For whatever reason it seems to me that people take FM Arena's testing rather than HarvestGreen's as a starting point, so I'll begin with that:
So we see here that stamina is moderately, not highly, important. Specifically it is 29.7% of either acceleration or pace.
Two important things to note are that points is used a measurement rather than league position, and that we are measuring from 8 > 20 stamina. It's not clear what the makeup of the team or opposition is, but at least it's giving us a fair idea of what to expect in any case.
We see here in HarvestGreen's latest result for stamina that is it 27.1% of acceleration or pace going from 1 > 18.
For 6 > 18 it is 14.1% of acceleration or pace. In other words, stamina is never critical, but becomes even less important beyond '6'. He also has 1 > 6 results showing this.
In his initial attribute test shown here, stamina 10 > 20 is 30.9% of acceleration, which in my view is the most important result in regards to application to the Premier League.
In keithb's GS weightings, stamina is weighted at 60 for DLR/WBLR/DM/MC, 20 for AMLR/ST, and 0 for DC.
What this no doubt reflects is the now outdated myth that different positions require different sets of attributes. This is not an article of faith for me; I myself used to believe in, and initially employed, weightings that varied per position. Partly this was because each position has different CA weightings for attributes, and so high stamina for low CA cost on fullbacks seemed like a boon. I suspect that the myth has been generally perpetuated throughout the years with the CA weightings as a primary impetus, and that keithb isn't even aware of this - he seems to just think that stamina is what's necessary to win, simple as that. My mind was changed by the test results.
What my test results found, and seemingly implicitly HarvestGreen's & FM Arena's too, is that pace/acc is just as critical on DC as it is on ST, many attributes such as 'tackling' or 'passing' don't matter at all for any position, and if you try to test for positional differences, there doesn't appear to be any, or at least many. There might be still be some differences - I'm still wondering if pace & acc are of equal importance across all positions for instance, but overall we're talking small differences, not major ones.
Through brute force testing, I found that stamina of 13 is the essential requirement for the Premier League, while pace/acc is 15:
However, you can get away with as low as ~13 pace/acc (think Harry Kane, or Lewandowski), so long as stamina is ~15 or higher. Conversely, a 20 pace/acc player has less need of stamina, and can get away with 12 and no doubt lower.
So if you put all that together, basically stamina should be weighted at ~33% of pace/acc, is what I found.
So you can think of it as either 33% or 86% of acc, perhaps somewhere inbetween. So ~50% roughly. This was a change from the ~15% I previously used, which was primarily based on HarvestGreen's 14.1% 10 > 20 finding.
With my latest weightings, which wipe the slate clean of assumptions and simply try to align weightings with actual real player rankings supported by test results as evidence, I found that only somewhere around ~90% weighting for stamina worked - or ~90-110% of acc. This is far more than even keithb's 60% weighting for sta on fullbacks.
But why is that necessary, and why does it work if so? It is necessary because someone such as Maeda or Furuhashi has very few green attributes, yet ranks above the likes of both all-rounders such as Lewandowski and fairly well rounded high pace/acc players such as Osimhen. If you analyze it carefully (you need to compare multiple players in conjunction to find out it can't be his high work rate, det, aggression, etc.), the only way to make the rankings align seems to be to boost stamina to such a high weight. Perhaps I've missed some other option, but this where I'm at. As to the explanation as to why it is so, it makes more sense once you realize that stamina is preserving both pace and acc, so its value is doubled, and it is preserving the two most valuable attributes.
No one that I'm aware of has previously come to these conclusions about stamina. Even the overlap between this and the old 'stamina for fullbacks' myth doesn't extend this far. And it puts a big dent I reckon in the general pervading view that pace/acc is everything, which was always sort of heard of, but never really solid fact until HarvestGreen's findings. The trouble with the 'pace/acc is everything' explanation is that it failed to account for players such as Kane and Lewandowski. It would be (and still is by some even on this forum!) explained away as compensated by high technical skill such as passing, etc. which is a red herring - these technical skills really are completely useless, and the differences lie in other areas such as stamina, work rate, anticipation, and a handful of select others. 2/3rds of attributes continue to have zero effect on final season position.
I wasn't going to respond but I guess it's good to take stock of where we're at from where we've come from. Instead of vaguely telling a narrative of progress, I'll be presenting precise data for a clear comparison.
Let's start with GKs:
HarvestGreen did 2 seperate tests on GKs.
December 2024:
April 2026:
The first thing I'll draw your attention to is that the results seemingly contradict each other. In the 1st test, acceleration does little to nothing. In the 2nd, it is the third most important attribute, above aerial reach which got a tick in the 1st test. Vision got 2 ticks in the first test, but does nothing in the 2nd test. There are more examples like this.
In skawkclsrn's case the issue is lack of samples, but here the issue is the methodology:
- The 1st test is using a team with 10 in every attribute, and increasing a single GK attribute to 20, then measuring the goals conceded. The first two aspects underlined are potential problematic factors, for instance what if a GK needs better reflexes and agility because the outfield is deficient in speed - perhaps with a speedy team, a GK only needs aerial reach to handle potshots he can see coming from afar. That is just a minor critique to show even solid tests can have pitfalls. The real problem is measuring the goals conceded, because as shown in my testing results, goals conceded is not at all a consistent measure of success, similar to how league points is all over the place compared to final league position. It will give some correlation, hence why agility, reflexes, and aerial reach all correctly have ticks, but that is just because teams who finish 1st obviously concede less goals than teams that finish 20th.
- The 2nd test is starting with the GK at '20' in all attributes and setting 1 attribute to '1'. This is different to how HarvestGreen does his outfield tests, which increase/decrease from '10'/'12' for all attributes, and it's obviously less realistic to begin with. But the main issue, only evidenced by my own testing later, is that having all attributes at '20' is likely compensating for and obscuring certain deficiencies. So we see that reflexes and agility are pretty much the only 2 attributes that matter, and even then, their individual impact is fairly minimal (12.8% at most).
HarvestGreen also stated that his observation is that GK is 20% of effect of an outfield player, if I remember correctly, which is basically saying the GK should be an afterthought and not really worth worrying about.
All of his tests also carry the same caveat that he is testing against opposition that has identical attributes. For some attributes, such as Jumping Reach, Aerial Reach, Strength, etc. I hope it's obvious how this could constitute a problem when it comes to translating to how things work in real leagues.
Now, coming to my tests. I brute force tested individual attributes for GK until I got a solid picture of what an optimal GK looks like. So what I would do is I would start with all attributes at 1, except a few obviously necessary ones like agil, aer, ref, etc. and measure the position. The initial result might be 13th. Then I would increase each attribute from '1' to '20' and measure the improvement. If no improvement in position, ignore it going forward. After learning what attributes matter and which don't, I would begin refinement, seeing how low I could get an attribute to find the 'sweet spot'. And I also start testing those attributes I took for granted at the start: agil, aer, ref. I would test a few potential combos (i.e. does aer only matter if jump is high?), but obviously it can't be an exhaustive search. Now what I would most often find is something like this:
Usually I would choose 14 to settle on. But if '13' is relegated, or '18' is 1st, then obviously I would likely change that to a '15' - while also considering realistic availability in the game.
Now these are the essential GK attributes I ended up with:
We see from my latest comparative testing of real players within the game, that this player would constitute something of a middling Premier League team GK. This GK finishes ~7th, the best finishes 4th, Barcelona's finishes 6.4, and a League 1 GK finishes 8.4.
