1. Introduction
In this experiment we will check impact of selected hidden attributes and Determination on team performance in a domestic league measured by team's points earned over the course of a season. This experiment is a continuation and improvement of my previous research of that case made in FM21 that can be viewed here.
2. Game setup and testing environment
In this experiment I've decided to load only 1 playable league that was English Premier League. The team of my choice was Leeds United. The idea to take Leeds came from one of the comments about my previous experiment where I've chosen Liverpool FC, that their good and best performance was indistinguishable simply because the margin of error at the high end of the points gained was very little and the team just couldn't perform better. I've checked the multiple simulations that Knap made to check his tactics and it turned out that Leeds is a team that in most cases ends up somewhere mid table. This results in a room for potential positive and negative impact of attributes change to be still visible in results. Other things that were set for the experiment:
all first team players attributes that were tested (Ambition, Pressure, Professionalism, Temperament, Consistency, Important Matches and Determination) were set using in game editor and then their attributes were locked preventing their changes throughout experiment
attributes were set to default, all 10's (kind of control group - all the tested attributes, not all the player's attributes), selected attribute set as 1 (low), selected attribute set as 20 (high)
option preventing player manager to be sacked was enabled
individual and team training was designated to assistant manager
match squad selection was left to assistant manager
all contract and transfer features were designated to player manager so there was no players coming in or out during the test
first transfer window was disabled to reduce personal shuffle in other teams in the league
testing time was 1 season (earliest possible starting date in England ; ending date just after the last fixture of the season)
only 1 playable league was enabled (English Premier League) and all competition that Leeds United was not participate match details was set to 'None' to reduce processing time
tactic that was used in all simulations was @knap's KASHMIR 451 P104 EC FA (THP93)
game version was 22.4.1
database version was default 22.4.0 database update
As our outcome value we will use amount of points that team gathered in domestic league during the whole season. Final result is shown as average number of points for that data set and as additional feature there will be indicator to show the spread of points gained within certain data set.
Every attribute set was simulated 7 times. Attributes sets that were tested:
Default [Ambition - 12,88 ; Pressure - 12,68 ; Professionalism - 14,08 ; Temperament - 12,36 ; Consistency - 11,48 ; Important Matches - 12 ; Determination 14,16] - default players attribute values (numbers in brackets are first team average)
All 10 - control group
Ambition 1
Ambition 20
Pressure 1
Pressure 20
Professionalism 1
Professionalism 20
Temperament 1
Temperament 20
Consistency 1
Consistency 20
Important Matches 1
Important Matches 20
Determination 1
Determination 20
3. Results
3.1 Overall results in a table
3.2 Average domestic league points (result spread is the lowest and the highest number of points in single simulation for certain attribute value)
3.3 Results difference compared to All 10 (control group)
4. Analysis
The first thing that is clearly visible is almost 50% drop in performance for very low Pressure and Professionalism values. On the other hand positive difference for high end values for those attributes is not that significant (5,6% and 10,18%). In general we can observe that every single attribute produced lower result when set to 1 when compared to control group. This shows that each tested attribute influences player's performance on the pitch. For the high end values the highest team improvement occurred for Determination, Pressure and Consistency (12,27%, 10,18% and 9,16% respectively). High Ambition and Important Matches did not produce significantly better results than control group but when those attributes were set to low the performance drop was visible (-9,41% and -6,36%). The most interesting result was Temperament that when set to high produced significantly lower result than low value (-8,91% compared to -15,52%).
5. Conclusion and free thoughts
Experiment showed that players should have at least medium range values for Pressure and Professionalism otherwise their negative impact on player's performance is significant. The positive impact of all of the tested attributes was much lower for high values than the negative impact for low values (except Temperament). High Temperament value resulting in a worse outcome than low temperament value might indicate that very high value for this attribute is not desired. However this observation requires further investigation because it's requirement for some player's personalities considered as desired and positive like Model Citizen/Professional or Spirited might indicate that this attribute should be considered as positive.
It is unclear whether 10 is an absolute neutral value or it's relative on the league average which was not calculated in this experiment. This also applies to checking if performance drop due to low Pressure/Professionalism would still be this high in a league with different average value for those attributes.
There was no clear tendency for final number of points spread within certain attributes data sets. Very interesting factor was high spread of result between certain seasons within the same data set - for example for 20 Pressure there was final result of 33 points and 76 points in a two consecutive simulations. There were no investigation for any specific reason behind that big gap between results (like for example injury of key player) but it's worth noticing that number of simulations for future tests should be as high as possible due to significant spread of end results within the same datasets.
Some players despite having 1 or 20 in Important Matches and Consistency did not show this as Pros/Cons indicator in scouting/coaching report even after full season. It behaved the same way every time for the same players in both cases, so for high/low value and both for consistency/important matches. Reason is unknown but is worth noticing in terms of scouting for players with certain values of those hidden attributes that cannot be obtained in any other way without the editor or 3rd party tools.
I hope this experiment clarified some questions and also revealed some unexpected aspects of attributes. Any questions or comments are welcomed.
Spreadsheet for those interested in detailed numbers