Recall that 87% for ST is 2.571 and 73% for ST is 6.111, and that positions other than ST appear to be consistently ~1 position lower.
Every position for the Knap 424 formation has been sampled now, and I'm satisfied that the same set of required attributes apply to all outfield positions in the same way.
I've done some readjustments to the weightings.
I've dropped Sterling the equivalent of ~1 position, but this means he should we should expect no worse than ~4 position, yet his average is 5.375 if we give +1 for not being ST. This is the best I've been able to do.
Non-ST positions seem more comparable to ST now (less unexplained position difference), and stamina is now a more reasonable 40 instead of 94 weight - stamina seemed to be the partial cause of Sterling's overrating. Quite a few players have pleasant coincidental changes, such as Maeda going higher and Gyokeres lower, which is more line with the real rankings.
However some changes had to go with it, such as Vlahovic dropping a little below Messi. I figure it's more likely that Sterling should drop 1 position, than Vlahovic should not drop 0.5 position. And given most players seem more to be more accurate now, I'm not too concerned about Vlahovic.
Next step is translating to Genie Scout weights, then I can upload the updated file. Main reason for updated file will be adding the new GK weights of course.
Recall that 87% for ST is 2.571 and 73% for ST is 6.111, and that positions other than ST appear to be consistently ~1 position lower.
Every position for the Knap 424 formation has been sampled now, and I'm satisfied that the same set of required attributes apply to all outfield positions in the same way.
I've done some readjustments to the weightings.
I've dropped Sterling the equivalent of ~1 position, but this means he should we should expect no worse than ~4 position, yet his average is 5.375 if we give +1 for not being ST. This is the best I've been able to do.
Non-ST positions seem more comparable to ST now (less unexplained position difference), and stamina is now a more reasonable 40 instead of 94 weight - stamina seemed to be the partial cause of Sterling's overrating. Quite a few players have pleasant coincidental changes, such as Maeda going higher and Gyokeres lower, which is more line with the real rankings.
However some changes had to go with it, such as Vlahovic dropping a little below Messi. I figure it's more likely that Sterling should drop 1 position, than Vlahovic should not drop 0.5 position. And given most players seem more to be more accurate now, I'm not too concerned about Vlahovic.
Next step is translating to Genie Scout weights, then I can upload the updated file. Main reason for updated file will be adding the new GK weights of course. Expand
Citation [citation='GeorgeFloydOverdosed' commentaire='53680'] 86 % | Eduardo Camavinga (DM) = 3e, 5e, 2e, 3e, 4e = 3,4 position 73 % | Andrian Kraev (DM) = 9e, 8e, 5e, 5e = 6,75 position
Rappelons que 87 % pour ST équivaut à 2,571 % et 73 % pour ST est à 6,111, et que les positions autres que ST semblent constamment ~1 position plus basses.
Chaque position pour la formation Knap 424 a été échantillonnée maintenant, et je suis satisfait que le même ensemble d’attributs requis s’applique à toutes les positions de champ extérieur de la même manière.
J’ai fait quelques ajustements des pondérations.
J’ai laissé tomber Sterling l’équivalent de ~1 position, mais cela signifie qu’il devrait s’attendre à une position de ~4, pourtant sa moyenne est de 5,375 si on donne +1 pour ne pas être ST. C’est le mieux que j’ai pu faire.
Les positions non-ST semblent désormais plus comparables aux ST (moins de différence de position inexpliquée), et l’endurance est désormais plus raisonnable à 40 au lieu de 94 - l’endurance semblait être la cause partielle de la surévaluation de Sterling. Beaucoup de joueurs ont des changements agréables et fortuits, comme Maeda qui monte plus haut et Gyokeres redescend, ce qui correspond davantage au classement réel.
Cependant, certains changements ont dû aller avec, comme la chute de Vlahovic un peu en dessous de Messi. Je pense qu’il est plus probable que Sterling perde 1 position, que Vlahovic ne perd pas 0,5 position. Et comme la plupart des joueurs semblent plus précis aujourd’hui, je ne m’inquiète pas trop pour Vlahovic.
