For those who played with it, I'd be interested to know how the tool is performing in your leagues.
For me, I took MAN (Brazilian Third Division). Tactic: PERFECT STRANGERS Training: Quickness+2MatchPractice+1Attacking+7xRecovery + Individual Quickness
I filtered my transfers for 0 Value + Interested in loan.
We won the Brazilian Cup vs FLA and got promoted to the Second Division. Our finances are solid, upgraded everything that they'd let me upgrade, except the stadium.
We're currently in the Copa Libertadores Second Round. We scored 69 goals in the Second Division, and we're smashing all the Player Stats, where two of my best strikers are making 375$ p/w and 160$ p/w
Kamas1 said: Now I can only add dm to team builder and the players' ratings increase? For example, Brice Wembangomo had scores around 300 and now he has 396 Expand
Yes, I had to review the initial formula, as it was too simplistic. I just pushed an update for the Team Builder. Can you please check?
cadoni said: You are welcome! Question: Sometimes, the player in range scouting showing inside the game a range. For example 9-13. Usually the "correct" attribute is in the middle (ie. 11). How the tool translate that? What value does it take? Expand
This should work too now, based on my explanation earlier. Can you please test it?
Kamas1 said: Hi, great job but I have one question. when a player has two natural positions wb and fb it shows me only in the wb section, is there any way to fix this? Expand
Turns out I deployed earlier than expected, my plane got delayed. Can you please try again?
Kamas1 said: Hi, great job but I have one question. when a player has two natural positions wb and fb it shows me only in the wb section, is there any way to fix this? Expand
Thank you for catching that! That is a bug. I will have to look into it. Should be fixed when I deploy again, probably end of this week.
cadoni said: You are welcome! Question: Sometimes, the player in range scouting showing inside the game a range. For example 9-13. Usually the "correct" attribute is in the middle (ie. 11). How the tool translate that? What value does it take? Expand
Funny you should ask that, as I had been working on just that yesterday. The update isn't ready yet, but the calculation I used now is as such:
Masked attributes (-) are defaulted to an 8, because that's what auto-generated players get in the game. Imho, it's fine that a player would have an inflated or deflated score, if he's far way from the 8, and is unscouted, because that's the point of scouting: to zero-in on the correct ability.
For semi-masked attributes (9-13), the formula is (min+max)/2 and then rounded, 9-13 would indeed be 11, but 5-12 would be 9.
---
For the formulas I have now made some adjustments, because I noticed that the outfield attributes are for 10 outfield players, while the goalkeeper is a single player.
So the formula goes as such: Each attribute's impact is adjusted to reflect its effect for a single player over one season (dividing by 10 for outfield players, as the original data measures team-wide results). It's then scaled based on how much the player's attribute exceeds the average baseline of 8 (up to 20), using: contribution = (adjusted_impact * (attribute_value - 8) / 12).
These contributions are summed to estimate the extra league points the player adds per season. To represent the total impact as observed in FM-Arena's extensive testing (equivalent to about 63 seasons from 2400 simulated matches), the seasonal total is multiplied by a scaling factor adjusted for position: around 24 for outfield players (accounting for shared team effects) and 3.5 for goalkeepers (reflecting their solo role and test variability). This provides a cumulative score aligned with the full test data.
So a Brazilian second division striker might add about 10 extra points per season, scaling to around 249 cumulatively, while a brazilian second division goalkeeper, adding a similar 10 per season, scales to about 37.
The formula feels off somehow still, so if anyone has a better recommendation on how to aggregate the numbers, I am more than happy to put that formula in.
cadoni said: Amazeballs! Thank you for creating and sharing such a tool! You can include a donation button, in order to help with maintain the cost; if you want. Expand
Thank you! I hadn't thought about that, but sure! Any little bit would help
BaZuKa said: could you make a calculator for overall attributes? excluding corners, free kick taking, long throws and penalty Expand
I don't know that I understand what you mean? The calculator is based on the results of the attribute tests on page 1 of this thread.
I suppose I could add all abilities to the Attribute Settings, and you can set your own impact values.
