treath said: mate i don't discredit your research, i think it's valid when we talk about cost effective relatively.
but people don't use the ratings for that, they use to find the best players, so when you put in your ratings ZERO for long shot, technique, first touch, etc. It will fall apart. It will not show the best players, but the more cost effective maybe.
Take a look at your picture here from GenieScout, there is a GK from KV Mechelen 112Ca better than Mamardashville 148ca..near as good as Diogo Costa and Verbruggen.
But he is not that good, am i right?
Your rating show that, well forGk with 110-120ca he is the best cost effective in the game but not the best player to play for my team now.
There is no way in hell Courtouis it's not the best Gk in the game, there is no way a Gk from Indepediente Del Valle and Burnley better than Oblak, just because the Aerial Reach and Pace (???) is a little bit better than Oblak (discredit for all other atributes).
So you misguiding people when we talk about find the best players to play for my team now.
But you help a lot, and helped me a lot when we talk about cost effective for training. Expand For many attributes, including all the ones you mention, there is simply no benefit to having them. They are in fact often a net negative because they take up CA, reducing available CA for useful attributes such as pace/acc and slowing development (CA-PA gap strongly influences growth).
That may sound hyperbolic, but consider the following example:
A player has 5 extra passing. +5 passing = Approx +0.96 win rate according to HarvestGreen's data I took a random 140 CA player and gave him +5 passing. His RCA went to 142 CA. So +2 CA for +5 passing. If I give him +1 acceleration instead, his RCA is 143. So +3 CA for +1 acceleration. +1 acceleration = Approx +4.78% win rate according to HarvestGreen's data. If we adjust the CA to match, it's +0.96 (passing) vs +3.186 (acceleration). So extra passing is just losing.
That's HarvestGreen's data.
For my own reference, I use my own data. I change an attribute from 1 to 20 for all players in a team, and if the team has an identical or worse position after a full season, I say that attribute is worthless, end of story, and mark it '1'. If going from 1 to 20 changes the position by 1 place, I put it in my weights - even if it costs a lot of CA. An example of this is strength.
A zero weighting does not mean they are penalized for having the attribute, it just doesn't give them an advantage for it.
Now as for saying Messi is obviously better than Joe Blow from Slough.. I have resigned myself to not making presumptions. First off, I'm not an expert on every great player in the footballing world, and my knowledge is probably a bit outdated. Second, it would obviously be a form of confirmation bias to judge results by name recognition.
The gold standard for me is results. I have compared a few top strikers, testing them in the same league as a control.
A good second option I believe is to see who the top clubs actually start with or buy. You say Courtois is not the best GK in the game. Well, he's the 1st choice GK for Real Madrid, and in a save I checked he averaged 7.21 rating over 5 years with 2 runner-up World Goalkeeper of the Year Awards and 3 third-place awards, which doesn't sound too shabby to me. I guess my question to you is.. on what basis do you know he is not one of the best GKs?
In regards to best players vs CA cost-effective, the current weightings I present do not take CA cost-effectiveness into account. I previously have, if you are familiar with the 'Blended' vs. 'Pure Performance' files. The only way it is currently coming into consideration is as follows:
Suppose I test X attribute '20' finishes 5th. '12' finishes 5th. '11' finishes 6th. '10' finishes 7th. '9' finishes 10th.
My thinking would be that I should choose somewhere between '10' and '12'. If attribute X is very CA costly, or more importantly difficult to find/train, then I will likely choose '11' or possibly '10'. Otherwise I will choose '12'.
How you should actually present your argument therefore is that I should target 1st, not 7th. But I think your typical player is taking Slough to the Champions League, not assembling the World's best XI in Season 1.
I mean honestly, what do you even suppose to propose? I can only imagine you would suggest weighting passing as 5 instead of 0 for example. But then you would have 36 year olds giving Div 2 strikers a run for their money, because their 16s in various dud technicals & mentals would make up for the difference in speed.
and also have tried to emphasize that Unique Nation ID matters a lot - as important as junior coaching or more.
But I've never discussed the randomness factor, let alone put a precise figure on it. And many people just handwave discussion of newgens away with 'it's all dominated by randomness anyway'.
So I think it is time to start determining and stating just how random it is exactly. After a brief thinkle I've put it at 50% and junior coaching at 13% for a comparison, but this is just a starting point for a more precise estimation.
treath said: not mention other positions that infer a player like a winger or midfield with 20 passing 20 first touch 20 long shoot 20 technic and 14 driblling are worst than a player with 20 driblling and 5 on the rest. Expand Passing, first touch, long shots, and technique have negligible benefit or even possibly negative correlation for outfield players.
If you don't want to take my word for it, refer to HarvestGreen's data on this:
You're also not attempting a fair example. No players are going to have 20 passing, first touch, long shots, and technique. Nor is a player going to have 20 dribbling and 5 in those other stats.
treath said: he blindly trust this prem 1.0 ratings that show pace is more importante for a GK than reflexes and his gk are a phisical monster.
the problem is people trust this ratings blindly i made tests with this rating with gsscout and it show goalkeepers with 100 or 110 pa better than great goalkeepers just because they are tall and have enough aerial reach and jumping reach to surpass lack of reflexes, 1-1, etc. Expand If you doubt it, you can edit an English Premier League's team in the editor to match these attributes and see if they come ~7th in combination with Knap tactic as I claim they do. For hiddens, convert the values here (simply divide by 4).
It requires a bit of work, but the difficult legwork is already done. It would take about 30 minutes, and then perhaps another 30 minutes to test.
I have tried to state clearly that while the attribute templates are very reliable (plug those figures in and you *will* get 7th on average and with not too much variation), weightings have the downside of being unable to distinguish between 1 acc/20 pace and 10 acc/10 pace.
You mention 'prem 1.0 ratings that show pace is more important for a GK than reflexes' and 'aerial reach and jumping reach to surpass lack of reflexes, 1vs1', which are examples of this inherent lack of discrimination. I have attempted a weighted weights version in attempt to try and compensate for this problem, however my comparison testing found that it did performed worse than the standard Premier League 1.0 weights under normal playing conditions (8.333 position result average vs 7.333 for standard Premier League 1.0 weights).
The comparison tests included a control of Orion's weights, which averaged 13.166 position, so my weightings are definitely worth using above any random set of values, and I daresay anyone else's weights presented so far.
You say that my weightings 'show goalkeepers with 100 or 110 pa better than great goalkeepers'. This irks me because this is just straight up disinfo. Now maybe what you mean to say is that sometimes a 100 CA goalkeeper can supposedly perform at the highest level, but cmon man, anyone can load up my ratings with the starting database in 3 minutes and see this:
bf3metro said: Thanks for your detailed reply, I really appreciate it.
I genuinely have this feeling that a goalkeeper with poor Reflexes is basically a walking sieve, haha! But at the same time, what you said makes perfect sense, because a goalkeeper isn't supposed to save everything on his own.
I'll post a screenshot so you can tell me what you think. This was my goalkeeper: he conceded 58 goals over the season. I replaced him the following year, but according to the ratings he's still considered the best goalkeeper in my save... despite having only 9 Reflexes. That just feels strange to me.
Anyway, thanks again. I also noticed you mentioned FMSuperScout. I've never used it before. Is it as accurate as Genie Scout when it comes to calculations and visible attributes? I see that FMSuperScout also takes hidden attributes into account, so it's definitely worth testing. I'll have a closer look at it. If you've already done some testing with it, I'd be really interested to hear your thoughts, especially regarding the reliability of its ratings and percentages.
One last thing: would it be possible to talk to you via DM instead of posting publicly here? Do you accept private messages? If not, no worries at all!
Thanks again, and speak soon! Expand The only issue with that player is the 9 reflexes. I would expect that player to do better than 6.7 rating in England Div 3. Could it be that the player has poor hiddens?
It's an inherent downside of weightings that it can't distinguish between (1 pace/20 acc) and (10 pace/10 acc). I think it can be mitigated in various ways though, similar to how there are perceptual tunings available in video encoding to improve the subjective quality.
I have attempted this by weighting the weightings, which you can find here. Here are the weighted weightings for GK, which I haven't posted before:
It's a trade off where determination for GK is hardly taken into account anymore, but on the other hand aerial reach will always get the priority it deserves. It should be an improvement, because it's worse to be deficient in aerial reach than in determination.