L’étape suivante consiste à traduire en poids Genie Scout, puis je pourrai télécharger le fichier mis à jour. La principale raison de la mise à jour du fichier sera bien sûr d’ajouter les nouveaux poids de gardien. [/citation]
Reading back through this thread's evolution, a few points seem worth flagging clearly — not to dismiss the overall contribution (the physical-attributes-dominate thesis holds up well against Zippo's isolated A/B test and skawkclsrn's large-scale randomized study), but because several specific claims here don't hold up as well as they're presented:
The "position proficiency caps at 18" claim (repeated with confidence early on) turned out to be wrong once tested — worth flagging since it may still be floating around in older posts/quotes. The Genie Scout personality-weighting bug wasn't caught internally — it took LightningFlik's independent tool to demonstrate the Osimhen-over-Haaland inconsistency. Worth being more explicit that GS output shouldn't be trusted at face value for hidden attributes even now. The "Blended" file and the "15 pace/acc realistic template" contradict each other on your own numbers (the Newcastle-vs-synthetic-squad comparison) — this was acknowledged but never really resolved, just reframed as "the file is a rough guesstimate." That's a fair characterization, but it should probably be stated up front rather than discovered by a reader cross-checking the math. The "attribute thresholds are relative to competition level" theory, used to explain away discrepancies with ykykyk05251/Zippo/Orion/HarvestGreen22, has never actually been tested — and skawkclsrn's much larger randomized dataset found no thresholds anywhere, which cuts against it rather than for it. A lot of the decimal-precision weights (Pressure=52, Determination=56, etc.) come from single small-sample runs, some explicitly labeled "pure speculation" or "I don't remember why I set this" in your own posts. That's fine as a starting point, but the precision of the numbers implies a confidence level the underlying data doesn't really support.
None of this undercuts the value of the overall synthesis — it's clearly the most complete one on the forum. But the granular numbers probably deserve a "confidence level" caveat next to them, given how often they've had to be walked back or reframed.
Ndour17 said: Reading back through this thread's evolution, a few points seem worth flagging clearly — not to dismiss the overall contribution (the physical-attributes-dominate thesis holds up well against Zippo's isolated A/B test and skawkclsrn's large-scale randomized study), but because several specific claims here don't hold up as well as they're presented:
The "position proficiency caps at 18" claim (repeated with confidence early on) turned out to be wrong once tested — worth flagging since it may still be floating around in older posts/quotes. The Genie Scout personality-weighting bug wasn't caught internally — it took LightningFlik's independent tool to demonstrate the Osimhen-over-Haaland inconsistency. Worth being more explicit that GS output shouldn't be trusted at face value for hidden attributes even now. The "Blended" file and the "15 pace/acc realistic template" contradict each other on your own numbers (the Newcastle-vs-synthetic-squad comparison) — this was acknowledged but never really resolved, just reframed as "the file is a rough guesstimate." That's a fair characterization, but it should probably be stated up front rather than discovered by a reader cross-checking the math. The "attribute thresholds are relative to competition level" theory, used to explain away discrepancies with ykykyk05251/Zippo/Orion/HarvestGreen22, has never actually been tested — and skawkclsrn's much larger randomized dataset found no thresholds anywhere, which cuts against it rather than for it. A lot of the decimal-precision weights (Pressure=52, Determination=56, etc.) come from single small-sample runs, some explicitly labeled "pure speculation" or "I don't remember why I set this" in your own posts. That's fine as a starting point, but the precision of the numbers implies a confidence level the underlying data doesn't really support.
None of this undercuts the value of the overall synthesis — it's clearly the most complete one on the forum. But the granular numbers probably deserve a "confidence level" caveat next to them, given how often they've had to be walked back or reframed. Expand Yes, these are good points, and most of them I still keep in mind, but it can be difficult to remember everything. I can see you've done a close reading, because I know some things here that I think everybody would have skipped over.
I will clarify a few things:
1) The hiddens bug with Genie Scout indeed remains unresolved, so I highly recommend to use FMST26 or FMSS. I choose to put out a GS file anyway because there are still useless features it has that the other two lack, plus its the established tool. I halved the personality weightings in my GS file to try and temper whatever inaccuracies arise, as personality turns out to be relatively unimportant for performance, but they remain included because I have to keep injury proneness and dirtiness in there anyway - there's no way around it. I'm no longer doing the ranking-to-weights match up work in GS, but I was initially, so this should bypass the bug issue to a degree, though now I do the weight work in FMST26 so it will probably drift more and more away from being accurate in GS. Long story short though, I think it's viable to continue using GS.