I'm also wondering where to store formations, as all the data just lives in the browser atm, but I figured it could be interesting to allow the community to upload formations & impact values, and you just select the predefined one from a list, based on upvotes or so.
Just so the tool can evolve on its own without my interference.
That said, I'd prefer to collect feedback in the other thread, as to not hijack this one. I feel that would be unfair to the people who put in the amazing work that made the calculator possible.
So I decided to create a calculator that just tells me which player/players to put on the field/buy.
What the calculator does: It aggregates the points, goals, goals conceded into a single score, akin to the 5 star system the game provides. So the highest rated player in the table should always be the best player.
Once you downloaded the views, you can use the print feature in FM24 to export a Web Print of the table. I recommend you name the exports as such to remember which one goes where, or the application might not be able to read the information correctly: "squad_data.html" "scouted_player_data.html" "players_in_range_data.html"
Once it's uploaded, you can click on the player and get a pareto chart along with their attributes.
Perhaps it's best you play around a bit with it and let me know what works and what stinks, or if you find any bugs.
The tool still has a few bugs to iron out, and I'm traveling for work right now, but I will do my best to get it uploaded by the end of this week so you can give it a try.
I built a calculator based on these results. So far it's only on my local machine, and I'm unsure whether to upload it somewhere.
You use a specific Squad & Scouting view, then use Print Screen -> Web Page It then calculates an aggregate score for each player based on this formula and the values in the screenshot below:
While a lot of these attributes do account for match wins for the team, I also wonder how it impacts the player's transfer value.
In my mind, most players are trained so as to be sold for the highest possible transfer value. Some of that comes by boosting their reputation, but some of it is relative to their CA, no?
Does the actual CA distribution impact the transfer value?
I'm looking into setting up personalized tests for FM24 tactics and player attributes. Does anyone here have or know of a Docker container image for this? Would love to get my hands on one for some streamlined testing.
harvestgreen22 said: I have a different take on this test result, As I mentioned above, " Note that the difference between attributes is only used to show the degree of differentiation and cannot be used for direct quantified comparisons.(Because it's not standardized) . For example, "difference from the standard value +40" is not twice as useful as "difference from the standard value +20" . " This result is not "standardized." For example (hypothetical) a +40 attribute can be three times more important than a +20 attribute And a attribute of -40 is three times worse than an attribute of -20 attribute
that means , Ignore the Work rate, Paceand Acceleration have an amazing 171 and 161, which means that the importance of physical attributes is not limited to 61.47% in the picture, the importance of physical attributes must be much greater than 61.47% Expand
I feel the focus might be too much on identifying the "best attributes" for enhancing performance. However, the significant negative impact of attributes like Work Rate at 1 underscores the importance of avoiding negative attributes just as much as maximizing positive ones.
Consider this hypothetical scenario: If everyone on the team has a Work Rate below 5, attributes like 20 in Acceleration and Pace could become irrelevant. It's like having a team of Usain Bolts who prefer to chat rather than run because they find the effort tedious. This principle likely applies to other attributes as well.
Here's how I think about it:
- Any attribute that pulls your team's performance below the control group's 20.1 goal difference is critical to consider.
The sequence of attribute impact might work like this (and it's how I would design such a system):
1. Decision Check: First, the game checks if the player decides to act or not. 2. Off-the-Ball Intelligence: Then, it determines if the player knows where to move. 3. Pace and Acceleration: These attributes determine how quickly they can get to that position. 4. First Touch: Checks if the player can control the ball when they receive it. 5. Dribbling: Decides how effective the player is with the ball in terms of movement. 6. Agility and Balance: These determine how well the player can avoid being tackled or recover if they are. 7. Vision and Decision: Another check to see if the player chooses to shoot or pass. 8. Type of Action: Decides the specifics of the pass or shot. 9. Shot Outcome: If shooting, this is measured against the goalkeeper's attributes to see if a goal is scored.
Each of these steps would be influenced by the relative attributes of the players involved, not just the absolute values. For instance, if all players had 20 in Acceleration and Pace, the value of these attributes would diminish because it's the differential between players that matters, not the absolute attribute itself.
It's also crucial to distinguish whether an attribute is more relevant for the interaction between players (like a striker versus a defender) or for the individual's own performance metrics (like shooting accuracy).
