First, I want to say that if you play on PC and are good with Python, you should really follow what Squirrel_Plays is doing on Youtube. It's amazing, it's the right way to go about stuff like this, total option for automation and quantitative analysis.
However, if you play on Touch/Console or just aren't that great at Python (I fit both categories) you might want a spreadsheet tool to help with player evaluations and transfer windows and such.
It uses FMScout attribute weights for positions vs. ykykyk, but you could easily modify it to use ykykyk. (I also use a different modified version for my saves that stresses other attributes and gives different weights to attributes that I would stress for my style of play).
But here's some things you might find helpful:
1.) You enter in the player attribute numbers, and it creates a score that is the sum of all the attributes multiplied by their FMScout weights.
2.) It calculates a score that compares that aggregate player attribute score to a score of a player who has "all 12s" - trying to represent how the player might compare to an absolutely "average" player (my attempt at baseball's WAR for FManager).
3.) It also has conditional formatting that will show if the player is actually a "13.5" or above.
4.) Because nobody is perfect (no straight 20's) I also do something to compare the player to the "Best In World." Basically, what I do is wait for the game to give me the "top 50" for the year, find the best for each position, and enter their attributes for their position. The weighted aggregate of their attributes for the position are then used as a "Best In World" score and each of your team's players can be compared to the very best. So I have a Wonderkid that I've helped become "95% of an Mbappe" at his peak.
5.) I'm also experimenting with comparing the weighted scores with the player spend (to optimize roster building on poor clubs). But I'm not sold on my current approach (simply dividing the weighted aggregate by their salary).
anyway, if you like it, cool let me know. If there are flaws or improvements, let me know, too.
I just type them in. Again, I've been playing on an iPad, and with it's limited capabilities, I will just type stuff from screen to screen. I suppose I could create a custom view based on the attributes for the individual position, but i'm lazy.
Kudos to you, AlexH for taking the initiative on this project! It's evident that you've put hard work into this and I'm sure many in the community will be thrilled with this valuable addition, and your efforts are truly appreciated.
That being said; Squirrel_Plays and Davy_Depuyt, the brain behind the FM LineUp Tool and now the FMPlus series, have the same working method that I find problematic.
They both operate under the assumption that the information provided by Sports Interactive (SI) within the game is entirely accurate. Per position attributes are divided into three categories: Required, Preferred, and Irrelevant. Required attributes carry the most weight, preferred attributes a bit less, and irrelevant attributes are ignored in their calculations.
However, if you've been keeping up with this forum and its tests and results, you might be aware that SI's information is often misleading. You can read more about it here:link.
The issue here is that attributes like "Finishing," which has been repeatedly shown to be of much less importance for most players, even strikers, are suddenly given significant weight in their calculations for various positions. This obviously skews the final results.
As it stands, I believe that FM Genie Scout still provides the most accurate results because it allows you to customize the weight of each attribute for different positions in the settings. By effectively adjusting these weights, you can prioritize attributes like Pace and Acceleration, which in reality have a more significant impact on a player's performance.
Originally inspired by the FM LineUp Tool, and subsequently Squirrel_Plays' Youtube videos I am working on very simple tool, just for private use, as it's far from a finished product to release.
The issue with these type of programs is that they're only able to take into account current attributes, and don't pay attention to possible future development of players. So FM Genie Scout is still King for me.
They both operate under the assumption that the information provided by Sports Interactive (SI) within the game is entirely accurate. Per position attributes are divided into three categories: Required, Preferred, and Irrelevant. Required attributes carry the most weight, preferred attributes a bit less, and irrelevant attributes are ignored in their calculations.
Right? That's one of the reasons I love the attribute testing on this site, but as you say, it could use what feels like an endless amount of work and variable manipulation to get closer to reality.
I love the python tooling. Will switch someday to it - if only because I want to weight statistical results in decision making more than the "attribute weight only" approach I have now.
Hi,
First, I want to say that if you play on PC and are good with Python, you should really follow what Squirrel_Plays is doing on Youtube. It's amazing, it's the right way to go about stuff like this, total option for automation and quantitative analysis.
