Sorry to pile on with demands @GeorgeFloydOverdosed, but can you provide these weights as raw data? That is, I don't think Genie Scout runs on Linux but I'd be interested in seeing what you've come up with.
GeorgeFloydOverdosed said: Obvious example would be finishing, where I found you can win the Premier League with 1 CA players and a ST with 1 finishing, it's just that the bulk of the goalscoring gets shifted to the other position that has the highest finishing. Expand
Well this is the thought I had. People explain the match engine the way they think it should work (e.g. "the game sees the opposing winger running to the byline, so it looks at your fullback's positioning, composure and decision making to determine whether he can track the runner and make himself available to the tackle" ) but my thought was: what if it just looks at the offensive capabilities of your team, your defensive capabilities (irrespective of what positions the players who have these attributes are in) and just simulates the results based off that, generating highlights to fit?
Hence my idea for the experiment, effectively swap your attackers' and defenders' attributes (but not their positional familiarities) and see what happens.
Idea for an experiment (which I'd run if I had a more performant PC, but I'm at the mercy of you kind strangers): what if you assembled a squad of players, who were capable of winning the league, but then randomly shuffled each player's set of attributes amongst each other?
For example, your LB has your MC's attributes, your ST has your RB's attributes, your DM has your ST's attributes and so on (leaving goalkeepers alone). Naturally each player's role analysis would be in the toilet but if experiments have revealed that tactics are less impactful than attributes alone, it might also follow that the sum talent of your team is more important than who plays where (assuming you're 1. using a tactic that makes sense and 2. players aren't playing out of position, just wildly out of role).
DOUBLE EDIT: I get it now but I've added my latest thought at the bottom.
@Possebrew Do you mind explaining the logic behind the values for the outfield and goalkeeper scaling? I read your initial post but couldn't understand what they're for.
It seems to me that they exist only to take the final rating and amplify it, but by drastically different amounts. If I've understood the formula correctly, it seems like the perfect outfield player would have a rating (using the goal weights/penalties formula) of 1016.49 and the perfect goalkeeper would be 92.75.
I don't understand why. Why not normalise the values so the best player, regardless of position, is 100? Or 1000 if you want to give more scope for variety (given that the average player is far, far, far away from perfect)?
EDIT: setting the weights to outfield:23.4631 and goalkeeper:37.7358 would ensure the perfect players are both 1,000 (but I'm not sure if that conflicts with what you were after re: the combined player contributions?)
DOUBLE EDIT: Okay, I understand now. You divide the contribution for all stats by 10 for outfield players to reflect the fact that there are 10 players contributing to the points/goals delta, and then multiply the final answer by a number to amplify the result again.
These two operations cancel each other out though, making one of them redundant.
To use my normalised example above, if you forego the division by 10 for outfield players and then multiply the final answer by 2.34631 (instead of 23.4631) then the final rating comes out to the same thing.
In theory yes but the only Mac I have is my work laptop and they'd be extremely cross with me if I installed Steam on it. In fact I'm not even sure ZScaler would let me do it. But if I open source this then it just needs someone to a) write a Mac version of the C code that reads process memory (which I could do, but I wouldn't be able to run and verify it) and b) possibly change the list of memory locations that I've got hard-coded, which need reading in order to make this all work (e.g. the memory address of the global player list, the address of the current in-game date and time).
Possebrew said: But even so, I noticed other similar tools popping up around the web lately, like FMScouts solution. Given that these teams have dedicated resources for this, it might be more realistic to expect updates from them.
If all I could provide is an impulse to create such tools, that is more than I could have ever hoped for. Indeed, the attention this calculator is something I am grateful for. Expand
You've already inspired me to create my own. I wrote some C code which reads the memory of Football Manager while it's running and serves it via a local web-server to the browser. The browser renders the currently-viewed player, a summary of all player's in your squads (and their role ratings), and I'm adding player search too (so far I've only added a wonderkid finder, because it doesn't need any input form elements configuring).
