the game you have 8 clubs in the Argentine Premier Division including Boca and River Plate.
- If 'inhabitants range' and/or 'attraction' were used as an absolute measure for newgen quality and/or number, then Mumbai India (20 attraction, 20000001+ inhabitants) would be a goldmine for newgens, yet it isn't (in the game, and in real life).
- Local regions serve a purpose in the editor for setting division boundaries where coordinates do not suffice; i.e. a team located in Wales, may actually play in England in real life. Coords fail here, but 'local region' can put the club's city in the right division.
The other part of this is, where exactly does this leave Youth Recruitment?
Youth recruitment still works as a factor, as a pecking order within a division. In fact, youth recruitment makes more sense now, given that I had known before that there is overlap between divisions (i.e. Premier League 140 > 100 median say, Championship 115 > 80 median) instead of Premier League 140 > 100, Championship 99 > 80.
There are other hints in the database that youth recruitment is just relative (i.e. pecking order) rather than absolute. In Turkey players in the top league have YR of 2 to 8. In Jamaica, 8 clubs in Div 1 have YR 20. Tiny nations can have YR 2-3 (San Marino) to YR 20 (Turks & Caicos Islands). This is neither absolute in terms of quality or number of production nor geographic distance.
The fact that it bears no relation to geography in my view is further evidence that there is no underlying 'draft' or 'pool' system going on, as you would expect 'youth recruitment' to be the extent of the club's tendrils into surrounding cities or coordinates of distance.
So there is nothing so sophisticated going on with Youth Recruitment, but it is drawing the better players to drop into unique divisions from somewhere, and that appears to be the national pool, by which I mean a number of hidden factors & values rather than a hidden pool of players within the game. It's clear that each nation or unique division has at least one hidden quality setting that is very significant (see 'Poland-England switch' above for example).
It would be kind of ok because pace/acc dominate and that didn't change, but a few attributes have changed up to 3x and some of them are moderately important not just minor. It wouldn't be as simple as making the attribute 21 > 63 (3x), as that's not how my calculations work and why I haven't done a FM26 version yet.
So I would stick with the old FM26 file I posted for now.
Alternatively you could look at HarvestGreen's differences for FM26, and give a +10 bonus for each +1x for attributes that have 10 weighting or more. I.e. 3x would be 12 > 32, 1.5x would be 25 > 30. That would make things roughly more appropriate for FM26.
I will eventually create a FM26 version, but it will be with my new method that I'm currently working on.
Rain said: Are there certain positions that are more important than others and if so what are they? Thanks
Although I haven't tested this, I think the tactic is more important than the positions. Or put another way, the best tactic determines what positions you require.
But there is definitely also a difference in CA required for positions, or what positions are easier to fill.
Starting with the easiest/cheapest: DM, ST, DL/DR, GK, DC, AML/AMR
In terms of what position can have the largest variation in impact, I would say it's DL/DR (has a lot of cheap yet highly impactful attributes, which you should try and take advantage of), then DC (expensive and rarer attributes but crucial, things like pace/acc, dribbling and jumping reach), then AML/AMR (mainly just needs high pace/acc which is very costly, but also has some cheap beneficial extras such as jumping reach and defensive attributes but these are also hard to find).
The DM requires very little CA, and ST can be whittled down to pace/acc with jump reach, dribbling semi-optional, and finishing almost completely optional. GK doesn't have freebies, is only 20% impact of outfield player according to HarvestGreen, and either already has the required agility/reflexes/aerial reach or they don't.
Is this 20% scale still the case? If so then I think it's not a coincidence that mental/physical/technical/goalkeeper attributes are internally stored as values 1-100 and personality attributes are 1-20.
If Genie Scout doesn't normalise these values then it's multiplying the personality weights against values that are one-fifth those of M/P/T/G attributes.
If you clear everything and make 'professionalism' 100 weight, players with 20 professionalism will have 20% rating. Here's someone else who discovered this and he lists the affected attributes. If you don't use it alone in your weights, you'll find it is a negative modifier on the rating.
But if you take the 'blended' ratings and do -21 to professionalism, +21 to pace, the rating will only change from 72.4% to 70.8% say. If you do -14 dribbling, +14 professionalism, it might go from 65.3% to 66.0%. So overall it seems to be working as its supposed to, but imperfectly.
I thought of the feet thing, and position proficiency. The Mbappe-Salah case rules this out specifically, as they are both the same, apart from a slight foot difference that should be a mere fraction of 1%. I would guess that what is going on, if you haven't made a mistake/change in your own calculations (i.e. perhaps you left out something like -27 for injury proneness), is that the personality attributes, injury proneness, natural fitness, etc. are exacerbating each other's minor errors in being combined, creating a large overall error. That's just a guess though.
