A4 said: I only heard that traits don’t really matter much in FM, but I’ve always noticed how good players with “tries tricks” are. I even started teaching it to everyone in my youth academy. Of course, it’s anecdotal evidence, but when youngsters learn it—or even just try to do it—their impact and match ratings seem to be so much higher.
I’ve also noticed the same thing with the Light-Hearted personality. Somehow, good players with that personality seem to perform so much better for me than players with other personalities.
Is this something anyone has ever tested before? Expand
PLus, "tries tricks" leads to some weird random moves on the field. I don't know if it's efficient, but it's entertaining I always try to have 1-2 wingers with it just for giggles.
The "edit weighting" is not super instinctive. UI/UX is not my forte.
But the idea is to reproduce the FMArena testing.
You can chose a "FROM - TO" attribute growth, and how many "points" would the team make if all players went from attribute FROM to attribute TO (e.g., going from 8 to 20 speed provides 64 pts for the team). That leads to the player having a direct contribution of +6.4. It considers linear impact.
BUT. You can change the linearity by adding other ranges. For instance, you could say that 1-8 has no impact, but you start "gaining" points from 8 onward. That way, you simply enter FROM 1 TO 8 With "0 pts". That will actually lead to players having 0 penalty for being below 8.
I'd actually be glad to find better ways to show this.
Unlike Genie Scout, the formula is fully known. Unlike the original FMSS, the formula can be made non-linear. Unlike FMST, the formula is not fully customizable. However, this is open source, so you CAN modify the formula in app.js if wanted.
To swap the formula entirely, see pointsContribution() in app/app.js. The weights used in the current formula come from the active preset JSON in app/meta-presets/. Presets you can change in the settings menu.
It's not 100% userfriendly, I know. But try it out and I'm open to other ideas
Purity said: That's truly amazing; changing the plugin to fetch position proficiencies at all positions is something I didn't know how to implement. I'm really looking forward to this new version. Expand
It's not yet super clean, I'm not a good developper -- heck, not even a dev at all --, just someone with ideas and time on his hands
Feel free to clone it for yourselves (it's not a packaged release like the OG) and test it out!
66connor66 said: Thanks for your work too! Looks like everyone is adding to it. Did you come up with a way of filtering players who are interested. Top tier clubs I found this not to be an issue but any lower tier clubs hard to find interested players? Expand
I did not work on that aspect much, sorry! Simply because my own playstyle these days is to do the Youth Challenge, where I can ONLY use academy-produced players in my team. That's why I really work on "what's the best XI", and not much on the mercato itself.
And for anyone who's concerned: I finished the youth challenge recently without "breaking" the engine like we are doing here. I'm just currently trying to see how many seasons I could have shaved off by min/maxing everything
I included @Purity features. Amazing work. I translated them in the UI to fit the selected language.
I changed the way meta are shown. Instead of an "average" of meta attributes, I reused FMArena's attribute testing from @Zippohttps://fm-arena.com/thread/14009-attribute-testing-football-manager-24/page-1/. So the score now shows how many "points" the player should directly contribute to over a season, as compared to a player with 8's all over the board.
The "meta score" column shows the base meta, but you can select a specific position so that the meta column shows the "effective meta" of your players at said position.
I changed the plugin to fetch position proficiencies at all positions. You can select which position you want to show the "effective meta" for. All players have base meta, but adjusted for positions they are played in (based on the same FMArena testbench.
I added a "edit meta" menu. Meta is now saved in a json instead of lines in the middle of the app.js. It's not as editable as the new tool https://www.fmscout.com/a-fmst-26.html. But I feel FMSS has better UI/UX than FMST. Anyways...
In the "Starting XI" tab, you can "ignore" players so it recomputes automatically (if you want to simulate injuries/suspension, and check what's better). Any player can play anywhere, but position proficiency hits hard so it's rare that it'll suggest playing a lad out of position.
Filtering by position in player view, you can chose what is the "position proficieny threshold" to consider a player for the position. Default - 15
Custom tactics is saved in between sessions, so you don't have to redo your formation when relaunching FMSS.
I don't want to mess the original repo, and neither want credit for the overhaul itself. But if @mavali, you are interested in the overhaul, just hit me up. It's been refactored a bit so a simple PR might be unsuitable. As a pet project, I don't expect you're putting much time in it, but if you do, I'll be glad to help
Being fixated on position proficiency's impact, I'd be interested to know if we ever tried the impact of dropping player's proficiencies below 15. I feel like the 15 -> 20 position proficiency has little impact, but that it would drop significantly below 15. But it's just a feeling.