It's Linux only at the moment, but I imagine the memory addresses of various elements are the same in Windows (given how Proton works).
(You can spot the vibe-coded UI a mile away because writing CSS is the least interesting part of this for me, but all the C code to read data from memory and _all_ the investigations in to mapping the game's internals was done personally).
(No rush, whenever you have time).
Well this is the thought I had. People explain the match engine the way they think it should work (e.g. "the game sees the opposing winger running to the byline, so it looks at your fullback's positioning, composure and decision making to determine whether he can track the runner and make himself available to the tackle" ) but my thought was: what if it just looks at the offensive capabilities of your team, your defensive capabilities (irrespective of what positions the players who have these attributes are in) and just simulates the results based off that, generating highlights to fit?
Hence my idea for the experiment, effectively swap your attackers' and defenders' attributes (but not their positional familiarities) and see what happens.
For example, your LB has your MC's attributes, your ST has your RB's attributes, your DM has your ST's attributes and so on (leaving goalkeepers alone). Naturally each player's role analysis would be in the toilet but if experiments have revealed that tactics are less impactful than attributes alone, it might also follow that the sum talent of your team is more important than who plays where (assuming you're 1. using a tactic that makes sense and 2. players aren't playing out of position, just wildly out of role).
@Possebrew Do you mind explaining the logic behind the values for the outfield and goalkeeper scaling? I read your initial post but couldn't understand what they're for.
It seems to me that they exist only to take the final rating and amplify it, but by drastically different amounts. If I've understood the formula correctly, it seems like the perfect outfield player would have a rating (using the goal weights/penalties formula) of 1016.49 and the perfect goalkeeper would be 92.75.
I don't understand why. Why not normalise the values so the best player, regardless of position, is 100? Or 1000 if you want to give more scope for variety (given that the average player is far, far, far away from perfect)?
EDIT: setting the weights to outfield: 23.4631 and goalkeeper: 37.7358 would ensure the perfect players are both 1,000 (but I'm not sure if that conflicts with what you were after re: the combined player contributions?)
DOUBLE EDIT: Okay, I understand now. You divide the contribution for all stats by 10 for outfield players to reflect the fact that there are 10 players contributing to the points/goals delta, and then multiply the final answer by a number to amplify the result again.
These two operations cancel each other out though, making one of them redundant.
To use my normalised example above, if you forego the division by 10 for outfield players and then multiply the final answer by 2.34631 (instead of 23.4631) then the final rating comes out to the same thing.
Check my maths on that but I think it's right.
In theory yes but the only Mac I have is my work laptop and they'd be extremely cross with me if I installed Steam on it. In fact I'm not even sure ZScaler would let me do it. But if I open source this then it just needs someone to a) write a Mac version of the C code that reads process memory (which I could do, but I wouldn't be able to run and verify it) and b) possibly change the list of memory locations that I've got hard-coded, which need reading in order to make this all work (e.g. the memory address of the global player list, the address of the current in-game date and time).
Ah yes, the "if I can't have you, nobody can" button. I've only had cause to use it once but it was 100% justified.
If all I could provide is an impulse to create such tools, that is more than I could have ever hoped for. Indeed, the attention this calculator is something I am grateful for.
You've already inspired me to create my own. I wrote some C code which reads the memory of Football Manager while it's running and serves it via a local web-server to the browser. The browser renders the currently-viewed player, a summary of all player's in your squads (and their role ratings), and I'm adding player search too (so far I've only added a wonderkid finder, because it doesn't need any input form elements configuring).
It's Linux only at the moment, but I imagine the memory addresses of various elements are the same in Windows (given how Proton works).
(You can spot the vibe-coded UI a mile away because writing CSS is the least interesting part of this for me, but all the C code to read data from memory and _all_ the investigations in to mapping the game's internals was done personally).