One key attribute that is hidden from that screenshot is technique, which turns out to be quite critical for GK. You can also see this reflected in the database data for GKs - the better the GK, the higher technique he is generally given. I actually notice for the first time now that HarvestGreen actually gave a tick next to technique in his 1st test, though in the 2nd it is listed as 0.0%.
It's not clear yet exactly how much a GK accounts for as a % of a team's overall performance, but we can see the GK is more critical to success than HarvestGreen gave the GK credit for. My current estimation is somewhere around ~66-100% of an outfield player.
So we know my template works. Let's compare to what we 'knew 2 years ago', which is HarvestGreen's data and nothing else:
- HarvestGreen found vision and pace, and later reflexes, to be the most important attributes. I found vision '1', pace '13', and reflexes '11' are adequate, while aerial reach is the most essential attribute. - HarvestGreen summed up that GK is has 20% impact of outfield player. My evidence shows it's much more than that, even the difference between relegation and a top 5 finish at times. - Generally speaking, there was no solid data on GK at all previously. Now I've provided you with a precise template for GK that is backed by solid evidence in the form of testing both real & artificial players in a real and popular league (English Premier League).
If I've missed anyone else's findings on GKs, that was any good, let me know.
Alisson - 6th, 3rd, 4th, 4th, 3rd = 4 position Thibaut Courtois - 3rd, 7th, 2nd, 5th, 8th = 5 position Jan Oblak - 5th, 8th, 6th, 4th, 3rd = 5.2 position Marc-Andre ter Stegen - 10th, 11th, 4th, 4th, 3rd = 6.4 position Anatolii Trubin - 15th (sacked), 6th, 4th (sacked), 5th = 7.5 position Jack Stevens - 13th (sacked), 4th, 9th (sacked), 8th (sacked), 8th (sacked) = 8.4 position Sinan Bolat - 4th, 2nd, 19th (sacked), 5th, 14th (sacked), 9th (sacked), 12th (sacked), 5th = 8.75 position
I removed Courtois' starting injury to test him.
It shows that GK does in fact matter, though it does seem a lot more variable - in the downwards direction.
So although a GK can't really make your team win much more, they can in fact make or break your team.
Observations through player comparison:
- Jack Stevens is a mediocre all rounder who normally plays for Cambridge, and show you can't really get away with playing mediocre GKs - Bolat is interesting.. he is like Stevens, but a tier above, but has green reflexes and jumping reach. Shows good reflexes aren't sufficient. - Trubin, like Bolat, also significantly underperforms. He has green Aer, Jump and Handling. None of these are sufficient alone therefore, even with seemingly above average values in all other areas.
We know that the following GK finishes ~5th and with good consistency too:
This GK finished 7th:
It seems like only a select few of real GKs can do better than the above players.
If I filter for attributes of that second GK (excluding natural fitness), no players come up.
It seems that GK is about what is the least worst deficiency do they have. I suspect it is this way so that, unlike the outfield, you don't get great GKs who make teams come 1st by the mere addition of themselves. Perhaps this also explains why GKs can't get really high match ratings, because their best is merely adequate.
Trubin has a slightly deficiency in determination, pace, acceleration. Alisson is only lacking 1 pace. Oblak slightly lacks first touch, acceleration, and agility.
To verify the theory, I reduced the filter by 1 for the attributes and tested the worst one of the 4 players that turned up (1 was Ederson @ Man City, 2 were Alisson and his backup GK @ Liverpool, and the worst was Davy Roef from AA Gent).
High variation, but the average result aligns with extra 1 in key attributes finishing ~7th
BTW it's stuff like Alisson's backup GK just coincidentally having exactly the right set of meta attributes that shows me SI are aware of and intentionally making most attributes useless and misleading. If it was an oversight, players that look like duds but nonetheless perform well and are placed in the top teams wouldn't be an identifiable pattern.
Now I know quite a few people are also interested in what kind of GK gives the most clean sheets, or lowest goals conceded. So here are those stats:
Alisson - 13 cln, 48 con | 14 cln, 39 con | 15 cln, 40 con | 14 cln, 36 con | 11 cln, 44 con = 13.4 cln, 41.4 con Thibaut Courtois - 9 cln, 41 con | 12 cln, 48 con | 10 cln, 56 con | 10 cln, 45 con | 11 cln, 50 con = 10.4 cln, 48 con Jan Oblak - 8 cln, 49 con | 11 cln, 43 con | 10 cln, 59 con | 14 cln, 34 con | 15 cln, 40 con = 11.6 cln, 45 con Marc-Andre ter Stegen - 4 cln, 58 con | 10 cln, 53 con | 11 cln, 52 con | 13 cln, 44 con | 14 cln, 46 con = 10.4 cln, 50.6 con Anatolii Trubin - 10 cln, 46 con Davy Roef - 14 cln, 45 con | 13 cln, 44 con = 13.5 cln, 44.5 con Jack Stevens - 16 cln, 41 con Sinan Bolat - 14 cln, 50 con | 10 cln, 52 con | 9 cln, 53 con | 8 cln, 54 con = 10.25 cln, 52.25 con
I only took stats from samples where there was no interruption by sacking.
bf3metro said: Just one small thing I noticed: you said you included Loyalty as “1” at the last moment, but in the weights you posted, Loyalty is 0.2. Is 0.2 the intended final value, or was Loyalty supposed to be 1?
Also, given what you said about Strength, Vision, Finishing, Teamwork and Loyalty, would you say these are attributes we should actually pay attention to when evaluating a player, or are they basically not worth considering unless the value is particularly low/high?
I’m especially wondering about Teamwork since you still seem a bit uncertain about it.
And one last thing: have you also updated the goalkeeper weights, or are these still the current ones?
PS: What is the correct way to write it? Expand Was referring to the FSMT26 weights. For FMSS I divided by 5 because I think it had problems if you put the numbers too large from memory.
Those 5 attributes are not really worth paying attention to.. except loyalty of course, for non-performance reasons. Not only are they low value, they are non-essential. By contrast, agility is also low value, but moderately essential around ~10. Work rate is absolutely essential to have at least 6. You can have 1 strength/finishing/vision and finish 5th, that's proven.
Overall I don't think teamwork does anything. There's just a small element of uncertainty.
GK weights unchanged. I'm currently doing samples of GKs for rankings list.
I think either way you've typed it is fine.. just test each and see
Kriek said: Is it still needed to use the filters with the new ratings on Genie Scout or only the ratings? Expand Only ratings is fine. Filters still useful, but should be able to phase this out later by adding non-linear weights to FMST26 (not GS though).
bf3metro said: I also noticed that you added 5 attributes that weren’t in the previous set: Strength, Finishing, Ambition, Loyalty and Vision.
Was that intentional as part of the new weighting method? Expand Finishing, strength, and vision were technically in the previous weights. I dropped them from the file because the attributes that are adequate you are bound to get at the required levels most of the time anyway:
Strength - 8 Vision - 7 Finishing - 7
I played around a fair bit with strength in particular in these new weights. I thought maybe it's around 10-20, but turned not to be the case. Vision is 20 on Messi which was food for thought, but it didn't seem to affect ranking alignment for the better.
Actually teamwork is the one I most wonder about.. players like Maeda have high teamwork, and there's some mathematical study on FM24 on github that a guy did for university work that found teamwork was a key correlate of performance.. but I read through it, and overall I think its just full of mistaken findings. My own testing and HarvestGreen's found teamwork doesn't matter, so at the moment I don't see a valid reason to include it.