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!
Just FYI, I checked the FM Scouting Tool26 and I realize I was doing the exact thing by modifying the code within FMSuperScout (being open-source paves the way to fully customizable score).
For instance, I have the following "base weight" for, specifically DC (the comments are w/r to basic weighting from FMArena testing.
InjuryProneness and Dirtiness have weight, but they are flagged as "adverse", so 20==1 and 1==20.
Then, I applied a transform on a couple of attributes that I saw being flagged as "non-linear" in theses forums:
WorkRate and Pressure, if below 6, are treated as half their value (so 4 is weighted as if it was a 2) Pace and acceleration, if above 15, have every point count as 1.5 (so 20 counts as if it was litterally a 22.5!!)
This is a first draft, but these non-linearity have weight considering the meta weightings. Meta score is simply the weighted average of all that considered.
Then, above that, I assign players an "effective meta" per position, according to its position proficiency (based again on some testing I've seen). A player untrained (1 proficiency at position X) has 0.5*meta. So even a player with perfect 20 in every meta attributes will be equivalent to a player with 10 everywhere in a non-proficient position.
And that multiplification factor is linear between 0.5 and 1.0 between 1 and 20 position proficiency.
This is the part I'm still working on to reproduce testings we've seen.
I wanted to show you this in case it gives you a "starting" point on how to implement custom scores in the new tool you foud.
CBP87 said: Thanks for the advice, managed to install it, but can't get it working. Followed the steps in the FAQs by adding the .txt file but still no luck. In fact, I rebooted FM and it wouldn't load until I deleted the .txt file Expand
How long did you wait when rebooting FM26? For me, it took almost 10 minutes before it loaded for the first time after the installation. I just when out for a coffee instead of abandonning and it paid off
However, I'm no developper and @mavali can clearly support you way better than I do if the bug persists. On my end it worked like a charm :|
One question: i worked this afternoon on supress some useless attributes on GS.
What do you think about suppress all negative attributes form the table in the first post ? Why keep them if they're negative ? Expand
If you look at the actual repo https://github.com/mavarobli/FMSuperScout, you can see the amazing upgrades from Purity in the pull requests. I also added one to take into account negative attributes (so you can weight them similarly). As Purity said, the open-source nature makes it easy to tryout non-linearity, filters, etc. directly into meta calculation.
I suggest trying it out! I love where this project could be the next tool for this community, and thank you lads for the no-bullying-no-arrogance conversation. It is refreshing <3
Also, let's give Mavali credits where credits is due for sharing his/hers open framework. I sure did spent a couple of bucks as a tiny encouragement.
Great info, that clarifies the test. I'm usually judging attributes without considering the "CA cost". While weird, this is mainly because, when trying to find out what player would be the most efficient in your squad, CA is of no interest.
It is very useful when trying to "buy players", where a badly distributed CA inflates its price. Or for training purposes where the CA-PA gap dictates the progression. But on a matchday, CA is of no importance, only the player effectiveness, which is related to meta attributes, not CA.
So that's why I misunderstood your results. It all makes sense now. Thanks again.
Also, positionning having such a bad influence on results points toward a problem with the ME. It might try to "position" players in a way it thinks helps, but it makes them play worst. That way, players who are out-of-position are often in an actual better spot than their "better" counterparts. Interesting result to be further investigated.
Does your simulation engine has any way of randomizing positional proficiency? (like having your ST being somewhere between ineffective and natural ST)
We have an early view of how it has an impact, but your simulation engine seems very efficient so we might be able to properly (finally!) isolate that.
Purity said: First of all, amazing work! Thank you. It is by far the best tool I've seen for FM in years. I was vibe-coding a similar tool using just exports, but it was painful. I tried implementing a few of my own ideas into your code. I'm not great at this and it probably broke a few things, but hopefully it gives you some ideas for future updates!
I've linked the modified files below (the link expires in 3 days, so don't hesitate to ask if you need me to re-upload them). I'm sorry the text in the app is in French, but the features should be fairly self-explanatory.
Here is a quick breakdown of what I added:
-GK Meta Score: Added a meta score for GKs based on harvestgreen22's work (I believe it was up to date).
-Position-based Meta Score: Added position-based scoring using very low-thought attribute weightings. It’s not a huge change, you could easily revert to FMArena weighting, I just felt this direction made sense for the future.
-PA-Meta Score: Added a Potential meta score named "PA-Meta" based on your potential attributes preview. It includes its own filter, column, and profile display.