2) Pressure, determination, I think perhaps aggression, and no doubt a couple of others that are mainly 0 CA attributes were never properly refined in my template tests. So I tested determination at 14, but unlike many/most other attributes, I didn't get round to trying it at 13, 12, and so on. So in theory an attribute like aggression could be anywhere between '1' and '11' as a requirement. It's set at 11 because I believe it matters, unlike say passing, based on either other people's tests, or my own previous tests (say the 1CA tests). I figured at the time that since these are 0 CA cost attributes, or necessary for player growth anyway (i.e. determination), then it's not a priority to pin them down like I pinned down agility to 10. I ended up never getting around to completing it thoroughly.
3) I am pretty dead certain there are attribute thresholds relative to competition level. HarvestGreen22's data shows this clearly. It's what I have observed, even now with the real player rank data albeit its more convincing than definitive - Haaland comes no.1, but he has work rate of 13. Luis Suarez has godly technicals & mentals, but very low acc/pace/sta, and we see he is one of the worst performers. Those are the obvious examples, but I've seen many more subtle ones that are nonetheless identifiable. All that said, work rate does appear to be of importance even beyond ~11-13, and we see similar things for stamina and anticipation and whatnot, so while I'm sure there are attribute thresholds, the understanding of the curvature could do with refinement. Part of it could be that certain things kick in at certain levels. My observation with GKs is that at a mid level, reflexes matter less, but reflexes seem to take precedence at a high level (~15+) while aerial reach is essential at mid level but is significantly less essential at a high level (~15+).
4) I don't recall the Blended file vs template problem. And I'm not sure which came first, so I can't assume it's that the template invalidated the Blended file. All I can say is that when I did my best attempt at an objective comparative test of all the files, the Blended one did poorly. From memory, the Blended file was mainly based on HarvestGreen22's data + consideration of CA weights + consideration of player growth. I was also still using positional differences at that time, which now turns out to be bunk. As a point of history now, we can go back and ask 'Well, was the Blended file actually a step backwards from even the first file, and therefore do you regret putting it out there?'. At least that's the question I ask myself. And for the other files, I can say, 'they were better than the first file, but perhaps only marginally in hindsight'. Actually was striking to me was how although the improvement was marginal, the improvements of my files and those of others appear remarkably gradual and consistent. I would have expected things to be more over the place. And I could be wrong, but I think this latest method and the weightings derived from it are a big step forward.
5) I think it needs to be restated the current precision of the attribute weights does not reflect the actual real influence/value of the attribute. I'm merely moving numbers up and down to get a best fit of the data. It's like wedging a piece of wood inbetween two metal joints to make the leaning tower stable. It's not the right material, but if it works, it works, and we can replace it with the nuts and bolts later.
GeorgeFloydOverdosed said: 4) I don't recall the Blended file vs template problem. And I'm not sure which came first, so I can't assume it's that the template invalidated the Blended file. All I can say is that when I did my best attempt at an objective comparative test of all the files, the Blended one did poorly. From memory, the Blended file was mainly based on HarvestGreen22's data + consideration of CA weights + consideration of player growth. I was also still using positional differences at that time, which now turns out to be bunk. As a point of history now, we can go back and ask 'Well, was the Blended file actually a step backwards from even the first file, and therefore do you regret putting it out there?'. At least that's the question I ask myself. And for the other files, I can say, 'they were better than the first file, but perhaps only marginally in hindsight'. Actually was striking to me was how although the improvement was marginal, the improvements of my files and those of others appear remarkably gradual and consistent. I would have expected things to be more over the place. And I could be wrong, but I think this latest method and the weightings derived from it are a big step forward. Expand Weirdly enough the blended file has been my favorite one so far out of all the ones I've used, but I'm generally not only looking for the "best" player and prefer getting a mix of performance and potential.
mytreds said: Would any of the advice in the OP work in older FM titles? Expand For attributes, too hard to say, but I think it's more likely things have stayed the same than that they have changed. I suspect it would largely hold true going back to ~FM18 at least, but that's just my guess.