Loyalty I included as '1' at the last moment pretty much symbolically. It would have some very minor to minor effect via morale, so i felt justified giving it a little '1'. But obviously loyalty deserves some weight for gameplay reasons.
bf3metro said: The WorkRate interaction theory is probably the most interesting part to me. If something like Determination × WorkRate × Stamina is happening, it could explain why isolated attribute testing and the ranking weights seem to tell slightly different stories. Expand
The main thing would be the non-linearity of attributes, which the testing did show, but can't be reflected in linear weightings.
HarvestGreen did do some theorizing on attribute interactions, and I've dug up quotes from the Collyer brothers and in-game tips and whatnot which describe attribute interactions as well. I found that those latter things turn out to be generally untrue, or at least outdated.
I reckon there are attribute interactions though, and HarvestGreen's ideas on it are interesting.. just lack the solid data on it at the moment though.
I don't really have solid data to back it, but I'm personally convinced that aggression x dirtiness is an interaction, it just seems logical and seemed to solve something insoluble with the ratings at one point too.
This is partly why I decided to release it as is now with mostly linear weights, because one could go down the rabbit role of trying out all these different attribute combos and either getting nowhere or being mislead into seeing something that isn't there, while also spending a lot of time doing so. It remains difficult to test attribute combinations, but I'm sure there's some method to bear it out properly.
bf3metro said: Also, I noticed there are some strange extra spaces between a few attributes in the list. Is that intentional, or just a formatting issue? Expand Probably a formatting issue
bf3metro said: One other thing I'm wondering: is it possible that some of your original FMSS weights were simply set too low at the beginning, which would also partly explain why a few attributes have increased so dramatically now?
Do you think these huge increases are entirely a consequence of the different methodology, or could your original FMSS weights also have been underestimating some of these attributes from the start? Expand The FMSS weights I gave before simply reflect the minimum set of attribute values to attain 5th in the Premier League. They represent the best 'bang-for-buck' relative ratio of attributes.
I guess the question that the objective ranking raises in relation to that is, if work rate supposedly caps out at 13, why is it so critical for Maeda, and important in general? And if dribbling isn't so essential, is it really necessary to include it high - even if it does actually have significant benefits. So it does shine a new light on certain things. Personally I strongly favor what is true in realistic testing (the player rankings derived from the team positions), rather than what the isolated or constrained testing shows (including my own).
johnconnerson said: Where does the 118 number come from? I'm trying to split up the visible and hidden attributes into two separate metrics for my own use. Expand The 118 number is just to get it to display with the highest % at ~90%. It's the same as the overall weight option in GS.
bf3metro said: The biggest question for me is: why such massive changes?
From what I understand, the old weights were based on finding the cheapest/minimum attribute balance capable of achieving around 5th in the Premier League, whereas the new weights are being fitted to a much larger set of objective player rankings.
So it makes sense that the result could be very different: instead of asking “what minimum combination of attributes gets results?”, you're now asking “which attributes best explain the actual ranking of players?” Expand Yes, that is precisely the correct summary of it, and I daresay a better explanation than I did.
I'm glad you immediately understand, because I think it's easy to misinterpret this latest thing I'm doing with the weights.
bf3metro said: The new model seems to put an enormous premium on Pace, Acceleration, Stamina, Work Rate and Anticipation, while attributes such as Dribbling, Consistency, Important Matches or Natural Fitness become much less influential.
And then you have Finishing at only 0.4, which is pretty wild too. Expand I started with the presumption that finishing is almost completely unnecessary, but ChatGPT independently came to the conclusion that finishing should be removed too when I fed it all the player's attributes and asked it to come up a set of weights to fit the rankings.
It was surprising how strongly weighted anticipation and work rate seems to be. Maeda is still down a bit, so work rate could in fact do with being a bit higher perhaps. It's strange to me, because I know that (and you can see HarvestGreen's data to verify this) that work rate almost caps out at 13. But that is when work rate has been tested in isolation or partial isolation. Perhaps there is something like 'determination x work rate x stamina' going on. I couldn't find a way of getting around weighting work rate highly.
Anticipation in my observations did continue to scale, but had diminishing returns. But putting that aside for now, it makes sense that it would be a key attribute because ostensibly it's the movement ('off the ball' as speed?) to the area before possessing the ball. So it sounds like it cuts down on the pace/acc requirement to me, because once they have the ball, they have less distance to travel. Concentration would be a similar kind of effect, where low concentration leads to a delay in getting into position to receive or stop a ball (the latter offset by 'positioning' perhaps).
Consistency, Important Matches, and Natural fitness has not been incorporated with much accuracy. They are kind of afterthoughts, as I know they will matter somewhat, but not sure to what degree. I've used HarvestGreen's data to set them, and so long as they're not interfering with the ranking, I generally leave them alone. Same with pressure, professionalism, etc. - and the left foot & right foot figures I've just pulled out of my ass, to give a little extra weight to the modest footedness bonus which we know exists. This stuff can be refined further later. I think HarvestGreen found that foot should also match the side they're on, and I think FMST26 allows us to do this as well.
Dribbling I've been in two minds about. Most of the time I had it set pretty high at ~40, sometimes as high as 60. I ended up reducing it to 15. ChatGPT actually said early on to do this too. Both were fairly equally functional. From testing, we know dribbling is a very strong attribute that scales well.. I suspect it's not needed much to match the rankings, because hardly any players have high dribbling anyway. It's the hardest attribute to get high in the game I believe.
bf3metro said: PS: Quick question: why are attributes like WorkRate, ImportantMatches, and NaturalFitness written without spaces? Is that just the naming format, and do they need to be written exactly like that in app.js as well? Also, should I add a comma after the final value, Consistency: 2.82, or should the last entry be left without one? Expand Yes, that is how they have to be written for FMSuperScout, otherwise the program won't work. That is how labels the attributes internally.
bf3metro said: Legend! Expand Actually this is proving more difficult than I thought it would be
I'm not a programmer, so I don't know how to implement the injury proneness & dirtiness weights. I thought, maybe I'll just add them as simple negatives, like for the GS weights, and adjust it until it matches the rankings, but then I realized it doesn't do FM24 db, only FM26.
Replace the weights in the app.js file with those (search for 'FM-Arena' ).
For adding injury proneness & dirtiness, which are in fact crucial (but I guess you could also just check players manually to have low inj and dirt values), we're going to need someone like Panneton0 or perhaps the creator of FMSuperScout itself to help out. Could probably do it myself, but can't be bothered doing an hour of research honestly.
bf3metro said: any release for FMSS? Expand Yeah, I left it out because I have to work out how to best translate it from the FMST26 weights first. I'll do that now.
This new file is a lot like mine LOL! Expand You have stamina weighted at 0 for DC, 20 for ST/TS/AMC/AML/AMR, and 60 elsewhere. It's not my fault your own weights contradict your own words.
Meanwhile, the key attribute of dirtiness you leave on 0, as you have 0 clue of course about what attributes actually matter beyond what we knew from HarvestGreen's testing a year or two ago.
But as I've said, you can have a variety of combinations that work to get to match the final ranking result. And at least you're implicitly accepting now that my objective rankings are correct.
Let's do a comparison of our two files to find out just how similar they really are. First, yours:
Junior is 1st for FS, even with 16 ST proficiency. Mbappe is above Haaland. Messi is 5% above Lewandowski and 10% above Maeda. Even Malen is above Maeda. Dybala is above Maeda and Furuhashi. Mbappe (8 jump, 8 head, 11 str) is a better target man than Glatzel (16 jump/head/str). It goes on.