But in a controlled test of it, it finished position 8.5 on average, which was worse than 7.333 for the standard Premier League 1.0 file. I will still be going down this route further, but that is where things are at right now. You can try using these weighted weights if you like.
I respond to DMs but obviously I only have the bandwidth for a few people from time to time
Kamas1 said: Does it need to be changed? const META_W = { Pace: 6, Acceleration: 6, JumpingReach: 5.2, Dribbling: 5.2, Balance: 4.8, Concentration: 5.2, Anticipation: 5.2, Determination: 5.6, Agility: 4, Stamina: 5.2, Composure: 4.4, WorkRate: 4.4, Aggression: 4.4, ImportantMatches: 5.2, NaturalFitness: 4.8, Consistency: 5.2, Pressure: 5.2, Professionalism: 5.2, };
And why is the highest value 6 if the scale goes up to 20? Expand Does what need to be changed? Seems correct
My presumption is that the weights are relative to each other rather than absolute. The results appear similar to FM26 Scoring System, so I haven't bothered verifying. I've simply divided by my weightings by 10.
bf3metro said: Hi, first of all, thank you so much for your incredibly detailed reply. I hope I'm not bothering you, but I have a couple more questions that could really help improve my experience with the game.
Regarding the Premier League 1.0 ratings, I feel like the goalkeeper ratings are a bit off. Quite often, average or even poor goalkeepers end up with very high percentages. In fact, the highest-rated player in my save is a goalkeeper with only 9 Reflexes who conceded 58 goals during the season. Do you think there's any way to improve the goalkeeper ratings in the file?
You also mentioned the Genie Scout bug regarding hidden attributes. In your original FM26 ratings file, hidden attributes are taken into account. I'm completely willing to modify the Premier League 1.0 ratings file to include only the hidden attributes, but do you know what weights or values they should be given? Would it simply make sense to import the hidden attribute weights from the original FM26 ratings file into the Premier League 1.0 file?
Thanks again in advance for your reply. What you're doing is genuinely impressive, and I really appreciate the amount of work you've put into it. I'll definitely continue supporting your work in the future. Expand For reference, these are the optimal minimum set of attributes for GK derived from testing:
The proper version has 8s instead of 1s, but this makes it clearer what attributes matter and which don't.
I've had a double check and it seems to be working as intended. The top rated GKs are the ones you'd expect to be (1st GKs from the very top clubs), and if I filter for current rep 5000< or 3000< then the top players even if low in value or have weird looking distribution of attributes nonetheless are getting high ratings and are getting picked up by higher clubs which are strong indications it's on the right track.
Some examples:
Keep in mind that a GK alone is not going to stop goals. The results depend largely on the rest of your team. HarvestGreen concluded that a GK is worth 20% of an outfield player. My impression is that it's quite a bit more than that, but a GK alone certainly won't save a bad team. What I assess by is the improvement or drop in league position.
In regards to Hidden Attributes in Genie Scout, the problem is not that I can't work out what weighting to give them - you can find those weightings here. The problem is that GS does not calculate using those weightings correctly. It uses some complex formula that makes setting them accurately difficult if not impossible. Think of it as two curves that don't match up and therefore can't be integrated together even if you work out what those curves exactly are, this is the challenge I'm facing. The band-aid solution right now is to combine the weights with a basic filter for hiddens (i.e. min 8 pro, pressure, etc.).
Now if you use FM26 you may be in luck because there is now a program that can do what we're looking for. See my post below this.
Looks better than FM26 scoring system on the face of it
For anyone interested in using my weightings with it, what you need to do is the following:
1) Go to install folder 2) Go inside 'app' folder 3) Open 'app.js' with notepad 4) Find 'meta-score (FM-Arena attribute testing)' 5) replace the weightings with the following and save:
66connor66 said: Hi, haven't played in a while... did we figure the best file for ratings so far? Is it different doing a long term save where developing vs looking for instant success? Expand bf3metro said: Hi @GeorgeFloydOverdosed,
I noticed that some people have been criticizing your ratings file. I've been using your FM26 Genie Scout Ratings file since almost the beginning of FM26. Then I stopped playing around February and only came back in June. Since then, I've still been using the FM26 Genie Scout Ratings file, but I recently saw that you now recommend using the Premier League 1.0 Genie Scout Ratings file instead.
First of all, congratulations on all the work you've put into this. It's rare to see this level of dedication and effort.
I have three questions:
Are you still actively improving and refining your ratings file? If you had to estimate it, how reliable and accurate do you think the Premier League 1.0 ratings are, as a percentage? Finally, which file should we actually be using: the FM26 Genie Scout Ratings file or the Premier League 1.0 Genie Scout Ratings file?
That's all! I hope you'll have the time to reply. Thanks again for all your hard work, and have a great day! Expand I recommend the Premier League 1.0 file, while using filtering for hiddens. It is designed to 'save' you in your first season, but I think this is the right balance and does not impair min-maxxing.
It would be less accurate for FM26 most likely, but I suspect the difference would be small.
This question gets asked a lot, so I'll briefly explain why. Take long shots - it's ~3x importance in FM26 supposedly, ok that's 3x0 = 0 for me.. maybe that ends up being a 10 minimum for the attribute, which is a minor difference since most players will have ~6-8+ by default anyway. Going by HarvestGreen's data, there don't seem to be any paradigm-shifting changes, and the thing is, if you suppose balance now has say a '16' requirement, that's highly unlikely to be the case because very few players would have 16 balance in the game. If I had to make a rough guess, the differences between FM24 and FM26 might be a player going from rank 57th > 68th say. Not nothing, but nothing huge either.
The ratings file will continue to be improved, but there is no set timetable.
The main goals I would like to achieve are:
1) Re-integrate hidden stats again. Either with a program that comes along that can do so, or by essentially backporting the rankings FM26 scoring system gives and fiddling with the numbers until it largely fits the mold. 2) Create a FM26 version. Waiting until FM26 is free on Epic, or otherwise settle for working with HarvestGreen's FM26 data. It's not unfeasible, it's just a lot of effort for little reward whichever way I do it. 3) Further improve attribute value accuracy and weightings accuracy. Ideally I want to be able to say this is player is 5th, that player is 6th, etc. with high confidence.
If I had to put my impression of the accuracy of my GS rating files as a % based purely on intuition, I would put it like this:
88% - Premier League 1.0 (in FM24) 83% - Premier League 1.0 (in FM26) 82% - FM24 Pure Performance 80% - FM26 Pure Performance 75% - If you just plugged in pace/acc at 100 weight and added a few others as keithb suggests (basically every simple interpretation of HarvestGreen's data) 70% - File based on Orion's data 56% - Default Genie Scout
I can't say I even trust my own intuition on this though. I know the attribute figures are very close to accurate, translation to GS weights is another matter. Here is what the first control testing showed (number is average finishing position in Premier League):
6.5 - FM24 Pure Performance 7.333 - Premier League 1.0 13.166 - Orion's weights
So I think there's pretty clear evidence it works well, but my intuition about Premier League 1.0 being an improvement over the previous version may be wrong. I still think Premier League 1.0 is better, because it's based on solid data (my extensive attribute testing). It could just be that beyond a certain point, further precision is superfluous (i.e. if one file gives 73.54% and the other 72.88%, you're going to end up picking the same player anyway). I anticipated this and measured overlap of players. From memory the overlap was only around 50% for all three, so there is still substantial variation going on, which was actually quite surprising to me.
BrushlessPlaymaker said: Still on this topic: Like I said, I prefer may saves with generated players rather than real ones and, since you mentioned it, I'm noticing a lot of young and potentially good player with very low jumping. Is it worth it trying to train that up? I've switched a couple of my own players with decent pace/Acc from quickness to Strength Individual training (which supposedly improves strength and jumping reach) but I'm yet to notice improvements. Expand I assessed alternative training focuses and found it to be a bad idea. But if a player is particularly deficient in a certain key attribute, it is probably worthwhile training them up to ~8 in that attribute.