-"Best XI" Tab: Calculates the best possible lineup for a given formation using your squad. You can either choose from presets or manually set the positions yourself. Clicking "⚡ Trouver la meilleure compo" automatically picks the preset formation that yields the highest overall meta score for your players.
-"Mercato" Feature: Located inside the Best XI tab, this button shows potential squad upgrades based on your chosen formation. It includes lightweight filters for interest, as well as a "Value for Money" filter (Meta Score divided by price) to highlight bargains. It offers up to 3 upgrade choices per position; you can dismiss players with a cross, and the next available upgrade will take their place.
-"Clubs & Divisions" Tab: A quick early concept that ranks all in-game divisions by average meta score. Clicking a division displays its clubs, ranked by the average meta score of their top 20 players. It also shows average PA meta, top player, and total squad value. Search filters are available for both division and club names.
These two new tabs are still in early stages, but I think they have a ton of potential.
Known Issues: Because I tweaked this mainly for my own playstyle, a few things are broken: -The "New Data" button doesn't work (you have to press F9 to load data). -Historical graphs currently don't render. -I modified how loaddumps are read because it was mixing data across different saves on my end. -And surely more
I'm just sharing these files in case you want to test out the features. it's definitely not a finished project and was never meant to be! I felt a bit guilty rewriting on top of your codebase since it started as a personal tweak, but I figured I'd share the ideas visually. They are surely better in yours and other hands. Everyone else is free to modify it again or give suggestions on top of it. Hope it helps!
Amazing rework mate! I was fiddling a bit with the same kind of target. Only thing I added was some weighting on hidden attributes. I was about to fiddle even more by weighting "bad hidden attributes", but using their scores as 21-attribute (so 20 injury proneness is like having a 1 and 1 is like having a 20 - thus keeping their weighting easily comparable to "good" attributes).
Big kudos to the original, and great job with those add-ons! I'll be sure to buy a Koffee for ya @mavali . And "bon travail" to you @Purity . All of the new features are an absolutely great idea to be added. I upvote them!
Also, I'm raising my hand if you want beta testers for some features or even accept contributors. This project is one of the best companion app I've found for us FM niche nerds
Also, if you ever make it to introduce position proficiency to weight the meta rating even more, that could lead to even better squad management using your tool! Again, great work!
OK, thanks for the info on the weighting choices in your GS file! That's enlightening and actually makes me understand better why seemingly best players are rated lower. And thanks for the infos on position proficiency.
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?
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?
Some visual (with another player) to complement my point. This guy is proficient as a DC, and can play somewhat as DR, DM and, to a lesser extent, WBR
Hi general rating (purely calculated through the attributes weighting) is similar everywhere (the weights are similar everywhere, except DC and ST where jumping reach has higher value in general)
Pretty much 41 across the board, and 42/43 DC/ST (the dude is huge)
Now, if we look at the actual position rating (the ones that appear if you set position ratings in your columns - it never shows the general rating), we see that the difference between his positional score as DC and as AMR is less than 10 points appart, which feels off. He should be very very low AMR, having 1 proficiency at that position.
Final thing, I never use the actual "role" rating since GS seem to add a layer of its own calculations on top of the user-defined weights. So I don't know how those relate to truly tested attributes.
Another thing about player position proficiency and how it should affect Genie Scout's ratings.
My understanding is that, according to the rating filter, each player gets a score for each position. This is the "general rating", when looking at one player's profil in GS. Then, the general rating is adjusted as a "positional rating" according to the player's position proficiency.
When chosing which player to play at a given position, "positional rating" is thus more relevant since it takes into consideration the position's proficiency. However, this can't seem to be configurable and only a GS inner calculation. We've seen somewhere that 1 point of proficiency has the similar impact on a player's performance than 1 point of pace "lost". E.g. A player with 17 speed and natural (20) is similar in performance than a player with 20 speed and accomplished (17). It's probably more complex than that, but it is the simplest way to compare.
Now, I'm not sure that this translates well into GS "positinal rating". For instance, let's look at 2 players in my team, contenders for playing WBL (for the sake of the discussion). I'm using the GS file in the OG post (zhf2yl)
Player A: General Rating = 45.0 WBL proficiency = 10 Positional Rating = 42.91 (So being only 10 proficient made him drop 2.09 pts) He is 45.0 positional rating for DR
Player B: General Rating = 42.6 WBL proficiency = 15 Positional Rating = 41.74 (So having 5 less than 20 proficiency made him drop 0.86 pts) He is 42.6 positional rating for DL
I feel like, even if GS shows player A as a better WBL, player B might be a better option. It seems to me that GS does not weight positional proficiency enough. My personal impression is that we should remove another 0.5 pt per proficiency below 20 to actually represent the player's efficiency.