Mine:
There are some minor issues, such as that Maeda should be ~3% higher, and that Malen & Glatzel should have a wider percentage gap between them.
keithb said: Why have you still used negative values and scored the hidden attributes in Genie Scout? Expand The only fair point you've raised in your entire posting history I believe
It is true that hiddens remain invalid for GS. I decided in the end to include them for my final GS adjustment at the end to try and closely match what I got in FMST26, halved for everything except dirtiness & injury proneness & natural fitness. Dirtiness & injury proneness are essential to the weightings, there's no way to do without them.
Because GS calculates incorrectly, the ratings remain a bit off compared to what you'll get in FMST26, hence I highly recommend FMST26, but I know many people aren't going to be willing to switch over.
ZaZ said: If you want people to respect the results of your tests, you need to respect the results of other people too. Saying stuff like "it is all wrong" is not very scientific. Their results are valid for their methodology and data set, and their interpretation is based on the method of their analysis. It is not up to you to decide which of the thesis are more trustworthy. Expand I think you've got the picture wrong.
As I referred to in my post, the OP of that thread said 'For goalkeepers, read the top two or three only.'
I didn't do the full quote, which follows with:
'Reflexes and Agility separate cleanly; below that it is noise, and Handling ranking under Corners is not a finding. One keeper per match against ten outfielders means that column has about a tenth of the statistical power.'
I'm not saying his other findings are 'completely wrong' - only the GK weights.
I'm using my own data to refute the data he got on GKs, that's the sound basis for me saying 'it is all wrong'. And it is up to me to decide which of the thesis are more trustworthy.
Panneton0 said: I'd be interested to see how this specific attribute ends up being even more important than pace/acc. Expand BTW I'll tell you how I got to such a high value for stamina, and the other values in general, since I didn't really explain.
I start with the existing weights, changed a few weights until the players roughly aligned properly, then I carefully compared players who would remain stubbornly out of alignment (fixing one, ruins another).
Maeda was key to this process. He's near the top, but he only has greens in aggression, determination, teamwork, work rate, acceleration, natural fitness, pace, stamina.
I start with ruling out teamwork, cause I know from testing before that that's useless.
Long story short, moving everything up and down except stamina and work rate were a no go. Stamina ended up being an indispensable part of the puzzle. And it worked for other players too. So this is how I ended up at such a high figure for stamina.
And as I said, I tried to revisit and lower this later, because I wanted the weights to more closely match HarvestGreen's data, but couldn't find a way of doing it.
Panneton0 said: Do you force a fixed starting XI so no rotation is possible? That might explain the abnormaly high Stamina required to fit the season result. I'd be interested to see how this specific attribute ends up being even more important than pace/acc. I feel like it would have this importance for a club with a poor backup, but not as much if the backup is still decent. Anyway, interesting! Expand Good question
I anticipate this by having 4 of the same player as the position I'm testing. The rest of the team also has extras for each position.
So it's not that fatigue is leading to stamina being overpowered. I was scratching my head over stamina until I thought about it, realizing that stamina is actually compensating for the 2 key attributes of pace and acc, not just one, so it makes sense in that way that it's so strongly weighted.
I did try and get it to work with say 25 stamina. Couldn't get it working. Other attributes, I found you could use 14 or 50 for it and it'd work either way, just shifting the other weights around. I think composure was one such attribute.
I actually paid some close attention to the game time the 4 players were getting, because obviously I wanted them to get adequate games (for match fitness & reliable scoring) without being overworked. I also didn't want a situation where injury leads to being a player short. I've got the precise data, but generally speaking all of the two most played players each got ~28-35 Premier League games/season. That doesn't include cup games and whatnot, which totaled all combined to 41-50 games/season for the assistant's most picked player of the four.
I did not force XI selection, just let the assistant select who he thought was best each game.
OpticFawn said: the same weightings for each position? Expand Yes
I was hesitant to release this before testing all positions, but these combined team results gave me enough confidence to believe it should be the same or about the same for all positions.
I did do another DR and a DC
82% | Kim Min Jae (DC) - 3rd, 3rd, 6th, 6th, 3rd, 4th, 5th = 4.286 position
compare to:
83% | Giovanni Di Lorenzo (DR) - 3rd, 3rd, 2nd, 9th, 2nd, 5th, 5th = 4.143 position
82% | Daizen Maeda - 2nd, 3rd, 4th, 4th, 2nd, 3rd, 3rd = 3 position 81% | Kyogo Furuhashi - 4th, 2nd, 3rd, 5th, 3rd, 2nd, 2nd = 3 position 82% | Vinicius Junior - 5th, 4th, 1st, 3rd = 3.25 position 83% | Harry Kane - 5th, 2nd, 3rd, 3rd, 1st, 7th = 3.5 position 83% | Lautaro Martinez - 7th, 3rd, 1st, 5th, 2nd, 5th, 2nd, 5th = 3.75 position 81% | Victor Osimhen - 3rd, 3rd, 7th, 3rd, 3rd, 4th, 3rd, 4th = 3.833 position 81% | Viktor Gyokeres - 6th, 4th, 3rd, 4th, 5th, 5th, 2nd, 5th, 2nd = 4 position
Both DR and DC appear a bit ineffectual compared to ST, but it's not off by much.
I had two options: Release what I have based on the above results, or test each position (so at least 100 samples) which would probably take a week or two. I could also end up getting burn out by that point. So I decided to just release it now, since I've got some stuff to do these next few days anyway. Testing of other positions will continue to be done. If it turns out it doesn't work for other positions properly, it'll be adjusted.
The weights for GK in that thread are completely wrong. For instance, Aerial Reach is 1.8 while Reflexes is 20. In fact Aerial Reach is the most important attribute while reflexes is the least important of the big three, and less important than has always been believed. I didn't comment on this in that thread, because the OP does denote 'For goalkeepers, read the top two or three only.'
HarvestGreen's GK data is also wrong. The problem both these people are having is low sample size leading to invalid results.
Here are the ideal minimum weights I derived from brute force testing:
Of those, Aerial Reach is the least flexible in terms how low you can go and get away with it.
Traits do not seem to effect performance at all for any player.
I can't remember if height itself plays any role, but jumping reach in indeed important, so not just Aerial Reach, and jumping reach is semi-determined by height I think (for starting database players it is, and I reckon they probably coded it for newgens too).
One attribute that matters for GK that I think pretty much everybody would be unaware of, and isn't shown on that image, is technique. Technique actually matters quite a lot for GK. It's useless for outfield players, but important for GK.
- Designed to align with the objective results of real players within the English Premier League - GK not yet done, weights from Premier League 1.0 are used which are decent - Do not read too much into the specific values for each attribute, I used HarvestGreen's and my own data as a basis to start with, but it's largely just plugging in numbers until I get the output I'm looking for, which is alignment with the rankings. Individual attribute weights will be inaccurate or even superfluous, but it's what they sum up to that matters. - GS file is a bit less accurate than the FMST26 weights. Highly recommend FMST26 over GS if possible.
I could keep working on this for forever and a day, but I feel like it's good enough right now for a first version.
You can make your own adjustments, add in non-linear formulas, etc. to line up with the rankings better if you like, since the ranking data is really what's solid.
bf3metro said: and btw, may i ask if you still refer to your ratings, or did you changed/tweaked them?
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, Expand Yes, those are the most recent. It's simply my findings for the balance of attributes that achieves 5th in the Premier League at minimal cost/requirements.
But now I have a bunch of objective player rankings to work with, so I'm currently working a set of weights that lines up with this objective ranking list. And I'm close to done on the first go at this.
bf3metro said: what's better in your opinion? FMST26 or FMSS? Expand I haven't used either enough to form an opinion on it. I'll be using FMST26 simply because it supports FM24, but FMSuperScout doesn't.
