Jump to content

Orion_

Members+
  • Posts

    168
  • Joined

  • Last visited

Reputation

67 "Houston, we have a problem"

Currently Managing

  • Currently Managing
    Polonia Warszawa

Recent Profile Visitors

The recent visitors block is disabled and is not being shown to other users.

  1. It's hard to tell since I haven't checked it for value 15 but as you can see in the graph when comparing the control group of 'all 10s' with Pressure 1 there was almost -50% drop in points and similar value for the 1 Professionalism while 20 Pressure and Professionalism had +10% and +5% respectively impact on points gain so general rule of thumb I'd say that at least for top 5 leagues the 'optimal minimum' would be said 10 and everything above this doesn't have that much of an impact on points gained. If you play in smaller leagues/countries it would require additional testing but my assumption would be that the bar is lower there - just like with any other attributes. I can't say for sure simply because we are lacking for example a distribution of Pressure and Professionalism among players in different leagues but again if we assume that the distribution of those attributes follows the difference in 'visible attributes' - so in better leagues the hidden attributes have also on average higher values. Again sorry to say that it's all assumptions and 'ifs' but sadly we can't rely on any data in this matter due to lack of testing. Attributes in general mean anything in relation to your opposition so it all comes to your league level.
  2. Good to see this proved again. Reminds me of an experiment when some guy won Prem with West Ham making all players artificially 1CA/PA and manually selecting their attributes to fit this CA/PA. Those player were also very physical - I even think he played strikerless formation due to strikers consuming a lot of CA for Acc/Pace while for other positions it was not (so he could make players with high physical attributes that were still 1CA). On the other hand it somehow reflects current football trends where top players are not only good from the technical side of the game but are also exceptional athletes.
  3. You're talking about 'Sportsmanship' not 'Temperament' but interesting point of view. I didn't think that way and removed Sportsmanship from the test to reduce processing time.
  4. I'm not an expert but my bet would be games against rivals and cup games. I agree with your statement. That's one possible explanation why for Leeds Important Matches didn't matter. They we're expected to finish mid table so if they were not fighting against relegation no league games were 'Important' maybe except some historical rivals like United? I haven't checked what rivals Leeds has in the game right now. I thought about this too but according to what we have in data it looks like high temperament gives worse results. It may be just bad luck due to small sample size but even if we do not count the highest and the lowest results it's still in significant favour towards Temp1 (~51 vs 47 points).
  5. Is there any particular reason why some roles like Complete Forward/Roaming Playmaker/Regista/Raumdeuter etc. have certain CA threshold until player appear as suitable for them? I get that star rating is not that important (I know it's only selected staff opinion about player) but why can't we get 'regular' rating of a player for those roles? We know that even lower league players can play those roles. They probably won't produce such a numbers as world top players but can still perform ok. For example I had some success in lower leagues playing for example Regista. Why we rob lower league experience from using those roles? I know that I can play players in those roles anyway but comparing them becomes a little bit harder when all of your squad, no matter the actual difference in player's quality, is rated 0,5 star in certain roles.
  6. 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
  7. It would be nice to have possibility of having bigger view for 'Edit search' windows in scouting view. Here's the picture how it looks right now in wqhd resolution: The windows does not resize itself in different resolution settings. Even thou I use wqhd resolution I'm unable to see more than 2 additional conditions at the time which looks just very bad when you want to have more conditions in your filter. Well you can say 'just go to 'advanced' tab and everything will be fine'. Technically yes but on the other hand if I add any attribute related search filters it suddenly start looking like this: and it's still not very friendly when it comes to adding other conditions since any new condition will be added at the bottom of the list. I'd recommend resizing this pop-up window depending on overall window/screen resolution because right now it's just waste of all this free space that is left behind.
  8. The same way as scouts can give us a low/high consistency/important matches indicator why we only have high injury proneness indicator but no low injury proneness indicator in scouting report? This came to my mind when I saw one of my key players having 'Injury susceptibility' in medical report as 'Very low'. Why this isn't listed in scouting report in his pros while if a player has high injury proneness it's listed in his cons.
×
×
  • Create New...