That would make the "adjusted positional rating" like so: Player A: 37.91 Player B: 40.24 (He's now the best WBL between the two)
For reference, I have a player C with 1 in WBL proficiency: Player C: General Rating = 53.3 WBL proficiency = 1 Positional Rating = 42.7 (Just 10.6 pts less, even being totally ineffectual) Making him "theoretically" (without the adujsted positional rating) the best WBL even with 1 proficiency.
I'd like thoughts of smarter people than me on this.
I’ve also noticed the same thing with the Light-Hearted personality. Somehow, good players with that personality seem to perform so much better for me than players with other personalities.
Is this something anyone has ever tested before?
PLus, "tries tricks" leads to some weird random moves on the field. I don't know if it's efficient, but it's entertaining
But the idea is to reproduce the FMArena testing.
You can chose a "FROM - TO" attribute growth, and how many "points" would the team make if all players went from attribute FROM to attribute TO (e.g., going from 8 to 20 speed provides 64 pts for the team). That leads to the player having a direct contribution of +6.4. It considers linear impact.
BUT. You can change the linearity by adding other ranges. For instance, you could say that 1-8 has no impact, but you start "gaining" points from 8 onward. That way, you simply enter FROM 1 TO 8 With "0 pts". That will actually lead to players having 0 penalty for being below 8.
I'd actually be glad to find better ways to show this.
Unlike Genie Scout, the formula is fully known.
Unlike the original FMSS, the formula can be made non-linear.
Unlike FMST, the formula is not fully customizable. However, this is open source, so you CAN modify the formula in app.js if wanted.
To swap the formula entirely, see pointsContribution() in app/app.js. The weights used in the current formula come from the active preset JSON in app/meta-presets/. Presets you can change in the settings menu.
It's not 100% userfriendly, I know. But try it out and I'm open to other ideas
It's not yet super clean, I'm not a good developper -- heck, not even a dev at all --, just someone with ideas and time on his hands
I've made a draft PR in the OG repo here:
https://github.com/mavarobli/FMSuperScout/pull/29
Feel free to clone it for yourselves (it's not a packaged release like the OG) and test it out!
66connor66 said: Thanks for your work too! Looks like everyone is adding to it. Did you come up with a way of filtering players who are interested. Top tier clubs I found this not to be an issue but any lower tier clubs hard to find interested players?
I did not work on that aspect much, sorry! Simply because my own playstyle these days is to do the Youth Challenge, where I can ONLY use academy-produced players in my team. That's why I really work on "what's the best XI", and not much on the mercato itself.
And for anyone who's concerned: I finished the youth challenge recently without "breaking" the engine like we are doing here. I'm just currently trying to see how many seasons I could have shaved off by min/maxing everything
I included @Purity features. Amazing work. I translated them in the UI to fit the selected language.
I changed the way meta are shown. Instead of an "average" of meta attributes, I reused FMArena's attribute testing from @Zippo https://fm-arena.com/thread/14009-attribute-testing-football-manager-24/page-1/. So the score now shows how many "points" the player should directly contribute to over a season, as compared to a player with 8's all over the board.
The "meta score" column shows the base meta, but you can select a specific position so that the meta column shows the "effective meta" of your players at said position.
I changed the plugin to fetch position proficiencies at all positions. You can select which position you want to show the "effective meta" for. All players have base meta, but adjusted for positions they are played in (based on the same FMArena testbench.
I added a "edit meta" menu. Meta is now saved in a json instead of lines in the middle of the app.js. It's not as editable as the new tool https://www.fmscout.com/a-fmst-26.html. But I feel FMSS has better UI/UX than FMST. Anyways...
In the "Starting XI" tab, you can "ignore" players so it recomputes automatically (if you want to simulate injuries/suspension, and check what's better). Any player can play anywhere, but position proficiency hits hard so it's rare that it'll suggest playing a lad out of position.
Filtering by position in player view, you can chose what is the "position proficieny threshold" to consider a player for the position. Default - 15
Custom tactics is saved in between sessions, so you don't have to redo your formation when relaunching FMSS.