With jumping reach, would it be worth say training up further to 12 instead of pace 16 > 18? It's hard to say. Personally I would just get the high jump reach player to begin with, because it will take time anyway, and jumping reach is particularly unforgiving if you lack it. You can get away with 14 pace; you can't get away with DCs that have 14 jump.
This set of guidelines for Italian FM volunteer researchers for FM20 is something of a goldmine when you plug it into Google Translate. Most of the FM info dished out by SI staff is pure BS, but here we have some tidbits of proper info about how it works under the hood.
There are two interesting things in it on height specifically:
1) There are conversation tables for height to jumping reach (one for GK, one for outfield). 2) Pace - 'Very short players cannot have a very high Speed value (at most they will have a high acceleration value)'
This means you can use minimum height to help filter players in the starting database, as the researchers have to follow these strict guidelines in the player data they're putting in.
We can deduce that a player under 1.95m won't ever reach 20 jump even with training. 1.87m would be the minimum to eventually reach 17 jump (ideal minimum for DC). 1.82m is the bare minimum for a DC. Under 1.72m would be too deficient in jumping reach in any position, and should probably be avoided.
We are told that short players are pace-constrained to boot as well.
Now that is the starting database, but if you think about it, they've probably programmed the game to generate new players according to the same guidelines.
Fraudiola01 said: @GeorgeFloydOverdosed With regards to the Match Engines on FM 24, what is the current consensus of the community? Does the FM Match Lab ME or other ME mods help with the game being more realistic/a wider variety of tactics being viable? Or is it just placebo? Expand I wouldn't know as I haven't used those mods, because I like playing the same game mostly everyone else is playing.
I suspect that problems may arise if you make meaningful changes in isolation. For instance if you somehow reduced the importance of physicals to winning, that would probably mess up the transfers side of the game.
Panneton0 said: So it is not a rating file that truly shows the "statistically best" player, but the "statistically most promising, considering pace/acc will be trained later". For instance, Haaland is way above Mbappe because Haaland could gain the 1-2 pace/acc that Mbappe has on him, while Mbappe could never gain the 10 jumping reach that Haaland has on him, even with perfect CA reallocation through Harvest's training regime.
So if I'm using the file to figure out the "best XI" of my team for a given tactic at a given date, your earlier "FM26 GS file" would make more sense, but for long-game recruiting purposes / understanding best promising youngster from my academy, your new "Premier League 1.0" file is prbly better? Expand I had to go back over my posts and have a few puffs of the pipe on this one.
I misremembered the reasoning for pace/acc being low. I've been away from it all for about a month.
The goal I had started with in my 3rd iteration was this: Get the pace/acc requirement as low as possible, because getting a full team of 18 pace/acc players your first season in the Premier League isn't realistic. It turned out that ~14-15 was feasible in combination with certain levels of other attributes - it wouldn't win the Premier League, but it would guarantee avoiding relegation and even potentially achieve a continental qualification finish.
Now it's true that I also adjusted the values for training later, however pace/acc remained at 15. And yes, the idea is to train them to ~18, but this is beyond what is strictly necessary to place highly. The idea is that growing pace/acc to 18+ will ensure finishing 1st in the 2nd season onwards.
The history of this can get very confusing, but I think this timeline makes it pretty simple:
Dec 15th - First GS ratings file released. May 7th - 'FM24 Pure Performance' is released. This is the "best XI" ratings file you have in mind. It is mostly based on HarvestGreen's data. May 14th - LightningFlik posts the discrepancy that leads me to finding Genie Scout is bugged. June 12th - 'Premier League 1.0' is released, which is mostly based on my own testing. June 21st - 'Premier League 1.0' tested in comparison to 'FM24 Pure Performance', with the latter edited to avoid causing the GS bugs. Position results were 7.333 and 6.5 respectively, with Orion's weights as a control being 13.166. I had also created another version of 'Premier League 1.0' which refined it according to the essentiality of the attributes and its result was 8.333. I think I planned for it to become 'Premier League 1.1' but either the result dissuaded me or I forgot about it and took a break.
So I recommend just using the 'Premier League 1.0' file.
Panneton0 said: Not sure what the point of that attitude is, but anyways.
I agree that speed and acceleration might be underweighted in the premier league GS file. Jumping reach having high weight is an interesting take, but can you remind me why it has actually higher weight that pace/acc? I feel like nothing should be higher, according to actual testing. Not saying that it's a bad idea, but I wonder the rational behind that choice.
Also, any pointers on how (according to your file, or of general understanding of positional proficiency) we should interpret GS ratings of sub-20 position for a player as per my messages before the interruption? Expand The reason why pace/acc is now seemingly under-weighted is because it is expected that you will train these up using the quickness focus in training. I have based the adjustment on real training results, not just the optimal possible. They still remain the highest weighted attributes.
Jumping Reach is only weighted higher in 2 positions, DC and ST target man, but generally it is up there with pace and acc. I can't remember all the nuances around it, but here are the key ones I can recall:
1) Jumping Reach is critical on DC and has a high minimum requirement. Something like the difference between 17 and 13 is 5th > Relegated say (you can probably find these results somewhere earlier in the thread). 2) It's not that you just need one or two tall players to do the job, and that having your MC be a bit taller makes no difference. Increases even at mid levels across the team result in significantly better performance. 3) Jumping Reach is harder to train than pace/acc, at least when we assume quickness focus is being used.
I read your post on position proficiency, but don't have anything to contribute to it really. I do make sure to search for players with only green position proficiency in Genie Scout. I've dabbled with position proficiency in various ways, but I don't think to find performance level at 1 proficiency say, and I'm too hazy on it now anyway.
What I will say is that I think certain dual positions that have no CA penalty (i.e. AML/AMR) are beneficial in a practical sense.
I vaguely recall experimenting with playing optimal players out of position to try and cut the CA cost and that it failed miserably. So it does have a big impact.
As I was thinking about this, it was lurking at the back of my mind that I'm sure someone had tested proficiency and I had seen the results once. It took a while, but I think I've found what I was recalling. HarvestGreen tested it:
He also did FM26 OOP proficiency and found the win rate difference between 4 OOP proficiency and 20 OOP proficiency to be 40.9% > 46.4%. Link to thread.
keithb said: Whats also funny is we know, at least you should, that someone pointed out the ratings were wrong using the old file you posted. But that was because you didn't understand how to use hidden attributes in GS. It has no relevance at all to your premier league garbage file. Does it? Expand Just to be clear, the process is:
test attributes in isolation + hundreds of possible attribute combinations over thousands of games > record best performing combination of attributes > translate to Genie Scout weightings
not GS weightings > GS Ratings > record winning combination of attributes
So you are confused when you believe my ranking of Mbappe is tied to how well I understand Genie Scout's formulae for hidden attributes.
The translation into weightings works accurately for FM26 scoring system, it is specifically a Genie Scout problem. What FM26 scoring system lacks is the ability to weight hidden attributes.
It is also not a matter of just work out what formula Genie Scout is using and then take that into account. Say it was that personality attributes are weighted at 50% of visible attributes. Ok, then we could just put 80 for pressure instead of 40. It is complicated, and perhaps even completely unworkable. The best way to use Genie Scout right now is to weight the visible attributes, and put filters on the hiddens.
keithb said: Any word on why Mbappe scores so low? Expand I've answered this before here, here, and here.
Someone else also tried to inform you here, to which you responded that the bottom line for you is your motivation to 'blame the person who made the file'.
This is why I will not be responding to any more Mbappe rubbish from you.
keithb said: This pretence that something is up with genie scout when the ratings severely undervalue speed is embarrassing. You could literally change speed to 100 for both and it would increase the players score a fair bit.
He's not even close to the near perfect player. He will do well for his CA because he's 18/18 speed. Near perfect would see a big increase in dribbling, anticipation and agility and balance. The player also doesn't need jumping reach. Some of the best 10's and wingers ive ever had were under 5 for jumping reach.
Not including his hidden attributes has nothing to do with the score and its deceitful to claim it is. Its also funny. You've still never answered why Mbappe scores so poorly using Premier league 1.0 ratings. But you always avoid questions and go full lockjaw. Expand There are 14 players in the starting database that have 18 pace/18 acc/14 drib or higher.