For everything else, it should be true going back a long way.
86% | Eduardo Camavinga (DM) = 3rd, 5th, 2nd, 3rd, 4th = 3.4 position
73% | Andrian Kraev (DM) = 9th, 8th, 5th, 5th = 6.75 position
Recall that 87% for ST is 2.571 and 73% for ST is 6.111, and that positions other than ST appear to be consistently ~1 position lower.
Every position for the Knap 424 formation has been sampled now, and I'm satisfied that the same set of required attributes apply to all outfield positions in the same way.
I've done some readjustments to the weightings.
I've dropped Sterling the equivalent of ~1 position, but this means he should we should expect no worse than ~4 position, yet his average is 5.375 if we give +1 for not being ST. This is the best I've been able to do.
Non-ST positions seem more comparable to ST now (less unexplained position difference), and stamina is now a more reasonable 40 instead of 94 weight - stamina seemed to be the partial cause of Sterling's overrating. Quite a few players have pleasant coincidental changes, such as Maeda going higher and Gyokeres lower, which is more line with the real rankings.
However some changes had to go with it, such as Vlahovic dropping a little below Messi. I figure it's more likely that Sterling should drop 1 position, than Vlahovic should not drop 0.5 position. And given most players seem more to be more accurate now, I'm not too concerned about Vlahovic.
Next step is translating to Genie Scout weights, then I can upload the updated file. Main reason for updated file will be adding the new GK weights of course.
GeorgeFloydOverdosed said: 86% | Eduardo Camavinga (DM) = 3rd, 5th, 2nd, 3rd, 4th = 3.4 position
73% | Andrian Kraev (DM) = 9th, 8th, 5th, 5th = 6.75 position
Recall that 87% for ST is 2.571 and 73% for ST is 6.111, and that positions other than ST appear to be consistently ~1 position lower.
Every position for the Knap 424 formation has been sampled now, and I'm satisfied that the same set of required attributes apply to all outfield positions in the same way.
I've done some readjustments to the weightings.
I've dropped Sterling the equivalent of ~1 position, but this means he should we should expect no worse than ~4 position, yet his average is 5.375 if we give +1 for not being ST. This is the best I've been able to do.
Non-ST positions seem more comparable to ST now (less unexplained position difference), and stamina is now a more reasonable 40 instead of 94 weight - stamina seemed to be the partial cause of Sterling's overrating. Quite a few players have pleasant coincidental changes, such as Maeda going higher and Gyokeres lower, which is more line with the real rankings.
However some changes had to go with it, such as Vlahovic dropping a little below Messi. I figure it's more likely that Sterling should drop 1 position, than Vlahovic should not drop 0.5 position. And given most players seem more to be more accurate now, I'm not too concerned about Vlahovic.
Next step is translating to Genie Scout weights, then I can upload the updated file. Main reason for updated file will be adding the new GK weights of course.
Can’t wait to see the new weights
Citation [citation='GeorgeFloydOverdosed' commentaire='53680']
86 % | Eduardo Camavinga (DM) = 3e, 5e, 2e, 3e, 4e = 3,4 position
73 % | Andrian Kraev (DM) = 9e, 8e, 5e, 5e = 6,75 position
Rappelons que 87 % pour ST équivaut à 2,571 % et 73 % pour ST est à 6,111, et que les positions autres que ST semblent constamment ~1 position plus basses.
Chaque position pour la formation Knap 424 a été échantillonnée maintenant, et je suis satisfait que le même ensemble d’attributs requis s’applique à toutes les positions de champ extérieur de la même manière.
J’ai fait quelques ajustements des pondérations.
J’ai laissé tomber Sterling l’équivalent de ~1 position, mais cela signifie qu’il devrait s’attendre à une position de ~4, pourtant sa moyenne est de 5,375 si on donne +1 pour ne pas être ST. C’est le mieux que j’ai pu faire.