Means I won't be able to do it on the fly, and I can't make it language agnostic without larger changes.
I might be able to adjust the parser.
Would be awesome if you could ZIP them and send the HTMLs to me in a DM.
For me, I took MAN (Brazilian Third Division).
Tactic: PERFECT STRANGERS
Training: Quickness+2MatchPractice+1Attacking+7xRecovery + Individual Quickness
I filtered my transfers for 0 Value + Interested in loan.
We won the Brazilian Cup vs FLA and got promoted to the Second Division.
Our finances are solid, upgraded everything that they'd let me upgrade, except the stadium.
We're currently in the Copa Libertadores Second Round.
We scored 69 goals in the Second Division, and we're smashing all the Player Stats, where two of my best strikers are making 375$ p/w and 160$ p/w
Awesome! Let me know if you find something else
Yes, I had to review the initial formula, as it was too simplistic.
I just pushed an update for the Team Builder. Can you please check?
This should work too now, based on my explanation earlier.
Can you please test it?
when a player has two natural positions wb and fb it shows me only in the wb section, is there any way to fix this?
Turns out I deployed earlier than expected, my plane got delayed.
Can you please try again?
I do not have information to calculate that.
If someone can provide the formula to calculate it, then I would be glad to add that feature.
when a player has two natural positions wb and fb it shows me only in the wb section, is there any way to fix this?
Thank you for catching that!
That is a bug. I will have to look into it.
Should be fixed when I deploy again, probably end of this week.
Funny you should ask that, as I had been working on just that yesterday. The update isn't ready yet, but the calculation I used now is as such:
Masked attributes (-) are defaulted to an 8, because that's what auto-generated players get in the game. Imho, it's fine that a player would have an inflated or deflated score, if he's far way from the 8, and is unscouted, because that's the point of scouting: to zero-in on the correct ability.
For semi-masked attributes (9-13), the formula is (min+max)/2 and then rounded, 9-13 would indeed be 11, but 5-12 would be 9.
---
For the formulas I have now made some adjustments, because I noticed that the outfield attributes are for 10 outfield players, while the goalkeeper is a single player.
So the formula goes as such:
Each attribute's impact is adjusted to reflect its effect for a single player over one season (dividing by 10 for outfield players, as the original data measures team-wide results). It's then scaled based on how much the player's attribute exceeds the average baseline of 8 (up to 20), using: contribution = (adjusted_impact * (attribute_value - 8) / 12).
These contributions are summed to estimate the extra league points the player adds per season. To represent the total impact as observed in FM-Arena's extensive testing (equivalent to about 63 seasons from 2400 simulated matches), the seasonal total is multiplied by a scaling factor adjusted for position: around 24 for outfield players (accounting for shared team effects) and 3.5 for goalkeepers (reflecting their solo role and test variability). This provides a cumulative score aligned with the full test data.
So a Brazilian second division striker might add about 10 extra points per season, scaling to around 249 cumulatively, while a brazilian second division goalkeeper, adding a similar 10 per season, scales to about 37.
The formula feels off somehow still, so if anyone has a better recommendation on how to aggregate the numbers, I am more than happy to put that formula in.
Thank you! I hadn't thought about that, but sure!
Any little bit would help
I don't know that I understand what you mean?
The calculator is based on the results of the attribute tests on page 1 of this thread.
I suppose I could add all abilities to the Attribute Settings, and you can set your own impact values.
I'm also wondering where to store formations, as all the data just lives in the browser atm, but I figured it could be interesting to allow the community to upload formations & impact values, and you just select the predefined one from a list, based on upvotes or so.
Just so the tool can evolve on its own without my interference.
That said, I'd prefer to collect feedback in the other thread, as to not hijack this one. I feel that would be unfair to the people who put in the amazing work that made the calculator possible.
https://fm-arena.com/thread/15561-player-attribute-calculator-aggregator/
Cheers for testing!
I'll have to look into that when I'm back.