I've done testing previously, and have posted about it, that jumping reach is not just necessary in high amounts for certain players - it is an important attribute for all players, and even going from say 8 to 12.
You are also wrong in your claim on the previous page that players age 18 or less benefit from loans. You seem to just reflexively claim the opposite of anything I say. Here is the data from EBFM on the matter:
We see here that for players age 18 or less:
Training with no matches = +17 CA Matches but no training = +13 CA Matches & training = +19 CA
By contrast for a player age 21:
Training with no matches = +1 CA Matches but no training = +4.5 CA Matches & training = +9 CA
Now factor in the following:
1) Your team (likely) has better training facilities, staff, and most importantly, uses a top training schedule 2) Your player age 18 or less is more likely to be inadequate to play in a decent division and either will be hard-capped by the low division rep, or simply not start games
And even if the planets did align, it would only be for ~10% extra growth. By contrast, a player age 21 simply doesn't grow without competitive matches. For a player age 20 it remains possible that keeping them at the club in the reserves is better than loaning them out (training no match vs. match no training).
being rated at 64, seems unfair. He's a beast, only downside I see is his determination. If I follow these ratings, he won't make the bench in the Portuguese league, where I'm still dominating by far with a team with avg rating way lower than the best in the league.
Can someone clarify this Premier League 1.0 ratings? I was using Orion's and Bafici's rating's a while back, what is everyone's opinion on theese ratings? Expand I'll have a look into it a bit later, but two things are obvious to me here:
1) That is a near perfect player, if you compare his attributes to what I've found to be the ideal set of attributes. The only thing lacking is jumping reach, which is quite important.
2) The Premier League 1.0 GS rating file does not weight hidden & personality attributes, because Genie Scout is too bugged to include them. I haven't given up on this forever, but at the moment there's no viable solution. Your player has ridiculously perfect hiddens & personality, even temperament is very close to its optimal of 10 rather than 20. I daresay this is actually this is the main reason the rating is inaccurate rather than the excellent distribution of visible attributes.
You could make the argument that hiddens & personality should be weighted at least somewhat, even if it messes the ratings up a bit, because a 4% error might be better than a 8% error say. But a player with those hiddens & personality is extremely atypical.. so if we did this it might end up that yes, your player becomes 4% more accurate rating, but 90% of players become ~1-2% less accurate say. I'm sure it could be tweaked a little, but I don't think it's obvious what that tweak would be.
keithb said: Did you say how old these players were? Expand From memory I set them to age 20, and they were age 23 at the end of the loan test.
It's worth saying a few extra things here. I picked this age for two reasons:
1) Age 14-18 is too young for both loans and loan tests. At that age, training takes precedence over match experience (U18s/reserve friendlies largely suffice). Your own training facilities and staff are also likely going to be better than the team you're loaning to, and your training regime certainly will be better. As a player goes beyond 18, the development increasingly skews strongly towards competitive (high reputation) match experience instead of training.
2) I think age 20 is probably the typical age we would start looking to loan out a player, as they're about to be too old for the reserves and/or want to start matches, but not good enough to sell or play.
Combining this info, we can infer that training facilities only matter a little for your loan club. It also means you should probably hold off on loaning out players until they're at least 20.
What about players that already reached 20/20 pace and acceleration? I remember reading something about it somewhere, some time ago, but can't remember the consensus. Is it worth it to keep Quickness as individual training? Expand I guess I would put a training individual focus on dribbling, stamina, balance, agility in that order - or any of the key attributes that are below ~10-12. If they hit PA and start losing quickness, I would train that again.
The quick summary is that matches played and division being inactive are the two most critical factors that you should target when loaning players out.
Beyond that there are some things to keep in mind:
- CA growth is hard capped by the division reputation. Your loan club choice should therefore be a delicate balance between their division reputation and the likelihood the player will play matches. It's probably best to go on the safe side and drop a division than risk not being played. - Club reputation also plays a role, but should be a secondary consideration to division reputation (the influence on CA growth is roughly a 30/70 split, but the club rep difference within a division will only amount to ~5% or less difference anyway) - Morale, rating, opposition quality, probably all have zero or close to zero impact on growth - CA-PA gap remains one of the strongest growth factors, after matches played - Although not tested specifically, it's clear that training facilities (and other club aspects) matter only a bit - A player can improve roughly ~20 CA in one season, so your player's CA should probably be at least ~20 under the division rep hardcap - In England the worst team seems to have its hardcap around ~40-50, so even the worst teams will still enable growth in some players provided their starting CA is low enough
Rough Guide:
140 CA player - Loan to inactive foreign league where possible, or no lower than England Div 2 88 CA player - Loan to inactive foreign league where possible, or no lower than England Div 7 and no higher than England Div 4 30 CA player - Can be loaned to even the worst club in the country and will still grow, so limit to 'Lower Division' clubs
Generally speaking it seems more forgiving placing the player in too low a division than one too high. A 88 CA player should ideally be in Switzerland Div 1 or England Div 4, but England Div 7 would still permit a season of maximum growth while guaranteeing his match experience.
The foreign clubs below I have handpicked as what should be some of the best performers. The only surprise is that the Scottish club did poorly, even when inactive, and I'm not sure why. So I would avoid Scotland for loaning players out.
Lower CA when the division is active is a sign that the division is highly competitive, which is bad from a loan perspective. What we want is high reputation but low competition (increased chance of matches played). If you had to choose an active division to loan to, I would choose South Korea Div 1. But inactive is simply best.
Results (3 year loans):
88 CA 200 PA, Inactive
England Div 2 (Preston) = 102 CA England Div 3 (Blackpool) = 97 CA England Div 4 (Doncaster) = 134 CA England Div 5 (Eastleigh) = 114 CA England Div 6 (Worthing) = 100 CA England Div 7 (Chesham) = 107 CA England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 149 CA Australia Div 1 (Melbourne City FC) = 135 CA USA Div 1 (St Louis CITY) = 144 CA Norway Div 1 (Stabaek) = 139 CA South Korea Div 1 (Pohang) = 148 CA Scotland Div 1 (Hearts) = 102 CA
88 CA 200 PA, Active
England Div 2 (Preston) = 96 CA England Div 3 (Blackpool) = 90 CA England Div 4 (Doncaster) = 110 CA England Div 5 (Eastleigh) = 114 CA England Div 6 (Worthing) = 114 CA England Div 7 (Chesham) = 105 CA England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 94 CA Australia Div 1 (Melbourne City FC) = 116 CA USA Div 1 (St Louis CITY) = 96 CA Norway Div 1 (Stabaek) = 141 CA South Korea Div 1 (Pohang) = 141 CA Scotland Div 1 (Hearts) = 92 CA
88 CA 200 PA, Active, Full Detail
England Div 2 (Preston) = 111 CA England Div 3 (Blackpool) = 91 CA England Div 4 (Doncaster) = 127 CA England Div 5 (Eastleigh) = 113 CA England Div 6 (Worthing) = 117 CA England Div 7 (Chesham) = 107 CA England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 92 CA Australia Div 1 (Melbourne City FC) = 90 CA USA Div 1 (St Louis CITY) = 95 CA Norway Div 1 (Stabaek) = 118 CA South Korea Div 1 (Pohang) = 132 CA Scotland Div 1 (Hearts) = 91 CA
140 CA 200 PA, Inactive
England Div 2 (Preston) = 159 CA England Div 3 (Blackpool) = 149 CA England Div 4 (Doncaster) = 140 CA England Div 5 (Eastleigh) = 140 CA England Div 6 (Worthing) = 140 CA England Div 7 (Chesham) = 140 CA
Switzerland Div 1 (Zurich) = 181 CA Australia Div 1 (Melbourne City FC) = 183 CA USA Div 1 (St Louis CITY) = 159 CA Norway Div 1 (Stabaek) = 170 CA South Korea Div 1 (Pohang) = 170 CA Scotland Div 1 (Hearts) = 163 CA
20 CA 200 PA, Inactive
England Lower Div (Bagshot) = 40 CA
100 CA 130 PA, Inactive
England Div 2 (Preston) = 109 CA England Div 3 (Blackpool) = 100 CA England Div 4 (Doncaster) = 105 CA England Div 5 (Eastleigh) = 100 CA England Div 6 (Worthing) = 99 CA England Div 7 (Chesham) = 100 CA
Switzerland Div 1 (Zurich) = 110 CA Australia Div 1 (Melbourne City FC) = 117 CA USA Div 1 (St Louis CITY) = 110 CA Norway Div 1 (Stabaek) = 110 CA South Korea Div 1 (Pohang) = 110 CA Scotland Div 1 (Hearts) = 109 CA
but people don't use the ratings for that, they use to find the best players, so when you put in your ratings ZERO for long shot, technique, first touch, etc. It will fall apart. It will not show the best players, but the more cost effective maybe.