For whatever reason it seems to me that people take FM Arena's testing rather than HarvestGreen's as a starting point, so I'll begin with that:
So we see here that stamina is moderately, not highly, important. Specifically it is 29.7% of either acceleration or pace.
Two important things to note are that points is used a measurement rather than league position, and that we are measuring from 8 > 20 stamina. It's not clear what the makeup of the team or opposition is, but at least it's giving us a fair idea of what to expect in any case.
We see here in HarvestGreen's latest result for stamina that is it 27.1% of acceleration or pace going from 1 > 18.
For 6 > 18 it is 14.1% of acceleration or pace. In other words, stamina is never critical, but becomes even less important beyond '6'. He also has 1 > 6 results showing this.
In his initial attribute test shown here, stamina 10 > 20 is 30.9% of acceleration, which in my view is the most important result in regards to application to the Premier League.
In keithb's GS weightings, stamina is weighted at 60 for DLR/WBLR/DM/MC, 20 for AMLR/ST, and 0 for DC.
What this no doubt reflects is the now outdated myth that different positions require different sets of attributes. This is not an article of faith for me; I myself used to believe in, and initially employed, weightings that varied per position. Partly this was because each position has different CA weightings for attributes, and so high stamina for low CA cost on fullbacks seemed like a boon. I suspect that the myth has been generally perpetuated throughout the years with the CA weightings as a primary impetus, and that keithb isn't even aware of this - he seems to just think that stamina is what's necessary to win, simple as that. My mind was changed by the test results.
What my test results found, and seemingly implicitly HarvestGreen's & FM Arena's too, is that pace/acc is just as critical on DC as it is on ST, many attributes such as 'tackling' or 'passing' don't matter at all for any position, and if you try to test for positional differences, there doesn't appear to be any, or at least many. There might be still be some differences - I'm still wondering if pace & acc are of equal importance across all positions for instance, but overall we're talking small differences, not major ones.
Through brute force testing, I found that stamina of 13 is the essential requirement for the Premier League, while pace/acc is 15:
However, you can get away with as low as ~13 pace/acc (think Harry Kane, or Lewandowski), so long as stamina is ~15 or higher. Conversely, a 20 pace/acc player has less need of stamina, and can get away with 12 and no doubt lower.
So if you put all that together, basically stamina should be weighted at ~33% of pace/acc, is what I found.
So you can think of it as either 33% or 86% of acc, perhaps somewhere inbetween. So ~50% roughly. This was a change from the ~15% I previously used, which was primarily based on HarvestGreen's 14.1% 10 > 20 finding.
With my latest weightings, which wipe the slate clean of assumptions and simply try to align weightings with actual real player rankings supported by test results as evidence, I found that only somewhere around ~90% weighting for stamina worked - or ~90-110% of acc. This is far more than even keithb's 60% weighting for sta on fullbacks.
But why is that necessary, and why does it work if so? It is necessary because someone such as Maeda or Furuhashi has very few green attributes, yet ranks above the likes of both all-rounders such as Lewandowski and fairly well rounded high pace/acc players such as Osimhen. If you analyze it carefully (you need to compare multiple players in conjunction to find out it can't be his high work rate, det, aggression, etc.), the only way to make the rankings align seems to be to boost stamina to such a high weight. Perhaps I've missed some other option, but this where I'm at. As to the explanation as to why it is so, it makes more sense once you realize that stamina is preserving both pace and acc, so its value is doubled, and it is preserving the two most valuable attributes.
No one that I'm aware of has previously come to these conclusions about stamina. Even the overlap between this and the old 'stamina for fullbacks' myth doesn't extend this far. And it puts a big dent I reckon in the general pervading view that pace/acc is everything, which was always sort of heard of, but never really solid fact until HarvestGreen's findings. The trouble with the 'pace/acc is everything' explanation is that it failed to account for players such as Kane and Lewandowski. It would be (and still is by some even on this forum!) explained away as compensated by high technical skill such as passing, etc. which is a red herring - these technical skills really are completely useless, and the differences lie in other areas such as stamina, work rate, anticipation, and a handful of select others. 2/3rds of attributes continue to have zero effect on final season position.
Let's start with GKs:
HarvestGreen did 2 seperate tests on GKs.
December 2024:
April 2026:
The first thing I'll draw your attention to is that the results seemingly contradict each other. In the 1st test, acceleration does little to nothing. In the 2nd, it is the third most important attribute, above aerial reach which got a tick in the 1st test. Vision got 2 ticks in the first test, but does nothing in the 2nd test. There are more examples like this.
In skawkclsrn's case the issue is lack of samples, but here the issue is the methodology:
- The 1st test is using a team with 10 in every attribute, and increasing a single GK attribute to 20, then measuring the goals conceded. The first two aspects underlined are potential problematic factors, for instance what if a GK needs better reflexes and agility because the outfield is deficient in speed - perhaps with a speedy team, a GK only needs aerial reach to handle potshots he can see coming from afar. That is just a minor critique to show even solid tests can have pitfalls. The real problem is measuring the goals conceded, because as shown in my testing results, goals conceded is not at all a consistent measure of success, similar to how league points is all over the place compared to final league position. It will give some correlation, hence why agility, reflexes, and aerial reach all correctly have ticks, but that is just because teams who finish 1st obviously concede less goals than teams that finish 20th.
- The 2nd test is starting with the GK at '20' in all attributes and setting 1 attribute to '1'. This is different to how HarvestGreen does his outfield tests, which increase/decrease from '10'/'12' for all attributes, and it's obviously less realistic to begin with. But the main issue, only evidenced by my own testing later, is that having all attributes at '20' is likely compensating for and obscuring certain deficiencies. So we see that reflexes and agility are pretty much the only 2 attributes that matter, and even then, their individual impact is fairly minimal (12.8% at most).
HarvestGreen also stated that his observation is that GK is 20% of effect of an outfield player, if I remember correctly, which is basically saying the GK should be an afterthought and not really worth worrying about.
All of his tests also carry the same caveat that he is testing against opposition that has identical attributes. For some attributes, such as Jumping Reach, Aerial Reach, Strength, etc. I hope it's obvious how this could constitute a problem when it comes to translating to how things work in real leagues.
Now, coming to my tests. I brute force tested individual attributes for GK until I got a solid picture of what an optimal GK looks like. So what I would do is I would start with all attributes at 1, except a few obviously necessary ones like agil, aer, ref, etc. and measure the position. The initial result might be 13th. Then I would increase each attribute from '1' to '20' and measure the improvement. If no improvement in position, ignore it going forward. After learning what attributes matter and which don't, I would begin refinement, seeing how low I could get an attribute to find the 'sweet spot'. And I also start testing those attributes I took for granted at the start: agil, aer, ref. I would test a few potential combos (i.e. does aer only matter if jump is high?), but obviously it can't be an exhaustive search. Now what I would most often find is something like this:
'10' = relegated
'12' = relegated
'13' = 8th
'14' = 5th
'15' = 4th
'16' = 4th
'18' = 3rd
'20' = 3rd
Usually I would choose 14 to settle on. But if '13' is relegated, or '18' is 1st, then obviously I would likely change that to a '15' - while also considering realistic availability in the game.
Now these are the essential GK attributes I ended up with:
We see from my latest comparative testing of real players within the game, that this player would constitute something of a middling Premier League team GK. This GK finishes ~7th, the best finishes 4th, Barcelona's finishes 6.4, and a League 1 GK finishes 8.4.