Les positions non-ST semblent désormais plus comparables aux ST (moins de différence de position inexpliquée), et l’endurance est désormais plus raisonnable à 40 au lieu de 94 - l’endurance semblait être la cause partielle de la surévaluation de Sterling. Beaucoup de joueurs ont des changements agréables et fortuits, comme Maeda qui monte plus haut et Gyokeres redescend, ce qui correspond davantage au classement réel.
Cependant, certains changements ont dû aller avec, comme la chute de Vlahovic un peu en dessous de Messi. Je pense qu’il est plus probable que Sterling perde 1 position, que Vlahovic ne perd pas 0,5 position. Et comme la plupart des joueurs semblent plus précis aujourd’hui, je ne m’inquiète pas trop pour Vlahovic.
L’étape suivante consiste à traduire en poids Genie Scout, puis je pourrai télécharger le fichier mis à jour. La principale raison de la mise à jour du fichier sera bien sûr d’ajouter les nouveaux poids de gardien.
[/citation]
Reading back through this thread's evolution, a few points seem worth flagging clearly — not to dismiss the overall contribution (the physical-attributes-dominate thesis holds up well against Zippo's isolated A/B test and skawkclsrn's large-scale randomized study), but because several specific claims here don't hold up as well as they're presented:
The "position proficiency caps at 18" claim (repeated with confidence early on) turned out to be wrong once tested — worth flagging since it may still be floating around in older posts/quotes.
The Genie Scout personality-weighting bug wasn't caught internally — it took LightningFlik's independent tool to demonstrate the Osimhen-over-Haaland inconsistency. Worth being more explicit that GS output shouldn't be trusted at face value for hidden attributes even now.
The "Blended" file and the "15 pace/acc realistic template" contradict each other on your own numbers (the Newcastle-vs-synthetic-squad comparison) — this was acknowledged but never really resolved, just reframed as "the file is a rough guesstimate." That's a fair characterization, but it should probably be stated up front rather than discovered by a reader cross-checking the math.
The "attribute thresholds are relative to competition level" theory, used to explain away discrepancies with ykykyk05251/Zippo/Orion/HarvestGreen22, has never actually been tested — and skawkclsrn's much larger randomized dataset found no thresholds anywhere, which cuts against it rather than for it.
A lot of the decimal-precision weights (Pressure=52, Determination=56, etc.) come from single small-sample runs, some explicitly labeled "pure speculation" or "I don't remember why I set this" in your own posts. That's fine as a starting point, but the precision of the numbers implies a confidence level the underlying data doesn't really support.
None of this undercuts the value of the overall synthesis — it's clearly the most complete one on the forum. But the granular numbers probably deserve a "confidence level" caveat next to them, given how often they've had to be walked back or reframed.
Ndour17 said: Reading back through this thread's evolution, a few points seem worth flagging clearly — not to dismiss the overall contribution (the physical-attributes-dominate thesis holds up well against Zippo's isolated A/B test and skawkclsrn's large-scale randomized study), but because several specific claims here don't hold up as well as they're presented:
The "position proficiency caps at 18" claim (repeated with confidence early on) turned out to be wrong once tested — worth flagging since it may still be floating around in older posts/quotes.
The Genie Scout personality-weighting bug wasn't caught internally — it took LightningFlik's independent tool to demonstrate the Osimhen-over-Haaland inconsistency. Worth being more explicit that GS output shouldn't be trusted at face value for hidden attributes even now.
The "Blended" file and the "15 pace/acc realistic template" contradict each other on your own numbers (the Newcastle-vs-synthetic-squad comparison) — this was acknowledged but never really resolved, just reframed as "the file is a rough guesstimate." That's a fair characterization, but it should probably be stated up front rather than discovered by a reader cross-checking the math.
The "attribute thresholds are relative to competition level" theory, used to explain away discrepancies with ykykyk05251/Zippo/Orion/HarvestGreen22, has never actually been tested — and skawkclsrn's much larger randomized dataset found no thresholds anywhere, which cuts against it rather than for it.
A lot of the decimal-precision weights (Pressure=52, Determination=56, etc.) come from single small-sample runs, some explicitly labeled "pure speculation" or "I don't remember why I set this" in your own posts. That's fine as a starting point, but the precision of the numbers implies a confidence level the underlying data doesn't really support.