Take a look at your picture here from GenieScout, there is a GK from KV Mechelen 112Ca better than Mamardashville 148ca..near as good as Diogo Costa and Verbruggen.
But he is not that good, am i right?
Your rating show that, well forGk with 110-120ca he is the best cost effective in the game but not the best player to play for my team now.
There is no way in hell Courtouis it's not the best Gk in the game, there is no way a Gk from Indepediente Del Valle and Burnley better than Oblak, just because the Aerial Reach and Pace (???) is a little bit better than Oblak (discredit for all other atributes).
So you misguiding people when we talk about find the best players to play for my team now.
But you help a lot, and helped me a lot when we talk about cost effective for training.
For many attributes, including all the ones you mention, there is simply no benefit to having them. They are in fact often a net negative because they take up CA, reducing available CA for useful attributes such as pace/acc and slowing development (CA-PA gap strongly influences growth).
That may sound hyperbolic, but consider the following example:
A player has 5 extra passing.
+5 passing = Approx +0.96 win rate according to HarvestGreen's data
I took a random 140 CA player and gave him +5 passing. His RCA went to 142 CA. So +2 CA for +5 passing.
If I give him +1 acceleration instead, his RCA is 143. So +3 CA for +1 acceleration.
+1 acceleration = Approx +4.78% win rate according to HarvestGreen's data.
If we adjust the CA to match, it's +0.96 (passing) vs +3.186 (acceleration).
So extra passing is just losing.
That's HarvestGreen's data.
For my own reference, I use my own data. I change an attribute from 1 to 20 for all players in a team, and if the team has an identical or worse position after a full season, I say that attribute is worthless, end of story, and mark it '1'. If going from 1 to 20 changes the position by 1 place, I put it in my weights - even if it costs a lot of CA. An example of this is strength.
A zero weighting does not mean they are penalized for having the attribute, it just doesn't give them an advantage for it.
Now as for saying Messi is obviously better than Joe Blow from Slough.. I have resigned myself to not making presumptions. First off, I'm not an expert on every great player in the footballing world, and my knowledge is probably a bit outdated. Second, it would obviously be a form of confirmation bias to judge results by name recognition.
The gold standard for me is results. I have compared a few top strikers, testing them in the same league as a control.
A good second option I believe is to see who the top clubs actually start with or buy. You say Courtois is not the best GK in the game. Well, he's the 1st choice GK for Real Madrid, and in a save I checked he averaged 7.21 rating over 5 years with 2 runner-up World Goalkeeper of the Year Awards and 3 third-place awards, which doesn't sound too shabby to me. I guess my question to you is.. on what basis do you know he is not one of the best GKs?
In regards to best players vs CA cost-effective, the current weightings I present do not take CA cost-effectiveness into account. I previously have, if you are familiar with the 'Blended' vs. 'Pure Performance' files. The only way it is currently coming into consideration is as follows:
Suppose I test X attribute
'20' finishes 5th. '12' finishes 5th. '11' finishes 6th. '10' finishes 7th. '9' finishes 10th.
My thinking would be that I should choose somewhere between '10' and '12'. If attribute X is very CA costly, or more importantly difficult to find/train, then I will likely choose '11' or possibly '10'. Otherwise I will choose '12'.
How you should actually present your argument therefore is that I should target 1st, not 7th. But I think your typical player is taking Slough to the Champions League, not assembling the World's best XI in Season 1.
I mean honestly, what do you even suppose to propose? I can only imagine you would suggest weighting passing as 5 instead of 0 for example. But then you would have 36 year olds giving Div 2 strikers a run for their money, because their 16s in various dud technicals & mentals would make up for the difference in speed.
Initially I explained things in more extensive and precise detail, but realized it would be too burdensome to read through.
It's still fairly long and could do with another touch up soon, but it has new sections and new info.
For instance I have previously characterized newgen PA as essentially:
40% Junior Coaching
25% Youth Recruitment
25% Nation Youth Rating
~10% Game Importance
0% Youth Facilities
and also have tried to emphasize that Unique Nation ID matters a lot - as important as junior coaching or more.
But I've never discussed the randomness factor, let alone put a precise figure on it. And many people just handwave discussion of newgens away with 'it's all dominated by randomness anyway'.
So I think it is time to start determining and stating just how random it is exactly. After a brief thinkle I've put it at 50% and junior coaching at 13% for a comparison, but this is just a starting point for a more precise estimation.
Passing, first touch, long shots, and technique have negligible benefit or even possibly negative correlation for outfield players.
If you don't want to take my word for it, refer to HarvestGreen's data on this:
You're also not attempting a fair example. No players are going to have 20 passing, first touch, long shots, and technique. Nor is a player going to have 20 dribbling and 5 in those other stats.
the problem is people trust this ratings blindly i made tests with this rating with gsscout and it show goalkeepers with 100 or 110 pa better than great goalkeepers just because they are tall and have enough aerial reach and jumping reach to surpass lack of reflexes, 1-1, etc.
If you doubt it, you can edit an English Premier League's team in the editor to match these attributes and see if they come ~7th in combination with Knap tactic as I claim they do. For hiddens, convert the values here (simply divide by 4).
It requires a bit of work, but the difficult legwork is already done. It would take about 30 minutes, and then perhaps another 30 minutes to test.
I have tried to state clearly that while the attribute templates are very reliable (plug those figures in and you *will* get 7th on average and with not too much variation), weightings have the downside of being unable to distinguish between 1 acc/20 pace and 10 acc/10 pace.
You mention 'prem 1.0 ratings that show pace is more important for a GK than reflexes' and 'aerial reach and jumping reach to surpass lack of reflexes, 1vs1', which are examples of this inherent lack of discrimination. I have attempted a weighted weights version in attempt to try and compensate for this problem, however my comparison testing found that it did performed worse than the standard Premier League 1.0 weights under normal playing conditions (8.333 position result average vs 7.333 for standard Premier League 1.0 weights).
The comparison tests included a control of Orion's weights, which averaged 13.166 position, so my weightings are definitely worth using above any random set of values, and I daresay anyone else's weights presented so far.
You say that my weightings 'show goalkeepers with 100 or 110 pa better than great goalkeepers'. This irks me because this is just straight up disinfo. Now maybe what you mean to say is that sometimes a 100 CA goalkeeper can supposedly perform at the highest level, but cmon man, anyone can load up my ratings with the starting database in 3 minutes and see this:
I genuinely have this feeling that a goalkeeper with poor Reflexes is basically a walking sieve, haha! But at the same time, what you said makes perfect sense, because a goalkeeper isn't supposed to save everything on his own.
I'll post a screenshot so you can tell me what you think. This was my goalkeeper: he conceded 58 goals over the season. I replaced him the following year, but according to the ratings he's still considered the best goalkeeper in my save... despite having only 9 Reflexes. That just feels strange to me.
Anyway, thanks again. I also noticed you mentioned FMSuperScout. I've never used it before. Is it as accurate as Genie Scout when it comes to calculations and visible attributes? I see that FMSuperScout also takes hidden attributes into account, so it's definitely worth testing. I'll have a closer look at it. If you've already done some testing with it, I'd be really interested to hear your thoughts, especially regarding the reliability of its ratings and percentages.
One last thing: would it be possible to talk to you via DM instead of posting publicly here? Do you accept private messages? If not, no worries at all!
Thanks again, and speak soon!
The only issue with that player is the 9 reflexes. I would expect that player to do better than 6.7 rating in England Div 3. Could it be that the player has poor hiddens?
It's an inherent downside of weightings that it can't distinguish between (1 pace/20 acc) and (10 pace/10 acc). I think it can be mitigated in various ways though, similar to how there are perceptual tunings available in video encoding to improve the subjective quality.