It should work with this link though: https://fmarenacalc.com/
https://fm-arena.com/thread/15561-player-attribute-calculator-aggregator/
Alas, I will be traveling again next week, but I'll check as often as I can.
https://fm-arena.com/thread/14009-attribute-testing-football-manager-24
So I decided to create a calculator that just tells me which player/players to put on the field/buy.
What the calculator does:
It aggregates the points, goals, goals conceded into a single score, akin to the 5 star system the game provides. So the highest rated player in the table should always be the best player.
Most of the information you'll find in the getting started page here:
https://fmarenacalc.com/
Once you downloaded the views, you can use the print feature in FM24 to export a Web Print of the table. I recommend you name the exports as such to remember which one goes where, or the application might not be able to read the information correctly:
"squad_data.html"
"scouted_player_data.html"
"players_in_range_data.html"
Once it's uploaded, you can click on the player and get a pareto chart along with their attributes.
Perhaps it's best you play around a bit with it and let me know what works and what stinks, or if you find any bugs.
The tool still has a few bugs to iron out, and I'm traveling for work right now,
but I will do my best to get it uploaded by the end of this week so you can give it a try.
You use a specific Squad & Scouting view, then use Print Screen -> Web Page
It then calculates an aggregate score for each player based on this formula and the values in the screenshot below:
const normalizedValue = Math.max(8, Math.min(20, value));
const impactRatio = (normalizedValue - 8) / 12; // 0 to 1 ratio
totalScore += impacts[calculatorKey] * impactRatio;
I also wonder how it impacts the player's transfer value.
In my mind, most players are trained so as to be sold for the highest possible transfer value. Some of that comes by boosting their reputation, but some of it is relative to their CA, no?
Does the actual CA distribution impact the transfer value?
I'm looking into setting up personalized tests for FM24 tactics and player attributes. Does anyone here have or know of a Docker container image for this? Would love to get my hands on one for some streamlined testing.
Thanks in advance
As I mentioned above,
"
Note that the difference between attributes is only used to show the degree of differentiation and cannot be used for direct quantified comparisons.(Because it's not standardized) . For example, "difference from the standard value +40" is not twice as useful as "difference from the standard value +20" .
"
This result is not "standardized."
For example (hypothetical)
a +40 attribute can be three times more important than a +20 attribute
And
a attribute of -40 is three times worse than an attribute of -20 attribute
that means ,
Ignore the Work rate,
Paceand Acceleration have an amazing 171 and 161,
which means that the importance of physical attributes is not limited to 61.47% in the picture,
the importance of physical attributes must be much greater than 61.47%
I feel the focus might be too much on identifying the "best attributes" for enhancing performance. However, the significant negative impact of attributes like Work Rate at 1 underscores the importance of avoiding negative attributes just as much as maximizing positive ones.
Consider this hypothetical scenario: If everyone on the team has a Work Rate below 5, attributes like 20 in Acceleration and Pace could become irrelevant. It's like having a team of Usain Bolts who prefer to chat rather than run because they find the effort tedious. This principle likely applies to other attributes as well.
Here's how I think about it:
- Any attribute that pulls your team's performance below the control group's 20.1 goal difference is critical to consider.
The sequence of attribute impact might work like this (and it's how I would design such a system):
1. Decision Check: First, the game checks if the player decides to act or not.
2. Off-the-Ball Intelligence: Then, it determines if the player knows where to move.
3. Pace and Acceleration: These attributes determine how quickly they can get to that position.
4. First Touch: Checks if the player can control the ball when they receive it.
5. Dribbling: Decides how effective the player is with the ball in terms of movement.
6. Agility and Balance: These determine how well the player can avoid being tackled or recover if they are.
7. Vision and Decision: Another check to see if the player chooses to shoot or pass.
8. Type of Action: Decides the specifics of the pass or shot.
9. Shot Outcome: If shooting, this is measured against the goalkeeper's attributes to see if a goal is scored.
Each of these steps would be influenced by the relative attributes of the players involved, not just the absolute values. For instance, if all players had 20 in Acceleration and Pace, the value of these attributes would diminish because it's the differential between players that matters, not the absolute attribute itself.
It's also crucial to distinguish whether an attribute is more relevant for the interaction between players (like a striker versus a defender) or for the individual's own performance metrics (like shooting accuracy).