One key attribute that is hidden from that screenshot is technique, which turns out to be quite critical for GK. You can also see this reflected in the database data for GKs - the better the GK, the higher technique he is generally given. I actually notice for the first time now that HarvestGreen actually gave a tick next to technique in his 1st test, though in the 2nd it is listed as 0.0%.
It's not clear yet exactly how much a GK accounts for as a % of a team's overall performance, but we can see the GK is more critical to success than HarvestGreen gave the GK credit for. My current estimation is somewhere around ~66-100% of an outfield player.
So we know my template works. Let's compare to what we 'knew 2 years ago', which is HarvestGreen's data and nothing else:
- HarvestGreen found vision and pace, and later reflexes, to be the most important attributes. I found vision '1', pace '13', and reflexes '11' are adequate, while aerial reach is the most essential attribute.
- HarvestGreen summed up that GK is has 20% impact of outfield player. My evidence shows it's much more than that, even the difference between relegation and a top 5 finish at times.
- Generally speaking, there was no solid data on GK at all previously. Now I've provided you with a precise template for GK that is backed by solid evidence in the form of testing both real & artificial players in a real and popular league (English Premier League).
If I've missed anyone else's findings on GKs, that was any good, let me know.
Alisson - 6th, 3rd, 4th, 4th, 3rd = 4 position
Thibaut Courtois - 3rd, 7th, 2nd, 5th, 8th = 5 position
Jan Oblak - 5th, 8th, 6th, 4th, 3rd = 5.2 position
Marc-Andre ter Stegen - 10th, 11th, 4th, 4th, 3rd = 6.4 position
Anatolii Trubin - 15th (sacked), 6th, 4th (sacked), 5th = 7.5 position
Jack Stevens - 13th (sacked), 4th, 9th (sacked), 8th (sacked), 8th (sacked) = 8.4 position
Sinan Bolat - 4th, 2nd, 19th (sacked), 5th, 14th (sacked), 9th (sacked), 12th (sacked), 5th = 8.75 position
I removed Courtois' starting injury to test him.
It shows that GK does in fact matter, though it does seem a lot more variable - in the downwards direction.
So although a GK can't really make your team win much more, they can in fact make or break your team.
Observations through player comparison:
- Jack Stevens is a mediocre all rounder who normally plays for Cambridge, and show you can't really get away with playing mediocre GKs
- Bolat is interesting.. he is like Stevens, but a tier above, but has green reflexes and jumping reach. Shows good reflexes aren't sufficient.
- Trubin, like Bolat, also significantly underperforms. He has green Aer, Jump and Handling. None of these are sufficient alone therefore, even with seemingly above average values in all other areas.
We know that the following GK finishes ~5th and with good consistency too:
This GK finished 7th:
It seems like only a select few of real GKs can do better than the above players.
If I filter for attributes of that second GK (excluding natural fitness), no players come up.
It seems that GK is about what is the least worst deficiency do they have. I suspect it is this way so that, unlike the outfield, you don't get great GKs who make teams come 1st by the mere addition of themselves. Perhaps this also explains why GKs can't get really high match ratings, because their best is merely adequate.
Trubin has a slightly deficiency in determination, pace, acceleration. Alisson is only lacking 1 pace. Oblak slightly lacks first touch, acceleration, and agility.
To verify the theory, I reduced the filter by 1 for the attributes and tested the worst one of the 4 players that turned up (1 was Ederson @ Man City, 2 were Alisson and his backup GK @ Liverpool, and the worst was Davy Roef from AA Gent).
Davy Roef - 13th (sacked), 4th, 14th (sacked), 6th (sacked), 1st = 7.6 position
High variation, but the average result aligns with extra 1 in key attributes finishing ~7th
BTW it's stuff like Alisson's backup GK just coincidentally having exactly the right set of meta attributes that shows me SI are aware of and intentionally making most attributes useless and misleading. If it was an oversight, players that look like duds but nonetheless perform well and are placed in the top teams wouldn't be an identifiable pattern.
Now I know quite a few people are also interested in what kind of GK gives the most clean sheets, or lowest goals conceded. So here are those stats:
Alisson - 13 cln, 48 con | 14 cln, 39 con | 15 cln, 40 con | 14 cln, 36 con | 11 cln, 44 con = 13.4 cln, 41.4 con
Thibaut Courtois - 9 cln, 41 con | 12 cln, 48 con | 10 cln, 56 con | 10 cln, 45 con | 11 cln, 50 con = 10.4 cln, 48 con
Jan Oblak - 8 cln, 49 con | 11 cln, 43 con | 10 cln, 59 con | 14 cln, 34 con | 15 cln, 40 con = 11.6 cln, 45 con
Marc-Andre ter Stegen - 4 cln, 58 con | 10 cln, 53 con | 11 cln, 52 con | 13 cln, 44 con | 14 cln, 46 con = 10.4 cln, 50.6 con
Anatolii Trubin - 10 cln, 46 con
Davy Roef - 14 cln, 45 con | 13 cln, 44 con = 13.5 cln, 44.5 con
Jack Stevens - 16 cln, 41 con
Sinan Bolat - 14 cln, 50 con | 10 cln, 52 con | 9 cln, 53 con | 8 cln, 54 con = 10.25 cln, 52.25 con
I only took stats from samples where there was no interruption by sacking.
Also, given what you said about Strength, Vision, Finishing, Teamwork and Loyalty, would you say these are attributes we should actually pay attention to when evaluating a player, or are they basically not worth considering unless the value is particularly low/high?
I’m especially wondering about Teamwork since you still seem a bit uncertain about it.
And one last thing: have you also updated the goalkeeper weights, or are these still the current ones?
Reflexes: 12.8, Agility: 8.0, Acceleration: 4.7, Pressure: 4.1, Pace: 3.5, AerialReach: 3.4
PS: What is the correct way to write it?
Was referring to the FSMT26 weights. For FMSS I divided by 5 because I think it had problems if you put the numbers too large from memory.
Those 5 attributes are not really worth paying attention to.. except loyalty of course, for non-performance reasons. Not only are they low value, they are non-essential. By contrast, agility is also low value, but moderately essential around ~10. Work rate is absolutely essential to have at least 6. You can have 1 strength/finishing/vision and finish 5th, that's proven.
Overall I don't think teamwork does anything. There's just a small element of uncertainty.
GK weights unchanged. I'm currently doing samples of GKs for rankings list.
I think either way you've typed it is fine.. just test each and see
Kriek said: Is it still needed to use the filters with the new ratings on Genie Scout or only the ratings?
Only ratings is fine. Filters still useful, but should be able to phase this out later by adding non-linear weights to FMST26 (not GS though).
Was that intentional as part of the new weighting method?
Finishing, strength, and vision were technically in the previous weights. I dropped them from the file because the attributes that are adequate you are bound to get at the required levels most of the time anyway:
Strength - 8
Vision - 7
Finishing - 7
I played around a fair bit with strength in particular in these new weights. I thought maybe it's around 10-20, but turned not to be the case. Vision is 20 on Messi which was food for thought, but it didn't seem to affect ranking alignment for the better.
Actually teamwork is the one I most wonder about.. players like Maeda have high teamwork, and there's some mathematical study on FM24 on github that a guy did for university work that found teamwork was a key correlate of performance.. but I read through it, and overall I think its just full of mistaken findings. My own testing and HarvestGreen's found teamwork doesn't matter, so at the moment I don't see a valid reason to include it.
Loyalty I included as '1' at the last moment pretty much symbolically. It would have some very minor to minor effect via morale, so i felt justified giving it a little '1'. But obviously loyalty deserves some weight for gameplay reasons.