I have attempted this by weighting the weightings, which you can find here. Here are the weighted weightings for GK, which I haven't posted before:
It's a trade off where determination for GK is hardly taken into account anymore, but on the other hand aerial reach will always get the priority it deserves. It should be an improvement, because it's worse to be deficient in aerial reach than in determination.
But in a controlled test of it, it finished position 8.5 on average, which was worse than 7.333 for the standard Premier League 1.0 file. I will still be going down this route further, but that is where things are at right now. You can try using these weighted weights if you like.
I respond to DMs but obviously I only have the bandwidth for a few people from time to time
Pace: 6, Acceleration: 6, JumpingReach: 5.2, Dribbling: 5.2, Balance: 4.8, Concentration: 5.2, Anticipation: 5.2, Determination: 5.6, Agility: 4, Stamina: 5.2, Composure: 4.4, WorkRate: 4.4, Aggression: 4.4, ImportantMatches: 5.2, NaturalFitness: 4.8, Consistency: 5.2, Pressure: 5.2, Professionalism: 5.2,
};
And why is the highest value 6 if the scale goes up to 20?
Does what need to be changed? Seems correct
My presumption is that the weights are relative to each other rather than absolute. The results appear similar to FM26 Scoring System, so I haven't bothered verifying. I've simply divided by my weightings by 10.
You can find my instructions on how to use my weights with the program here.
Regarding the Premier League 1.0 ratings, I feel like the goalkeeper ratings are a bit off. Quite often, average or even poor goalkeepers end up with very high percentages. In fact, the highest-rated player in my save is a goalkeeper with only 9 Reflexes who conceded 58 goals during the season. Do you think there's any way to improve the goalkeeper ratings in the file?
You also mentioned the Genie Scout bug regarding hidden attributes. In your original FM26 ratings file, hidden attributes are taken into account. I'm completely willing to modify the Premier League 1.0 ratings file to include only the hidden attributes, but do you know what weights or values they should be given? Would it simply make sense to import the hidden attribute weights from the original FM26 ratings file into the Premier League 1.0 file?
Thanks again in advance for your reply. What you're doing is genuinely impressive, and I really appreciate the amount of work you've put into it. I'll definitely continue supporting your work in the future.
For reference, these are the optimal minimum set of attributes for GK derived from testing:
The proper version has 8s instead of 1s, but this makes it clearer what attributes matter and which don't.
I've had a double check and it seems to be working as intended. The top rated GKs are the ones you'd expect to be (1st GKs from the very top clubs), and if I filter for current rep 5000< or 3000< then the top players even if low in value or have weird looking distribution of attributes nonetheless are getting high ratings and are getting picked up by higher clubs which are strong indications it's on the right track.
Some examples:
Keep in mind that a GK alone is not going to stop goals. The results depend largely on the rest of your team. HarvestGreen concluded that a GK is worth 20% of an outfield player. My impression is that it's quite a bit more than that, but a GK alone certainly won't save a bad team. What I assess by is the improvement or drop in league position.
In regards to Hidden Attributes in Genie Scout, the problem is not that I can't work out what weighting to give them - you can find those weightings here. The problem is that GS does not calculate using those weightings correctly. It uses some complex formula that makes setting them accurately difficult if not impossible. Think of it as two curves that don't match up and therefore can't be integrated together even if you work out what those curves exactly are, this is the challenge I'm facing. The band-aid solution right now is to combine the weights with a basic filter for hiddens (i.e. min 8 pro, pressure, etc.).
Now if you use FM26 you may be in luck because there is now a program that can do what we're looking for. See my post below this.
For anyone interested in using my weightings with it, what you need to do is the following:
1) Go to install folder
2) Go inside 'app' folder
3) Open 'app.js' with notepad
4) Find 'meta-score (FM-Arena attribute testing)'
5) replace the weightings with the following and save:
Pace: 6, Acceleration: 6, JumpingReach: 5.2, Dribbling: 5.2, Balance: 4.8, Concentration: 5.2, Anticipation: 5.2, Determination: 5.6, Agility: 4, Stamina: 5.2, Composure: 4.4, WorkRate: 4.4, Aggression: 4.4, ImportantMatches: 5.2, NaturalFitness: 4.8, Consistency: 5.2, Pressure: 5.2, Professionalism: 5.2,
This fixes the inability to weight hidden attributes that Genie Scout & FM26 Scoring System suffer from. I assume it calculates properly..
bf3metro said: Hi @GeorgeFloydOverdosed,
I noticed that some people have been criticizing your ratings file. I've been using your FM26 Genie Scout Ratings file since almost the beginning of FM26. Then I stopped playing around February and only came back in June. Since then, I've still been using the FM26 Genie Scout Ratings file, but I recently saw that you now recommend using the Premier League 1.0 Genie Scout Ratings file instead.
First of all, congratulations on all the work you've put into this. It's rare to see this level of dedication and effort.
I have three questions:
Are you still actively improving and refining your ratings file?
If you had to estimate it, how reliable and accurate do you think the Premier League 1.0 ratings are, as a percentage?
Finally, which file should we actually be using: the FM26 Genie Scout Ratings file or the Premier League 1.0 Genie Scout Ratings file?
That's all! I hope you'll have the time to reply. Thanks again for all your hard work, and have a great day!
I recommend the Premier League 1.0 file, while using filtering for hiddens. It is designed to 'save' you in your first season, but I think this is the right balance and does not impair min-maxxing.
It would be less accurate for FM26 most likely, but I suspect the difference would be small.
This question gets asked a lot, so I'll briefly explain why. Take long shots - it's ~3x importance in FM26 supposedly, ok that's 3x0 = 0 for me.. maybe that ends up being a 10 minimum for the attribute, which is a minor difference since most players will have ~6-8+ by default anyway. Going by HarvestGreen's data, there don't seem to be any paradigm-shifting changes, and the thing is, if you suppose balance now has say a '16' requirement, that's highly unlikely to be the case because very few players would have 16 balance in the game. If I had to make a rough guess, the differences between FM24 and FM26 might be a player going from rank 57th > 68th say. Not nothing, but nothing huge either.
The ratings file will continue to be improved, but there is no set timetable.
The main goals I would like to achieve are:
1) Re-integrate hidden stats again. Either with a program that comes along that can do so, or by essentially backporting the rankings FM26 scoring system gives and fiddling with the numbers until it largely fits the mold.
2) Create a FM26 version. Waiting until FM26 is free on Epic, or otherwise settle for working with HarvestGreen's FM26 data. It's not unfeasible, it's just a lot of effort for little reward whichever way I do it.
3) Further improve attribute value accuracy and weightings accuracy. Ideally I want to be able to say this is player is 5th, that player is 6th, etc. with high confidence.
If I had to put my impression of the accuracy of my GS rating files as a % based purely on intuition, I would put it like this:
88% - Premier League 1.0 (in FM24)
83% - Premier League 1.0 (in FM26)
82% - FM24 Pure Performance
80% - FM26 Pure Performance
75% - If you just plugged in pace/acc at 100 weight and added a few others as keithb suggests (basically every simple interpretation of HarvestGreen's data)
70% - File based on Orion's data
56% - Default Genie Scout
I can't say I even trust my own intuition on this though. I know the attribute figures are very close to accurate, translation to GS weights is another matter. Here is what the first control testing showed (number is average finishing position in Premier League):
6.5 - FM24 Pure Performance
7.333 - Premier League 1.0
13.166 - Orion's weights
So I think there's pretty clear evidence it works well, but my intuition about Premier League 1.0 being an improvement over the previous version may be wrong. I still think Premier League 1.0 is better, because it's based on solid data (my extensive attribute testing). It could just be that beyond a certain point, further precision is superfluous (i.e. if one file gives 73.54% and the other 72.88%, you're going to end up picking the same player anyway). I anticipated this and measured overlap of players. From memory the overlap was only around 50% for all three, so there is still substantial variation going on, which was actually quite surprising to me.
BrushlessPlaymaker said: Still on this topic:
Like I said, I prefer may saves with generated players rather than real ones and, since you mentioned it, I'm noticing a lot of young and potentially good player with very low jumping. Is it worth it trying to train that up? I've switched a couple of my own players with decent pace/Acc from quickness to Strength Individual training (which supposedly improves strength and jumping reach) but I'm yet to notice improvements.