None of this undercuts the value of the overall synthesis — it's clearly the most complete one on the forum. But the granular numbers probably deserve a "confidence level" caveat next to them, given how often they've had to be walked back or reframed.
Yes, these are good points, and most of them I still keep in mind, but it can be difficult to remember everything. I can see you've done a close reading, because I know some things here that I think everybody would have skipped over.
I will clarify a few things:
1) The hiddens bug with Genie Scout indeed remains unresolved, so I highly recommend to use FMST26 or FMSS. I choose to put out a GS file anyway because there are still useless features it has that the other two lack, plus its the established tool. I halved the personality weightings in my GS file to try and temper whatever inaccuracies arise, as personality turns out to be relatively unimportant for performance, but they remain included because I have to keep injury proneness and dirtiness in there anyway - there's no way around it. I'm no longer doing the ranking-to-weights match up work in GS, but I was initially, so this should bypass the bug issue to a degree, though now I do the weight work in FMST26 so it will probably drift more and more away from being accurate in GS. Long story short though, I think it's viable to continue using GS.
2) Pressure, determination, I think perhaps aggression, and no doubt a couple of others that are mainly 0 CA attributes were never properly refined in my template tests. So I tested determination at 14, but unlike many/most other attributes, I didn't get round to trying it at 13, 12, and so on. So in theory an attribute like aggression could be anywhere between '1' and '11' as a requirement. It's set at 11 because I believe it matters, unlike say passing, based on either other people's tests, or my own previous tests (say the 1CA tests). I figured at the time that since these are 0 CA cost attributes, or necessary for player growth anyway (i.e. determination), then it's not a priority to pin them down like I pinned down agility to 10. I ended up never getting around to completing it thoroughly.
3) I am pretty dead certain there are attribute thresholds relative to competition level. HarvestGreen22's data shows this clearly. It's what I have observed, even now with the real player rank data albeit its more convincing than definitive - Haaland comes no.1, but he has work rate of 13. Luis Suarez has godly technicals & mentals, but very low acc/pace/sta, and we see he is one of the worst performers. Those are the obvious examples, but I've seen many more subtle ones that are nonetheless identifiable. All that said, work rate does appear to be of importance even beyond ~11-13, and we see similar things for stamina and anticipation and whatnot, so while I'm sure there are attribute thresholds, the understanding of the curvature could do with refinement. Part of it could be that certain things kick in at certain levels. My observation with GKs is that at a mid level, reflexes matter less, but reflexes seem to take precedence at a high level (~15+) while aerial reach is essential at mid level but is significantly less essential at a high level (~15+).
4) I don't recall the Blended file vs template problem. And I'm not sure which came first, so I can't assume it's that the template invalidated the Blended file. All I can say is that when I did my best attempt at an objective comparative test of all the files, the Blended one did poorly. From memory, the Blended file was mainly based on HarvestGreen22's data + consideration of CA weights + consideration of player growth. I was also still using positional differences at that time, which now turns out to be bunk. As a point of history now, we can go back and ask 'Well, was the Blended file actually a step backwards from even the first file, and therefore do you regret putting it out there?'. At least that's the question I ask myself. And for the other files, I can say, 'they were better than the first file, but perhaps only marginally in hindsight'. Actually was striking to me was how although the improvement was marginal, the improvements of my files and those of others appear remarkably gradual and consistent. I would have expected things to be more over the place. And I could be wrong, but I think this latest method and the weightings derived from it are a big step forward.
5) I think it needs to be restated the current precision of the attribute weights does not reflect the actual real influence/value of the attribute. I'm merely moving numbers up and down to get a best fit of the data. It's like wedging a piece of wood inbetween two metal joints to make the leaning tower stable. It's not the right material, but if it works, it works, and we can replace it with the nuts and bolts later.
GeorgeFloydOverdosed said: 4) I don't recall the Blended file vs template problem. And I'm not sure which came first, so I can't assume it's that the template invalidated the Blended file. All I can say is that when I did my best attempt at an objective comparative test of all the files, the Blended one did poorly. From memory, the Blended file was mainly based on HarvestGreen22's data + consideration of CA weights + consideration of player growth. I was also still using positional differences at that time, which now turns out to be bunk. As a point of history now, we can go back and ask 'Well, was the Blended file actually a step backwards from even the first file, and therefore do you regret putting it out there?'. At least that's the question I ask myself. And for the other files, I can say, 'they were better than the first file, but perhaps only marginally in hindsight'. Actually was striking to me was how although the improvement was marginal, the improvements of my files and those of others appear remarkably gradual and consistent. I would have expected things to be more over the place. And I could be wrong, but I think this latest method and the weightings derived from it are a big step forward.