The main thing would be the non-linearity of attributes, which the testing did show, but can't be reflected in linear weightings.
HarvestGreen did do some theorizing on attribute interactions, and I've dug up quotes from the Collyer brothers and in-game tips and whatnot which describe attribute interactions as well. I found that those latter things turn out to be generally untrue, or at least outdated.
I reckon there are attribute interactions though, and HarvestGreen's ideas on it are interesting.. just lack the solid data on it at the moment though.
I don't really have solid data to back it, but I'm personally convinced that aggression x dirtiness is an interaction, it just seems logical and seemed to solve something insoluble with the ratings at one point too.
This is partly why I decided to release it as is now with mostly linear weights, because one could go down the rabbit role of trying out all these different attribute combos and either getting nowhere or being mislead into seeing something that isn't there, while also spending a lot of time doing so. It remains difficult to test attribute combinations, but I'm sure there's some method to bear it out properly.
bf3metro said: Also, I noticed there are some strange extra spaces between a few attributes in the list. Is that intentional, or just a formatting issue?
Probably a formatting issue
bf3metro said: One other thing I'm wondering: is it possible that some of your original FMSS weights were simply set too low at the beginning, which would also partly explain why a few attributes have increased so dramatically now?
Do you think these huge increases are entirely a consequence of the different methodology, or could your original FMSS weights also have been underestimating some of these attributes from the start?
The FMSS weights I gave before simply reflect the minimum set of attribute values to attain 5th in the Premier League. They represent the best 'bang-for-buck' relative ratio of attributes.
I guess the question that the objective ranking raises in relation to that is, if work rate supposedly caps out at 13, why is it so critical for Maeda, and important in general? And if dribbling isn't so essential, is it really necessary to include it high - even if it does actually have significant benefits. So it does shine a new light on certain things. Personally I strongly favor what is true in realistic testing (the player rankings derived from the team positions), rather than what the isolated or constrained testing shows (including my own).
The 118 number is just to get it to display with the highest % at ~90%. It's the same as the overall weight option in GS.
From what I understand, the old weights were based on finding the cheapest/minimum attribute balance capable of achieving around 5th in the Premier League, whereas the new weights are being fitted to a much larger set of objective player rankings.
So it makes sense that the result could be very different: instead of asking “what minimum combination of attributes gets results?”, you're now asking “which attributes best explain the actual ranking of players?”
Yes, that is precisely the correct summary of it, and I daresay a better explanation than I did.
I'm glad you immediately understand, because I think it's easy to misinterpret this latest thing I'm doing with the weights.
bf3metro said: The new model seems to put an enormous premium on Pace, Acceleration, Stamina, Work Rate and Anticipation, while attributes such as Dribbling, Consistency, Important Matches or Natural Fitness become much less influential.
And then you have Finishing at only 0.4, which is pretty wild too.
I started with the presumption that finishing is almost completely unnecessary, but ChatGPT independently came to the conclusion that finishing should be removed too when I fed it all the player's attributes and asked it to come up a set of weights to fit the rankings.
It was surprising how strongly weighted anticipation and work rate seems to be. Maeda is still down a bit, so work rate could in fact do with being a bit higher perhaps. It's strange to me, because I know that (and you can see HarvestGreen's data to verify this) that work rate almost caps out at 13. But that is when work rate has been tested in isolation or partial isolation. Perhaps there is something like 'determination x work rate x stamina' going on. I couldn't find a way of getting around weighting work rate highly.
Anticipation in my observations did continue to scale, but had diminishing returns. But putting that aside for now, it makes sense that it would be a key attribute because ostensibly it's the movement ('off the ball' as speed?) to the area before possessing the ball. So it sounds like it cuts down on the pace/acc requirement to me, because once they have the ball, they have less distance to travel. Concentration would be a similar kind of effect, where low concentration leads to a delay in getting into position to receive or stop a ball (the latter offset by 'positioning' perhaps).
Consistency, Important Matches, and Natural fitness has not been incorporated with much accuracy. They are kind of afterthoughts, as I know they will matter somewhat, but not sure to what degree. I've used HarvestGreen's data to set them, and so long as they're not interfering with the ranking, I generally leave them alone. Same with pressure, professionalism, etc. - and the left foot & right foot figures I've just pulled out of my ass, to give a little extra weight to the modest footedness bonus which we know exists. This stuff can be refined further later. I think HarvestGreen found that foot should also match the side they're on, and I think FMST26 allows us to do this as well.
Dribbling I've been in two minds about. Most of the time I had it set pretty high at ~40, sometimes as high as 60. I ended up reducing it to 15. ChatGPT actually said early on to do this too. Both were fairly equally functional. From testing, we know dribbling is a very strong attribute that scales well.. I suspect it's not needed much to match the rankings, because hardly any players have high dribbling anyway. It's the hardest attribute to get high in the game I believe.
bf3metro said: PS: Quick question: why are attributes like WorkRate, ImportantMatches, and NaturalFitness written without spaces? Is that just the naming format, and do they need to be written exactly like that in app.js as well? Also, should I add a comma after the final value, Consistency: 2.82, or should the last entry be left without one?
Yes, that is how they have to be written for FMSuperScout, otherwise the program won't work. That is how labels the attributes internally.
I would add the comma.
Actually this is proving more difficult than I thought it would be
I'm not a programmer, so I don't know how to implement the injury proneness & dirtiness weights. I thought, maybe I'll just add them as simple negatives, like for the GS weights, and adjust it until it matches the rankings, but then I realized it doesn't do FM24 db, only FM26.
Here's the weights at least that will work:
Pace: 17.36, Acceleration: 17.24, JumpingReach: 9.24, Dribbling: 2.92, Pressure: 3.34, Balance: 2.7,
Concentration: 9.46, Anticipation: 11.64, Determination: 6, Agility: 3.4, Stamina: 18.78,
Strength: 0.2, Composure: 5.12, WorkRate: 12.6, Finishing: 0.4,
Aggression: 1.26, Professionalism: 3, Ambition: 0.4, Loyalty: 0.2, Vision: 0.1, ImportantMatches: 2.04, NaturalFitness: 1.58, Consistency: 2.82
Replace the weights in the app.js file with those (search for 'FM-Arena' ).
For adding injury proneness & dirtiness, which are in fact crucial (but I guess you could also just check players manually to have low inj and dirt values), we're going to need someone like Panneton0 or perhaps the creator of FMSuperScout itself to help out. Could probably do it myself, but can't be bothered doing an hour of research honestly.
Yeah, I left it out because I have to work out how to best translate it from the FMST26 weights first. I'll do that now.
Any insights about how newgen generation works under the hood?
Not stuff we already know generally about what effects newgens, but is your detection method say revealing anything that's going on?
This new file is a lot like mine LOL!
You have stamina weighted at 0 for DC, 20 for ST/TS/AMC/AML/AMR, and 60 elsewhere. It's not my fault your own weights contradict your own words.
Meanwhile, the key attribute of dirtiness you leave on 0, as you have 0 clue of course about what attributes actually matter beyond what we knew from HarvestGreen's testing a year or two ago.
But as I've said, you can have a variety of combinations that work to get to match the final ranking result. And at least you're implicitly accepting now that my objective rankings are correct.
Let's do a comparison of our two files to find out just how similar they really are. First, yours:
Junior is 1st for FS, even with 16 ST proficiency. Mbappe is above Haaland. Messi is 5% above Lewandowski and 10% above Maeda. Even Malen is above Maeda. Dybala is above Maeda and Furuhashi. Mbappe (8 jump, 8 head, 11 str) is a better target man than Glatzel (16 jump/head/str). It goes on.