I assessed alternative training focuses and found it to be a bad idea. But if a player is particularly deficient in a certain key attribute, it is probably worthwhile training them up to ~8 in that attribute.
With jumping reach, would it be worth say training up further to 12 instead of pace 16 > 18? It's hard to say. Personally I would just get the high jump reach player to begin with, because it will take time anyway, and jumping reach is particularly unforgiving if you lack it. You can get away with 14 pace; you can't get away with DCs that have 14 jump.
This set of guidelines for Italian FM volunteer researchers for FM20 is something of a goldmine when you plug it into Google Translate. Most of the FM info dished out by SI staff is pure BS, but here we have some tidbits of proper info about how it works under the hood.
There are two interesting things in it on height specifically:
1) There are conversation tables for height to jumping reach (one for GK, one for outfield).
2) Pace - 'Very short players cannot have a very high Speed value (at most they will have a high acceleration value)'
This means you can use minimum height to help filter players in the starting database, as the researchers have to follow these strict guidelines in the player data they're putting in.
We can deduce that a player under 1.95m won't ever reach 20 jump even with training. 1.87m would be the minimum to eventually reach 17 jump (ideal minimum for DC). 1.82m is the bare minimum for a DC. Under 1.72m would be too deficient in jumping reach in any position, and should probably be avoided.
We are told that short players are pace-constrained to boot as well.
Now that is the starting database, but if you think about it, they've probably programmed the game to generate new players according to the same guidelines.
I wouldn't know as I haven't used those mods, because I like playing the same game mostly everyone else is playing.
I suspect that problems may arise if you make meaningful changes in isolation. For instance if you somehow reduced the importance of physicals to winning, that would probably mess up the transfers side of the game.
So if I'm using the file to figure out the "best XI" of my team for a given tactic at a given date, your earlier "FM26 GS file" would make more sense, but for long-game recruiting purposes / understanding best promising youngster from my academy, your new "Premier League 1.0" file is prbly better?
I had to go back over my posts and have a few puffs of the pipe on this one.
I misremembered the reasoning for pace/acc being low. I've been away from it all for about a month.
The goal I had started with in my 3rd iteration was this: Get the pace/acc requirement as low as possible, because getting a full team of 18 pace/acc players your first season in the Premier League isn't realistic. It turned out that ~14-15 was feasible in combination with certain levels of other attributes - it wouldn't win the Premier League, but it would guarantee avoiding relegation and even potentially achieve a continental qualification finish.
Now it's true that I also adjusted the values for training later, however pace/acc remained at 15. And yes, the idea is to train them to ~18, but this is beyond what is strictly necessary to place highly. The idea is that growing pace/acc to 18+ will ensure finishing 1st in the 2nd season onwards.
The history of this can get very confusing, but I think this timeline makes it pretty simple:
Dec 15th - First GS ratings file released.
May 7th - 'FM24 Pure Performance' is released. This is the "best XI" ratings file you have in mind. It is mostly based on HarvestGreen's data.
May 14th - LightningFlik posts the discrepancy that leads me to finding Genie Scout is bugged.
June 12th - 'Premier League 1.0' is released, which is mostly based on my own testing.
June 21st - 'Premier League 1.0' tested in comparison to 'FM24 Pure Performance', with the latter edited to avoid causing the GS bugs. Position results were 7.333 and 6.5 respectively, with Orion's weights as a control being 13.166. I had also created another version of 'Premier League 1.0' which refined it according to the essentiality of the attributes and its result was 8.333. I think I planned for it to become 'Premier League 1.1' but either the result dissuaded me or I forgot about it and took a break.
So I recommend just using the 'Premier League 1.0' file.
I agree that speed and acceleration might be underweighted in the premier league GS file. Jumping reach having high weight is an interesting take, but can you remind me why it has actually higher weight that pace/acc? I feel like nothing should be higher, according to actual testing. Not saying that it's a bad idea, but I wonder the rational behind that choice.
Also, any pointers on how (according to your file, or of general understanding of positional proficiency) we should interpret GS ratings of sub-20 position for a player as per my messages before the interruption?
The reason why pace/acc is now seemingly under-weighted is because it is expected that you will train these up using the quickness focus in training. I have based the adjustment on real training results, not just the optimal possible. They still remain the highest weighted attributes.
Jumping Reach is only weighted higher in 2 positions, DC and ST target man, but generally it is up there with pace and acc. I can't remember all the nuances around it, but here are the key ones I can recall:
1) Jumping Reach is critical on DC and has a high minimum requirement. Something like the difference between 17 and 13 is 5th > Relegated say (you can probably find these results somewhere earlier in the thread).
2) It's not that you just need one or two tall players to do the job, and that having your MC be a bit taller makes no difference. Increases even at mid levels across the team result in significantly better performance.
3) Jumping Reach is harder to train than pace/acc, at least when we assume quickness focus is being used.
I read your post on position proficiency, but don't have anything to contribute to it really. I do make sure to search for players with only green position proficiency in Genie Scout. I've dabbled with position proficiency in various ways, but I don't think to find performance level at 1 proficiency say, and I'm too hazy on it now anyway.
What I will say is that I think certain dual positions that have no CA penalty (i.e. AML/AMR) are beneficial in a practical sense.
I vaguely recall experimenting with playing optimal players out of position to try and cut the CA cost and that it failed miserably. So it does have a big impact.
As I was thinking about this, it was lurking at the back of my mind that I'm sure someone had tested proficiency and I had seen the results once. It took a while, but I think I've found what I was recalling. HarvestGreen tested it:
He also did FM26 OOP proficiency and found the win rate difference between 4 OOP proficiency and 20 OOP proficiency to be 40.9% > 46.4%. Link to thread.
Just to be clear, the process is:
test attributes in isolation + hundreds of possible attribute combinations over thousands of games > record best performing combination of attributes > translate to Genie Scout weightings
not GS weightings > GS Ratings > record winning combination of attributes
So you are confused when you believe my ranking of Mbappe is tied to how well I understand Genie Scout's formulae for hidden attributes.
The translation into weightings works accurately for FM26 scoring system, it is specifically a Genie Scout problem. What FM26 scoring system lacks is the ability to weight hidden attributes.
It is also not a matter of just work out what formula Genie Scout is using and then take that into account. Say it was that personality attributes are weighted at 50% of visible attributes. Ok, then we could just put 80 for pressure instead of 40. It is complicated, and perhaps even completely unworkable. The best way to use Genie Scout right now is to weight the visible attributes, and put filters on the hiddens.
I've answered this before here, here, and here.
Someone else also tried to inform you here, to which you responded that the bottom line for you is your motivation to 'blame the person who made the file'.
This is why I will not be responding to any more Mbappe rubbish from you.
He's not even close to the near perfect player. He will do well for his CA because he's 18/18 speed. Near perfect would see a big increase in dribbling, anticipation and agility and balance. The player also doesn't need jumping reach. Some of the best 10's and wingers ive ever had were under 5 for jumping reach.
Not including his hidden attributes has nothing to do with the score and its deceitful to claim it is. Its also funny. You've still never answered why Mbappe scores so poorly using Premier league 1.0 ratings. But you always avoid questions and go full lockjaw.
There are 14 players in the starting database that have 18 pace/18 acc/14 drib or higher.
I've done testing previously, and have posted about it, that jumping reach is not just necessary in high amounts for certain players - it is an important attribute for all players, and even going from say 8 to 12.
You are also wrong in your claim on the previous page that players age 18 or less benefit from loans. You seem to just reflexively claim the opposite of anything I say. Here is the data from EBFM on the matter:
We see here that for players age 18 or less:
Training with no matches = +17 CA
Matches but no training = +13 CA
Matches & training = +19 CA
By contrast for a player age 21:
Training with no matches = +1 CA
Matches but no training = +4.5 CA
Matches & training = +9 CA
Now factor in the following:
1) Your team (likely) has better training facilities, staff, and most importantly, uses a top training schedule
2) Your player age 18 or less is more likely to be inadequate to play in a decent division and either will be hard-capped by the low division rep, or simply not start games
And even if the planets did align, it would only be for ~10% extra growth. By contrast, a player age 21 simply doesn't grow without competitive matches. For a player age 20 it remains possible that keeping them at the club in the reserves is better than loaning them out (training no match vs. match no training).
being rated at 64, seems unfair. He's a beast, only downside I see is his determination. If I follow these ratings, he won't make the bench in the Portuguese league, where I'm still dominating by far with a team with avg rating way lower than the best in the league.