Weirdly enough the blended file has been my favorite one so far out of all the ones I've used, but I'm generally not only looking for the "best" player and prefer getting a mix of performance and potential.
Premier League 2.1 weights
FMST26 weights (copy paste this into statistics > custom metrics (advanced)):
Outfield:
(acceleration * 90.5 + pace * 94 + jumping_reach * 43 + pressure * 17 + dribbling * 14.3 + work_rate * 66.5 + agility * 16.0 + anticipation * 40 + composure * 26 + stamina * 50 + consistency * 14.05 + determination * 43.5 + balance * 14.25 + strength * 5.0 + concentration * 45 + finishing * 2.0 + important_matches * 10.1 + natural_fitness * 6.45 + professionalism * 15.0 + ambition * 2.0 + loyalty * 1.0 + aggression * 10 + vision * 0.5 + left_foot * 6 + right_foot * 5 - (injury_proneness * (48 / (natural_fitness * 0.75))) - (dirtiness * 32 * (aggression * 0.1))) / 113.2
GK:
((aerial_reach * 28.68 + command_of_area * 15.69 + first_touch * 16.99 + passing * 10.46 + reflexes * 86 + concentration * 82.35 + determination * 88.89 + work_rate * 38.68 + acceleration * 15.03 + balance * 10.46 + agility * 32.68 + jumping_reach * 14.30 + natural_fitness * 10.46 + pace * 28.30 + stamina * 32.68 + strength * 10.46 + technique * 15.69 + pressure * 15.03 + professionalism * 9.80 + flair * 49.02 - injury_proneness * 49.02 + vision * 25 - dirtiness * 16.34 - ca * 9.80)) / 84.5
Genie Scout file: https://files.catbox.moe/9n18q0.grf
I translated it to GS as best I could.
Outfield:
90% | Erling Haaland - 1st, 1st, 4th, 1st, 2nd, 1st = 1.666 position
88% | Kylian Mbappe - 2nd, 3rd, 3rd, 3rd, 5th, 2nd, 1st, 1st = 2.5 position
87% | Mohamed Salah* - 1st, 3rd, 5th, 3rd, 3rd, 2nd, 1st = 2.571 position
88% | Kylian Mbappe (AML) - 1st, 2nd, 3rd, 5th = 2.75 position
82% | Bukayo Saka (AMR) - 2nd, 3rd, 3rd, 3rd = 2.75 position
82% | Heung-Min Son - 3rd, 2nd, 2nd, 2nd, 2nd, 6th, 4th = 3 position
83% | Daizen Maeda - 2nd, 3rd, 4th, 4th, 2nd, 3rd, 3rd = 3 position
80% | Kyogo Furuhashi - 4th, 2nd, 3rd, 5th, 3rd, 2nd, 2nd = 3 position
82% | Vinicius Junior - 5th, 4th, 1st, 3rd = 3.25 position
83% | Eduardo Camavinga (DM) = 3rd, 5th, 2nd, 3rd, 4th = 3.4 position
82% | Harry Kane - 5th, 2nd, 3rd, 3rd, 1st, 7th = 3.5 position
83% | Robert Lewandowski - 2nd, 2nd, 2nd, 3rd, 5th, 2nd, 8th, 5th, 3rd = 3.555 position
77% | Dusan Vlahovic - 1st, 4th, 4th, 5th, 1st, 6th, 4th, 4th = 3.625
82% | Lautaro Martinez - 7th, 3rd, 1st, 5th, 2nd, 5th, 2nd, 5th = 3.75 position
80% | Victor Osimhen - 3rd, 3rd, 7th, 3rd, 3rd, 4th, 3rd, 4th = 3.833 position
78% | Lionel Messi - 4th, 2nd, 1st, 5th, 9th, 3rd = 4 position
79% | Viktor Gyokeres - 6th, 4th, 3rd, 4th, 5th, 5th, 2nd, 5th, 2nd = 4 position