Mine:
There are some minor issues, such as that Maeda should be ~3% higher, and that Malen & Glatzel should have a wider percentage gap between them.
keithb said: Why have you still used negative values and scored the hidden attributes in Genie Scout?
The only fair point you've raised in your entire posting history I believe
It is true that hiddens remain invalid for GS. I decided in the end to include them for my final GS adjustment at the end to try and closely match what I got in FMST26, halved for everything except dirtiness & injury proneness & natural fitness. Dirtiness & injury proneness are essential to the weightings, there's no way to do without them.
Because GS calculates incorrectly, the ratings remain a bit off compared to what you'll get in FMST26, hence I highly recommend FMST26, but I know many people aren't going to be willing to switch over.
I think you've got the picture wrong.
As I referred to in my post, the OP of that thread said 'For goalkeepers, read the top two or three only.'
I didn't do the full quote, which follows with:
'Reflexes and Agility separate cleanly; below that it is noise, and Handling ranking under Corners is not a finding.
One keeper per match against ten outfielders means that column has about a tenth of the statistical power.'
I'm not saying his other findings are 'completely wrong' - only the GK weights.
I'm using my own data to refute the data he got on GKs, that's the sound basis for me saying 'it is all wrong'. And it is up to me to decide which of the thesis are more trustworthy.
BTW I'll tell you how I got to such a high value for stamina, and the other values in general, since I didn't really explain.
I start with the existing weights, changed a few weights until the players roughly aligned properly, then I carefully compared players who would remain stubbornly out of alignment (fixing one, ruins another).
Maeda was key to this process. He's near the top, but he only has greens in aggression, determination, teamwork, work rate, acceleration, natural fitness, pace, stamina.
I start with ruling out teamwork, cause I know from testing before that that's useless.
Long story short, moving everything up and down except stamina and work rate were a no go. Stamina ended up being an indispensable part of the puzzle. And it worked for other players too. So this is how I ended up at such a high figure for stamina.
And as I said, I tried to revisit and lower this later, because I wanted the weights to more closely match HarvestGreen's data, but couldn't find a way of doing it.
Good question
I anticipate this by having 4 of the same player as the position I'm testing. The rest of the team also has extras for each position.
So it's not that fatigue is leading to stamina being overpowered. I was scratching my head over stamina until I thought about it, realizing that stamina is actually compensating for the 2 key attributes of pace and acc, not just one, so it makes sense in that way that it's so strongly weighted.
I did try and get it to work with say 25 stamina. Couldn't get it working. Other attributes, I found you could use 14 or 50 for it and it'd work either way, just shifting the other weights around. I think composure was one such attribute.
I actually paid some close attention to the game time the 4 players were getting, because obviously I wanted them to get adequate games (for match fitness & reliable scoring) without being overworked. I also didn't want a situation where injury leads to being a player short. I've got the precise data, but generally speaking all of the two most played players each got ~28-35 Premier League games/season. That doesn't include cup games and whatnot, which totaled all combined to 41-50 games/season for the assistant's most picked player of the four.
I did not force XI selection, just let the assistant select who he thought was best each game.
Yes
I was hesitant to release this before testing all positions, but these combined team results gave me enough confidence to believe it should be the same or about the same for all positions.
I did do another DR and a DC
82% | Kim Min Jae (DC) - 3rd, 3rd, 6th, 6th, 3rd, 4th, 5th = 4.286 position
compare to:
83% | Giovanni Di Lorenzo (DR) - 3rd, 3rd, 2nd, 9th, 2nd, 5th, 5th = 4.143 position
82% | Daizen Maeda - 2nd, 3rd, 4th, 4th, 2nd, 3rd, 3rd = 3 position
81% | Kyogo Furuhashi - 4th, 2nd, 3rd, 5th, 3rd, 2nd, 2nd = 3 position
82% | Vinicius Junior - 5th, 4th, 1st, 3rd = 3.25 position
83% | Harry Kane - 5th, 2nd, 3rd, 3rd, 1st, 7th = 3.5 position
83% | Lautaro Martinez - 7th, 3rd, 1st, 5th, 2nd, 5th, 2nd, 5th = 3.75 position
81% | Victor Osimhen - 3rd, 3rd, 7th, 3rd, 3rd, 4th, 3rd, 4th = 3.833 position
81% | Viktor Gyokeres - 6th, 4th, 3rd, 4th, 5th, 5th, 2nd, 5th, 2nd = 4 position
Both DR and DC appear a bit ineffectual compared to ST, but it's not off by much.
I had two options: Release what I have based on the above results, or test each position (so at least 100 samples) which would probably take a week or two. I could also end up getting burn out by that point. So I decided to just release it now, since I've got some stuff to do these next few days anyway. Testing of other positions will continue to be done. If it turns out it doesn't work for other positions properly, it'll be adjusted.
HarvestGreen's GK data is also wrong. The problem both these people are having is low sample size leading to invalid results.
Here are the ideal minimum weights I derived from brute force testing:
Of those, Aerial Reach is the least flexible in terms how low you can go and get away with it.
Traits do not seem to effect performance at all for any player.
I can't remember if height itself plays any role, but jumping reach in indeed important, so not just Aerial Reach, and jumping reach is semi-determined by height I think (for starting database players it is, and I reckon they probably coded it for newgens too).
One attribute that matters for GK that I think pretty much everybody would be unaware of, and isn't shown on that image, is technique. Technique actually matters quite a lot for GK. It's useless for outfield players, but important for GK.
Use FMST26 (works for FM24 & FM26) and copy paste this into statistics > custom metrics (advanced):
(acceleration * 86.8 + pace * 86.2 + jumping_reach * 46.2 + pressure * 16.7 + dribbling * 14.6 + work_rate * 63.0 + agility * 17.0 + anticipation * 58.2 + composure * 25.6 + stamina * 93.9 + consistency * 14.1 + determination * 30.0 + balance * 13.5 + strength * 1.0 + concentration * 47.3 + finishing * 2.0 + important_matches * 10.2 + natural_fitness * 7.9 + professionalism * 15.0 + ambition * 2.0 + loyalty * 1.0 + aggression * 6.3 + vision * 0.5 + left_foot * 6 + right_foot * 5 - (injury_proneness * (50 / (natural_fitness * 0.85))) - (dirtiness * 32 * (aggression * 0.1))) / 118
Genie Scout file:
https://files.catbox.moe/z7hsqg.grf
Notes:
- Designed to align with the objective results of real players within the English Premier League
- GK not yet done, weights from Premier League 1.0 are used which are decent
- Do not read too much into the specific values for each attribute, I used HarvestGreen's and my own data as a basis to start with, but it's largely just plugging in numbers until I get the output I'm looking for, which is alignment with the rankings. Individual attribute weights will be inaccurate or even superfluous, but it's what they sum up to that matters.
- GS file is a bit less accurate than the FMST26 weights. Highly recommend FMST26 over GS if possible.
I could keep working on this for forever and a day, but I feel like it's good enough right now for a first version.
You can make your own adjustments, add in non-linear formulas, etc. to line up with the rankings better if you like, since the ranking data is really what's solid.
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,
Yes, those are the most recent. It's simply my findings for the balance of attributes that achieves 5th in the Premier League at minimal cost/requirements.
But now I have a bunch of objective player rankings to work with, so I'm currently working a set of weights that lines up with this objective ranking list. And I'm close to done on the first go at this.
I haven't used either enough to form an opinion on it. I'll be using FMST26 simply because it supports FM24, but FMSuperScout doesn't.