Can someone clarify this Premier League 1.0 ratings? I was using Orion's and Bafici's rating's a while back, what is everyone's opinion on theese ratings?
I'll have a look into it a bit later, but two things are obvious to me here:
1) That is a near perfect player, if you compare his attributes to what I've found to be the ideal set of attributes. The only thing lacking is jumping reach, which is quite important.
2) The Premier League 1.0 GS rating file does not weight hidden & personality attributes, because Genie Scout is too bugged to include them. I haven't given up on this forever, but at the moment there's no viable solution. Your player has ridiculously perfect hiddens & personality, even temperament is very close to its optimal of 10 rather than 20. I daresay this is actually this is the main reason the rating is inaccurate rather than the excellent distribution of visible attributes.
You could make the argument that hiddens & personality should be weighted at least somewhat, even if it messes the ratings up a bit, because a 4% error might be better than a 8% error say. But a player with those hiddens & personality is extremely atypical.. so if we did this it might end up that yes, your player becomes 4% more accurate rating, but 90% of players become ~1-2% less accurate say. I'm sure it could be tweaked a little, but I don't think it's obvious what that tweak would be.
From memory I set them to age 20, and they were age 23 at the end of the loan test.
It's worth saying a few extra things here. I picked this age for two reasons:
1) Age 14-18 is too young for both loans and loan tests. At that age, training takes precedence over match experience (U18s/reserve friendlies largely suffice). Your own training facilities and staff are also likely going to be better than the team you're loaning to, and your training regime certainly will be better. As a player goes beyond 18, the development increasingly skews strongly towards competitive (high reputation) match experience instead of training.
2) I think age 20 is probably the typical age we would start looking to loan out a player, as they're about to be too old for the reserves and/or want to start matches, but not good enough to sell or play.
Combining this info, we can infer that training facilities only matter a little for your loan club. It also means you should probably hold off on loaning out players until they're at least 20.
Went back to FM24 and this was a major tim saver. One question tho:
What about players that already reached 20/20 pace and acceleration?
I remember reading something about it somewhere, some time ago, but can't remember the consensus. Is it worth it to keep Quickness as individual training?
I guess I would put a training individual focus on dribbling, stamina, balance, agility in that order - or any of the key attributes that are below ~10-12. If they hit PA and start losing quickness, I would train that again.
The quick summary is that matches played and division being inactive are the two most critical factors that you should target when loaning players out.
Beyond that there are some things to keep in mind:
- CA growth is hard capped by the division reputation. Your loan club choice should therefore be a delicate balance between their division reputation and the likelihood the player will play matches. It's probably best to go on the safe side and drop a division than risk not being played.
- Club reputation also plays a role, but should be a secondary consideration to division reputation (the influence on CA growth is roughly a 30/70 split, but the club rep difference within a division will only amount to ~5% or less difference anyway)
- Morale, rating, opposition quality, probably all have zero or close to zero impact on growth
- CA-PA gap remains one of the strongest growth factors, after matches played
- Although not tested specifically, it's clear that training facilities (and other club aspects) matter only a bit
- A player can improve roughly ~20 CA in one season, so your player's CA should probably be at least ~20 under the division rep hardcap
- In England the worst team seems to have its hardcap around ~40-50, so even the worst teams will still enable growth in some players provided their starting CA is low enough
Rough Guide:
140 CA player - Loan to inactive foreign league where possible, or no lower than England Div 2
88 CA player - Loan to inactive foreign league where possible, or no lower than England Div 7 and no higher than England Div 4
30 CA player - Can be loaned to even the worst club in the country and will still grow, so limit to 'Lower Division' clubs
Generally speaking it seems more forgiving placing the player in too low a division than one too high. A 88 CA player should ideally be in Switzerland Div 1 or England Div 4, but England Div 7 would still permit a season of maximum growth while guaranteeing his match experience.
The foreign clubs below I have handpicked as what should be some of the best performers. The only surprise is that the Scottish club did poorly, even when inactive, and I'm not sure why. So I would avoid Scotland for loaning players out.
Lower CA when the division is active is a sign that the division is highly competitive, which is bad from a loan perspective. What we want is high reputation but low competition (increased chance of matches played). If you had to choose an active division to loan to, I would choose South Korea Div 1. But inactive is simply best.
Results (3 year loans):
88 CA 200 PA, Inactive
England Div 2 (Preston) = 102 CA
England Div 3 (Blackpool) = 97 CA
England Div 4 (Doncaster) = 134 CA
England Div 5 (Eastleigh) = 114 CA
England Div 6 (Worthing) = 100 CA
England Div 7 (Chesham) = 107 CA
England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 149 CA
Australia Div 1 (Melbourne City FC) = 135 CA
USA Div 1 (St Louis CITY) = 144 CA
Norway Div 1 (Stabaek) = 139 CA
South Korea Div 1 (Pohang) = 148 CA
Scotland Div 1 (Hearts) = 102 CA
88 CA 200 PA, Active
England Div 2 (Preston) = 96 CA
England Div 3 (Blackpool) = 90 CA
England Div 4 (Doncaster) = 110 CA
England Div 5 (Eastleigh) = 114 CA
England Div 6 (Worthing) = 114 CA
England Div 7 (Chesham) = 105 CA
England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 94 CA
Australia Div 1 (Melbourne City FC) = 116 CA
USA Div 1 (St Louis CITY) = 96 CA
Norway Div 1 (Stabaek) = 141 CA
South Korea Div 1 (Pohang) = 141 CA
Scotland Div 1 (Hearts) = 92 CA
88 CA 200 PA, Active, Full Detail
England Div 2 (Preston) = 111 CA
England Div 3 (Blackpool) = 91 CA
England Div 4 (Doncaster) = 127 CA
England Div 5 (Eastleigh) = 113 CA
England Div 6 (Worthing) = 117 CA
England Div 7 (Chesham) = 107 CA
England Lower Div (Bagshot) = 88 CA
Switzerland Div 1 (Zurich) = 92 CA
Australia Div 1 (Melbourne City FC) = 90 CA
USA Div 1 (St Louis CITY) = 95 CA
Norway Div 1 (Stabaek) = 118 CA
South Korea Div 1 (Pohang) = 132 CA
Scotland Div 1 (Hearts) = 91 CA
140 CA 200 PA, Inactive
England Div 2 (Preston) = 159 CA
England Div 3 (Blackpool) = 149 CA
England Div 4 (Doncaster) = 140 CA
England Div 5 (Eastleigh) = 140 CA
England Div 6 (Worthing) = 140 CA
England Div 7 (Chesham) = 140 CA
Switzerland Div 1 (Zurich) = 181 CA
Australia Div 1 (Melbourne City FC) = 183 CA
USA Div 1 (St Louis CITY) = 159 CA
Norway Div 1 (Stabaek) = 170 CA
South Korea Div 1 (Pohang) = 170 CA
Scotland Div 1 (Hearts) = 163 CA
20 CA 200 PA, Inactive
England Lower Div (Bagshot) = 40 CA
100 CA 130 PA, Inactive
England Div 2 (Preston) = 109 CA
England Div 3 (Blackpool) = 100 CA
England Div 4 (Doncaster) = 105 CA
England Div 5 (Eastleigh) = 100 CA
England Div 6 (Worthing) = 99 CA
England Div 7 (Chesham) = 100 CA
Switzerland Div 1 (Zurich) = 110 CA
Australia Div 1 (Melbourne City FC) = 117 CA
USA Div 1 (St Louis CITY) = 110 CA
Norway Div 1 (Stabaek) = 110 CA
South Korea Div 1 (Pohang) = 110 CA
Scotland Div 1 (Hearts) = 109 CA
50 CA 80 PA, Inactive
England Lower Div (Bagshot) = 50 CA