You may be on to something in saying that it could be to do with attributes being 100 vs personality being 20. Could be why Genie Scout is doing it this complicated way in the first place.
I will have more dumb questions later as soon as I organise them.
EDIT: I might as well ask this one now, while it's fresh. When you rated players according to various weights and formulae in this post, where did the player data come from?
I ask because I tried recreating the calculations manually (using, for example, the Genie weights you attached via screenshot earlier) and got a completely different order of players when looking for the best strikers in the world.
I created a new game in FM 24, July 3rd 2023, and got the following when calculating using your Fast Striker weights:
1. Erling Haaland
2. Mohamed Salah
3. Kylian Mbappé
4. Lautaro Martínez
5. Marcus Rashford
6. Victor Osimhen
7. Robert Lewandowski
8. Lionel Messi
9. Randal Kolo Muani
10. Romelu Lukaku
I did get it working when using HarvestGreen's new GK weights but either we're using different data for strikers or I'm incorrectly guessing how Genie Scout calculates ratings via weights (it is the sum of all attributes multiplied by their respective weights, right?)
So it turned out the Genie Scout thing was mostly a false alarm
If you isolate personality/negative attributes, it does weird things, but in standard use +21 professionalism is in fact equivalent to +21 pace or +21 tackling. It's not 100% exact though, it can change the results ~2-3%, probably because it's doing this unusual non-linear thing.
It is concerning though that you find Salah to be ahead of Mbappe. That's a 7.5% difference. Not sure what's going on with that.
So I know that you can win the Premier League consistently with 1 CA players so long as they all have just about 20 pace/acc. But of course this isn't realistic to have.
On the other hand, what is realistic is that you can take a bunch of ~12-14 pace/acc players and get them to 16-18 pace/acc with ~4 years of meta training. 16-17 pace/acc for all outfield positions is the minimum you need to win the Premier league. So winning in the end, isn't really an all too difficult challenge anymore, and it gets easier if it's Championship or lower level.
Now if you take a look at starting top Premier league players in the game, you'll see quite a few with 14 pace/acc, which got me thinking. First, it means it's probably possible to have mentals/technicals be enough to make up for the low pace/acc, to the extent of 14 pace/acc. Second, that elevating mentals/technicals just enough to allow for 15 or lower pace/acc should be the name of the game now.
As it turns out, it's difficult to make even 15 pace/acc viable, but it is possible, even with a whole bunch of attributes left at '1' and others at a reasonable '13' it would win the league. But when I was initially testing it, I left the players with perfect 0 CA cost stats.
I realized I had to make it fully realistic, reducing all those 0 CA stats to ~13 as well, which reduced performance quite a lot. At the moment I'm getting results of ~7th, but the conclusion I've come to is that for the Premier League, that's good enough for a first season. The idea would be, tailor the Genie Scout ratings to get these 15 pace/acc 13 other guys for a 1st season mid-table finish (if newly promoted team) and then reach 16-18 pace/acc through training/purchases the following year for a guaranteed win.
Here's an example (DL/DR) of where I'm at so far (a team of players like this achieved 7th):
The plan is to keep reducing each attribute one by one until I whittle it down to the essentials. Then I can test some positional variety (maybe only DC/DL/DR need higher concentration) and then make some final adjustments for CA weight and pull things a little closer to HarvestGreen's findings on mentals/technicals just to be safe (some attributes I discard initially might have a small beneficial effect I didn't notice anyway). Training will also be taken into account, to the extent its still relevant. I am also testing in the Championship, as I feel it's important to be able to win that.
This will be more transparent, less arbitrary, and closely aligned to real results in a real and popular league.
I will have more dumb questions later as soon as I organise them.
EDIT: I might as well ask this one now, while it's fresh. When you rated players according to various weights and formulae in this post, where did the player data come from?
I ask because I tried recreating the calculations manually (using, for example, the Genie weights you attached via screenshot earlier) and got a completely different order of players when looking for the best strikers in the world.
I created a new game in FM 24, July 3rd 2023, and got the following when calculating using your Fast Striker weights:
1. Erling Haaland
2. Mohamed Salah
3. Kylian Mbappé
4. Lautaro Martínez
5. Marcus Rashford
6. Victor Osimhen
7. Robert Lewandowski
8. Lionel Messi
9. Randal Kolo Muani
10. Romelu Lukaku
I did get it working when using HarvestGreen's new GK weights but either we're using different data for strikers or I'm incorrectly guessing how Genie Scout calculates ratings via weights (it is the sum of all attributes multiplied by their respective weights, right?)
If I recall correctly, 18 position competency is same as 20. If it is 16, you do need to take that difference into account. Genie Scout does adjust rating using position proficiency, but it's probably somewhat inaccurate.