I don't want to mess the original repo, and neither want credit for the overhaul itself. But if @mavali, you are interested in the overhaul, just hit me up. It's been refactored a bit so a simple PR might be unsuitable. As a pet project, I don't expect you're putting much time in it, but if you do, I'll be glad to help
Has this test ever checked that? @Zippo
For instance, I have the following "base weight" for, specifically DC (the comments are w/r to basic weighting from FMArena testing.
// DC — JumpingReach rises to tier-1 (closer to Pace/Acc). Finishing removed.
const META_DC_W = {
Pace: 20.5, Acceleration: 20.4, JumpingReach: 18.0,
WorkRate: 6.5, Anticipation: 6.5, Concentration: 5.5, Balance: 4.0,
Strength: 3.5, Determination: 3.0, Stamina: 2.5, Agility: 2.0, Aggression: 1.5,
Pressure: 5.0, Consistency: 2.0, ImportantMatches: 2.0,
InjuryProneness: 1.5, Dirtiness: 1.5,
};
InjuryProneness and Dirtiness have weight, but they are flagged as "adverse", so 20==1 and 1==20.
Then, I applied a transform on a couple of attributes that I saw being flagged as "non-linear" in theses forums:
WorkRate and Pressure, if below 6, are treated as half their value (so 4 is weighted as if it was a 2)
Pace and acceleration, if above 15, have every point count as 1.5 (so 20 counts as if it was litterally a 22.5!!)
This is a first draft, but these non-linearity have weight considering the meta weightings. Meta score is simply the weighted average of all that considered.
Then, above that, I assign players an "effective meta" per position, according to its position proficiency (based again on some testing I've seen). A player untrained (1 proficiency at position X) has 0.5*meta. So even a player with perfect 20 in every meta attributes will be equivalent to a player with 10 everywhere in a non-proficient position.
And that multiplification factor is linear between 0.5 and 1.0 between 1 and 20 position proficiency.
This is the part I'm still working on to reproduce testings we've seen.
I wanted to show you this in case it gives you a "starting" point on how to implement custom scores in the new tool you foud.
How long did you wait when rebooting FM26? For me, it took almost 10 minutes before it loaded for the first time after the installation. I just when out for a coffee instead of abandonning and it paid off
However, I'm no developper and @mavali can clearly support you way better than I do if the bug persists. On my end it worked like a charm :|
One question: i worked this afternoon on supress some useless attributes on GS.
What do you think about suppress all negative attributes form the table in the first post ? Why keep them if they're negative ?
If you look at the actual repo https://github.com/mavarobli/FMSuperScout, you can see the amazing upgrades from Purity in the pull requests. I also added one to take into account negative attributes (so you can weight them similarly). As Purity said, the open-source nature makes it easy to tryout non-linearity, filters, etc. directly into meta calculation.
I suggest trying it out! I love where this project could be the next tool for this community, and thank you lads for the no-bullying-no-arrogance conversation. It is refreshing <3
Also, let's give Mavali credits where credits is due for sharing his/hers open framework. I sure did spent a couple of bucks as a tiny encouragement.
I bypassed windows security and inspected the raw code. It seems safe. It just doesn't have any certificate. Risk is very minimal.
It is very useful when trying to "buy players", where a badly distributed CA inflates its price. Or for training purposes where the CA-PA gap dictates the progression. But on a matchday, CA is of no importance, only the player effectiveness, which is related to meta attributes, not CA.
So that's why I misunderstood your results. It all makes sense now. Thanks again.
We have an early view of how it has an impact, but your simulation engine seems very efficient so we might be able to properly (finally!) isolate that.
Amazing work buddy.
I've linked the modified files below (the link expires in 3 days, so don't hesitate to ask if you need me to re-upload them). I'm sorry the text in the app is in French, but the features should be fairly self-explanatory.
Here is a quick breakdown of what I added:
-GK Meta Score: Added a meta score for GKs based on harvestgreen22's work (I believe it was up to date).
-Position-based Meta Score: Added position-based scoring using very low-thought attribute weightings. It’s not a huge change, you could easily revert to FMArena weighting, I just felt this direction made sense for the future.
-PA-Meta Score: Added a Potential meta score named "PA-Meta" based on your potential attributes preview. It includes its own filter, column, and profile display.
-"Best XI" Tab: Calculates the best possible lineup for a given formation using your squad. You can either choose from presets or manually set the positions yourself. Clicking "⚡ Trouver la meilleure compo" automatically picks the preset formation that yields the highest overall meta score for your players.