However, if you play on Touch/Console or just aren't that great at Python (I fit both categories) you might want a spreadsheet tool to help with player evaluations and transfer windows and such.
I made one, it's on my github here:
https://github.com/AlexanderHutton/AlexFMXLS/blob/main/AlexFM24RatingsMkIII.xlsx
It uses FMScout attribute weights for positions vs. ykykyk, but you could easily modify it to use ykykyk. (I also use a different modified version for my saves that stresses other attributes and gives different weights to attributes that I would stress for my style of play).
But here's some things you might find helpful:
1.) You enter in the player attribute numbers, and it creates a score that is the sum of all the attributes multiplied by their FMScout weights.
2.) It calculates a score that compares that aggregate player attribute score to a score of a player who has "all 12s" - trying to represent how the player might compare to an absolutely "average" player (my attempt at baseball's WAR for FManager).
3.) It also has conditional formatting that will show if the player is actually a "13.5" or above.
4.) Because nobody is perfect (no straight 20's) I also do something to compare the player to the "Best In World." Basically, what I do is wait for the game to give me the "top 50" for the year, find the best for each position, and enter their attributes for their position. The weighted aggregate of their attributes for the position are then used as a "Best In World" score and each of your team's players can be compared to the very best. So I have a Wonderkid that I've helped become "95% of an Mbappe" at his peak.
5.) I'm also experimenting with comparing the weighted scores with the player spend (to optimize roster building on poor clubs). But I'm not sold on my current approach (simply dividing the weighted aggregate by their salary).
anyway, if you like it, cool let me know. If there are flaws or improvements, let me know, too.
The link didn't seem to come through - https://github.com/AlexanderHutton/AlexFMXLS/blob/main/AlexFM24RatingsMkIII.xlsx
Cheers for the heads up about squirrel. Im loving his series on YT
Very nice job
But what filter view have to use to have this outcome
Can you provide them?
I just type them in. Again, I've been playing on an iPad, and with it's limited capabilities, I will just type stuff from screen to screen. I suppose I could create a custom view based on the attributes for the individual position, but i'm lazy.
tell me if you dot mind how to use it or where to type what and i fix something
Kudos to you, AlexH for taking the initiative on this project! It's evident that you've put hard work into this and I'm sure many in the community will be thrilled with this valuable addition, and your efforts are truly appreciated.
That being said; Squirrel_Plays and Davy_Depuyt, the brain behind the FM LineUp Tool and now the FMPlus series, have the same working method that I find problematic.
They both operate under the assumption that the information provided by Sports Interactive (SI) within the game is entirely accurate. Per position attributes are divided into three categories: Required, Preferred, and Irrelevant. Required attributes carry the most weight, preferred attributes a bit less, and irrelevant attributes are ignored in their calculations.
However, if you've been keeping up with this forum and its tests and results, you might be aware that SI's information is often misleading. You can read more about it here:link.
The issue here is that attributes like "Finishing," which has been repeatedly shown to be of much less importance for most players, even strikers, are suddenly given significant weight in their calculations for various positions. This obviously skews the final results.
As it stands, I believe that FM Genie Scout still provides the most accurate results because it allows you to customize the weight of each attribute for different positions in the settings. By effectively adjusting these weights, you can prioritize attributes like Pace and Acceleration, which in reality have a more significant impact on a player's performance.
Originally inspired by the FM LineUp Tool, and subsequently Squirrel_Plays' Youtube videos I am working on very simple tool, just for private use, as it's far from a finished product to release.
The issue with these type of programs is that they're only able to take into account current attributes, and don't pay attention to possible future development of players. So FM Genie Scout is still King for me.
They both operate under the assumption that the information provided by Sports Interactive (SI) within the game is entirely accurate. Per position attributes are divided into three categories: Required, Preferred, and Irrelevant. Required attributes carry the most weight, preferred attributes a bit less, and irrelevant attributes are ignored in their calculations.
Right? That's one of the reasons I love the attribute testing on this site, but as you say, it could use what feels like an endless amount of work and variable manipulation to get closer to reality.
I love the python tooling. Will switch someday to it - if only because I want to weight statistical results in decision making more than the "attribute weight only" approach I have now.