Your second question perplexed me for a while, but I think I get what's happening now. You are using the same start date/vanilla game data, but your manual calculation (WITHOUT using Genie Scout) does not match my Genie Scout results.
I haven't done the math on it myself, but this could indeed be a Genie Scout problem. If I clear the rating data and just make it acc 100 for ST, then I end up with a player with 16 acc equal to one with 17 acc (both are 20 position proficiency). I found 2 more examples, and it's clear that the extra footedness is making the extra contribution.
But that would only be a small part of the difference here.
It turns out Genie Scout isn't weighting all attributes equally. This has always been at the back of my mind, but I figured we've got what we've got and ended up neglecting this even as I got more seriously into it. Thankfully it turns out to only affect the personality attributes and ones with negative values.
Personality attributes are valued at 20% of physical/mental/technical. This unfortunately means attributes like 'pressure' will have to be hard-capped at 20%. EDIT: It is unfortunately more complicated than this.
Negative attributes like injury proneness work strangely. '100' acc, '-100' injury makes 65% go to 22%, so a 65% reduction.
There is also an up to 6% discrepancy occurring. I thought maybe Genie Scout is assessing values non-linearly, but even when controlling with identical weighted attributes/proficiency/feet, I get 3 STs that are 74.00%, 73.00%, 72.00%. And it seems like all possible correlates are ruled out too, as far as I can tell, which suggests it might be just a bug. Overall it seems like it would add ~2% margin-of-error to the results, which is moderately significant.
This is all a genie scout problem, so I would think your own calculated player rankings are correct and you should use them.
tl;dr for anyone using the Genie Scout files, it turns out personality is just not working in a way I can understand in Genie Scout, and I don't have a solution right now. I'll probably take a few days to work this out.
Yes
keithb said: Stamina is definitely ahead of those. Its very important for midfield and full backs. I thought you had done some kind of values by position? Anticipation might also be ahead.
I just asked a question. You said your tests got other results?
No. I could win the premier league with a team of 1 CA players that have 1 stamina. And the reason stamina was left at 1 was because I found increasing it had no statistically significant effect, at least not any greater than 10 or so other attributes.
That does not mean that stamina does nothing, but it demonstrates that stamina is far from essential, even for DL/DR. HarvestGreen's data shows 6 > 18 stamina is +8.1% win rate, which is less than concentration (+8.6%), which was the last attribute I included on my toplist.
It's one thing to posit challenges based on your own intuition, nothing wrong with that. And even arrogance has preservation of dignity as is its virtue. But where is the dignity in insulting me only to piss up into your own face in front of everyone?
Kma said: @GeorgeFloydOverdosed Please do you have in-game filters for the vanilla game ? I don't use GS and other fm lab files
I did before. They're somewhere, but I recommend just filtering for some key attributes, say this (for adult player):
pace/acc 12
drib 8
concentration 8 (on DC/DL/DR only)
work rate 6
That would filter out most of the complete duds.
at this point do you think this is the best one?
I definitely recommend the new ones over the old file. It's an improvement in spite of the flaws.
If i understand it right, with this new file the attributes of acceleration and speed are not as valued, also taking into account the issue of training and possible growth. However, I am using the fm match lab training file, will it have an impact on the development of speed and acceleration and therefore will this have an effect on this ratings?
I hope you can understand my question
Not that familiar with FM Match Labs, but I think they change everything up to balance things right? So it will make the ratings less accurate, but not by that much. The main things being considered are performance and CA cost, and the training bonuses/penalties I've treated as the strawberry on top.
Honestly, I'm thinking of doing another redo from scratch that will use a more grounded method that I can present more clearly and transparently.
keithb said: You dont think stamina is important for a full back? Definitely ahead of jumping, balance and strength. I would also include work rate.
Later on you go on to say you had to accept harvest green was correct about some things. Had you previously said he was wrong?
Sorry im obsessed again but your attributes for full back seem wrong.
Concentration 25 was the last on that list. Stamina is 17. I missed work rate, which is 31. Balance and Jumping Reach have 2 weight, stamina is 6 weight, so it's apples and oranges.
No I did not previously say HarvestGreen was wrong, I simply meant that in assessing the performance of balance & strength I trust his results because I know other attributes he gives values for are pretty precisely correct. Part of it is that his own results has changed, due to him using a new method, but mainly it is that I have taken 6 > 18 results as the basis instead of 1 > 18 results (since it is unlikely we would sign players with 1 strength, or otherwise be unable to train them to ~6).
keithb said: I will say again multiple times you have boldly declared other's work and findings to be wrong, only at a later date to retract and say you were wrong. Once is fine, maybe even twice. But you were prolific.