81% | Giovanni Di Lorenzo (DR) - 3rd, 3rd, 2nd, 9th, 2nd, 5th, 5th = 4.143 position
82% | Kim Min Jae (DC) - 3rd, 3rd, 6th, 6th, 3rd, 4th, 5th = 4.286 position
82% | Ronald Araujo (DR) - 4th, 8th, 3rd, 1st, 7th = 4.6 position
73% | Donyell Malen - 2nd, 2nd, 7th, 5th, 5th, 7th = 4.666 position
78% | Jules Kounde (DR) - 5th, 4th, 7th 5th, 3rd = 4.8 position
75% | Kurt Zouma (DC) - 7th, 5th, 6th, 3rd = 5.6 position
72% | Robert Glatzel - 5th, 7th, 6th, 3rd, 12th, 6th, 2nd, 6th, 8th = 6.111 position
81% | Raheem Sterling (AMR) - 6th, 7th, 7th, 7th, 6th, 6th, 6th, 6th = 6.375 position
69% | Paulo Dybala - 5th, 5th, 6th, 10th, 3rd, 12th, 6th, 5th, 6th, 6th = 6.4 position
72% | Andrian Kraev (DM) = 9th, 8th, 5th, 5th = 6.75 position
62% | Adam Le Fondre - 8th, 11th (sacked), 5th, 7th (sacked), 6th (sacked), 8th (sacked) = 7.5 position
66% | Kingsley Schindler (DR) - 4th, 11th, 6th, 11th = 8 position
63% | Luis Suarez - 7th, 9th, 10th, 8th, 8th = 8.4 position
71% | Sean Goldberg (DC) - 5th, 16th (sacked), 8th (sacked), 5th = 8.5 position
77% | Sacha Boey (DR) - 7th (sacked), 12th (sacked), 12th (sacked) = 10.333 position
Error rate = 4/32 = 12.5%
Vlahovic = 6.5% off
Malen = 6.8% off
Sterling = 12.3% off
Boey = 22.1% off
GK:
90% | Alisson - 6th, 3rd, 4th, 4th, 3rd = 4 position
84% | Thibaut Courtois - 3rd, 7th, 2nd, 5th, 8th = 5 position
82% | Jan Oblak - 5th, 8th, 6th, 4th, 3rd = 5.2 position
82% | Walter Benitez - 4th, 9th, 4th, 6th, 5th = 5.6 position
82% | Ugurcan Cakir - 7th, 9th, 2nd = 6 position
79% | Ederson - 6th, 6th, 4th, 8th, 7th, 7th = 6.333 position
81% | Marc-Andre ter Stegen - 10th, 11th, 4th, 4th, 3rd = 6.4 position
84% | Gregor Kobel - 4th, 12th, 2nd, 10th (sacked), 3rd, 10th (sacked), 5th = 6.571 position
78% | Anatolii Trubin - 15th (sacked), 6th, 4th (sacked), 5th = 7.5 position
70% | Davy Roef - 13th (sacked), 4th, 14th (sacked), 6th (sacked), 1st = 7.6 position
61% | Jack Stevens - 13th (sacked), 4th, 9th (sacked), 8th (sacked), 8th (sacked) = 8.4 position
75% | Sinan Bolat - 4th, 2nd, 19th (sacked), 5th, 14th (sacked), 9th (sacked), 12th (sacked), 5th = 8.75 position
67% | Ben Winterbottom - 10th (sacked), 5th (sacked), 12th (sacked), 18th (sacked) = 11.25 position
Harder to tell who is inaccurate and who is error for GK..
Error rate = 3/13 = 23.1%
Kobel = 7.1% off
Roef = 7.1%(?) off
Stevens = 18.0%(?) off
Would any of the advice in the OP work in older FM titles?
mytreds said: Would any of the advice in the OP work in older FM titles?
For attributes, too hard to say, but I think it's more likely things have stayed the same than that they have changed. I suspect it would largely hold true going back to ~FM18 at least, but that's just my guess.
For everything else, it should be true going back a long way.