-"Mercato" Feature: Located inside the Best XI tab, this button shows potential squad upgrades based on your chosen formation. It includes lightweight filters for interest, as well as a "Value for Money" filter (Meta Score divided by price) to highlight bargains. It offers up to 3 upgrade choices per position; you can dismiss players with a cross, and the next available upgrade will take their place.
-"Clubs & Divisions" Tab: A quick early concept that ranks all in-game divisions by average meta score. Clicking a division displays its clubs, ranked by the average meta score of their top 20 players. It also shows average PA meta, top player, and total squad value. Search filters are available for both division and club names.
These two new tabs are still in early stages, but I think they have a ton of potential.
Known Issues:
Because I tweaked this mainly for my own playstyle, a few things are broken:
-The "New Data" button doesn't work (you have to press F9 to load data).
-Historical graphs currently don't render.
-I modified how loaddumps are read because it was mixing data across different saves on my end.
-And surely more
I'm just sharing these files in case you want to test out the features. it's definitely not a finished project and was never meant to be! I felt a bit guilty rewriting on top of your codebase since it started as a personal tweak, but I figured I'd share the ideas visually. They are surely better in yours and other hands. Everyone else is free to modify it again or give suggestions on top of it. Hope it helps!
Files download
Amazing rework mate! I was fiddling a bit with the same kind of target. Only thing I added was some weighting on hidden attributes. I was about to fiddle even more by weighting "bad hidden attributes", but using their scores as 21-attribute (so 20 injury proneness is like having a 1 and 1 is like having a 20 - thus keeping their weighting easily comparable to "good" attributes).
Big kudos to the original, and great job with those add-ons! I'll be sure to buy a Koffee for ya @mavali . And "bon travail" to you @Purity . All of the new features are an absolutely great idea to be added. I upvote them!
Also, I'm raising my hand if you want beta testers for some features or even accept contributors. This project is one of the best companion app I've found for us FM niche nerds
Great job btw
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?
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?
This guy is proficient as a DC, and can play somewhat as DR, DM and, to a lesser extent, WBR
Hi general rating (purely calculated through the attributes weighting) is similar everywhere (the weights are similar everywhere, except DC and ST where jumping reach has higher value in general)
Pretty much 41 across the board, and 42/43 DC/ST (the dude is huge)
Now, if we look at the actual position rating (the ones that appear if you set position ratings in your columns - it never shows the general rating), we see that the difference between his positional score as DC and as AMR is less than 10 points appart, which feels off. He should be very very low AMR, having 1 proficiency at that position.
Final thing, I never use the actual "role" rating since GS seem to add a layer of its own calculations on top of the user-defined weights. So I don't know how those relate to truly tested attributes.
My understanding is that, according to the rating filter, each player gets a score for each position.
This is the "general rating", when looking at one player's profil in GS. Then, the general rating is adjusted as a "positional rating" according to the player's position proficiency.
When chosing which player to play at a given position, "positional rating" is thus more relevant since it takes into consideration the position's proficiency. However, this can't seem to be configurable and only a GS inner calculation. We've seen somewhere that 1 point of proficiency has the similar impact on a player's performance than 1 point of pace "lost". E.g. A player with 17 speed and natural (20) is similar in performance than a player with 20 speed and accomplished (17). It's probably more complex than that, but it is the simplest way to compare.
Now, I'm not sure that this translates well into GS "positinal rating". For instance, let's look at 2 players in my team, contenders for playing WBL (for the sake of the discussion). I'm using the GS file in the OG post (zhf2yl)
Player A:
General Rating = 45.0
WBL proficiency = 10
Positional Rating = 42.91 (So being only 10 proficient made him drop 2.09 pts)
He is 45.0 positional rating for DR
Player B:
General Rating = 42.6
WBL proficiency = 15
Positional Rating = 41.74 (So having 5 less than 20 proficiency made him drop 0.86 pts)
He is 42.6 positional rating for DL
I feel like, even if GS shows player A as a better WBL, player B might be a better option. It seems to me that GS does not weight positional proficiency enough. My personal impression is that we should remove another 0.5 pt per proficiency below 20 to actually represent the player's efficiency.
That would make the "adjusted positional rating" like so:
Player A: 37.91
Player B: 40.24 (He's now the best WBL between the two)
For reference, I have a player C with 1 in WBL proficiency:
Player C:
General Rating = 53.3
WBL proficiency = 1
Positional Rating = 42.7 (Just 10.6 pts less, even being totally ineffectual)
Making him "theoretically" (without the adujsted positional rating) the best WBL even with 1 proficiency.
I'd like thoughts of smarter people than me on this.