Instead of providing a single example demonstrating the above claim, you are instead trying to ask me now 'what about this one.. i-is that a time you said HarvestGreen was wrong??'
LightningFlik said: Sorry if this seems like a dumb question but what do you mean by "max required"? Do you mean that the positive impact from an attribute is capped at this value?
Yes, benefit tails off greatly or is statistically insignificant above that value.
Based on the physical side always assumed it would be the other way around.
Assuming you're assessing for DR position, then the main attributes for DR are pace, acc, drib, jump, bal, injury, str, concentration.
Baio vs Martim:
16 acc > 14
15 pace > 14
11 drib < 14
10 jump < 12
13 bal < 15
11 inj < 7
11 str | 11
12 con < 13
So at a glance they look fairly even, trading 3 points of pace/acc for ~13 points of ~30% valued other attributes. Not to mention Martim is doing it with 8% less CA cost, but this isn't part of the rating, just one of the goals.
I agree with you though that at a glance, it wasn't obvious that Martim was as good as Baio, but the math seems to check out.
Keep in mind that 'blended' devalues pace/acc a bit compared to other attributes, because it's imbued with the expectation that over ~4 years of training, pace/acc will grow but technicals/mentals will stagnate/decline. But even if you use the 'performance' file, they will probably still be near even given the math above.
I know I'm blathering too much, but I would also like to say that my old file values pace/acc more, but I simply had to accept what HarvestGreen's results are showing. Based on my 1 CA tests, I don't see evidence for balance and strength being worth ~30% weighting, but his results have always ended up being on the money so I decided to accept and include it.
Panneton0 said: I am currently trying a Youth Academy Challenge, which makes me unable to buy players, and only use my academy newgens.
With that in mind, I'm trying to put together the best way to approach the GS rating files you provided (I am on FM26 so I know they are not fully compatible, but I am wondering about the philosophy of it anyways, more than the actual scores). In this challenge, I only want to assess my own team a) probable best performers b) probable future best performers. But I don't need to find players who are "good even if low CA" because anyways I have a fixed roster and can't try to find a cheap hidden elite.
The "pure performance" file would provide me with an indication of probable best performers in my team. That part seems straightforward.
But is the "youth" file as relevant in that context? Wouldn't a player's potential, rated by the "pure performance" file, be a better prospect than a player with good "youth" rating? Do we know how GS rates "potential" of a player is computed? Is it simply considering a direct scaling of their current attributes as if linearly scaled up to their PA?
Sorry if these questions are unclear, I'm still trying to wrap my head around all this!
How GS computes potential is not known to me, and really I should have thought before to say bluntly that using GS 'potential' rating is probably too inaccurate with my files.
We've all used it for years, or at least I know I have, but just as with the rating values it's just not accurate enough anymore given what we know now. It would still give you a good indication of whether the player has room to grow or not, and that's a key thing, but we know that attribute distribution matters more than PA now. So I would look at current rating + PA + CA-to-PA gap + overall picture (i.e. injury 18 would rule a player out for me), and make a judgement based on that.
In your case I would still use the 'youth' file, as it optimizes for low CA (therefore can attain higher peak performance later) and takes into account the effect of training over ~4 years. If you're choosing youth to play first team games, then just switch to 'performance' for that temporarily to assess (or use 'blended' ).
If you just use the 'performance' file or similar, even if you intend to use this youth player in your first team straightaway then he will probably be subpar first team player at first (very few youth would have the pace/acc required immediately), and then a limited player later (high pace/acc, but low mentals/technicals that never grow).
And that's why first intake is much better - it is "half-blind-generated" in a different way maybe during generating profile when starting new game? I need two weeks to be 100% certain.
Yes, it's a good possibility that the game is simply giving it a running start for the first year.
Looking back at the original post of this thread, I realized this could all be a symptom perhaps of affiliate clubs. I had forgotten about this since it was over half a year ago, but I said that affiliate clubs reduced median PA for Man City by ~15-20, which is the same drop we see. And it would make sense that players from affiliates don't come through in the first year. But then again Aston Villa, Exeter and Forest Green shouldn't really suffer from this problem.
EDIT: It's not the affiliates
Man City affiliates removed:
2024 - 142.5
2025 - 119.5
2026 - 123
2027 - 101
2028 - 113
2029 - 107.5
2030 - 114.5
Average: 117.28
EDIT 2: It's not 'youth importance' of the club either. I've tested youth importance before and found it does nothing for PA, but I thought maybe there's a multi-year effect I somehow missed.
Man City affiliates removed 20 youth importance:
2024 - 141.5
2025 - 126
2026 - 121.5
2027 - 107.5
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.