Jump to content
Sports Interactive Community
Stegthomson

Determination and Player Personality

What influences player development?  

37 members have voted

  1. 1. What influences player development?

    • Player Personality
    • Determination stat


Recommended Posts

I have seen this many a time and wondering if there is an official SI response to the theory of Determination has no influence of player developments?

I have read many times it's soley down to player personality and Tutoring changes this...

Another thing that would be handy is an official article on training.

Thanks

Share this post


Link to post
Share on other sites

Moved this to the Tactics and Training forum. IIRC, Ambition and Professionalism are the two traits that influence player development. Game time is also needed, of course.

I know that Determination has no effect on development.

Share this post


Link to post
Share on other sites

I was under the impression that Determination is a key factor & maybe is in fact the most influential factor in player development.

I can see why the OP is unsure.

Share this post


Link to post
Share on other sites

Determination can be a good indicator that a player has a decent personality, but not always. In pure development terms, it means nothing.

Share this post


Link to post
Share on other sites

Cleon has it all listed here http://community.sigames.com/showthread.php/380395-Ajax-When-Real-Life-Meets-Football-Manager-FM14 - skip down to posts 10-13 for all the detail on training and tutoring.

Basically, Determination has nothing to do with player development. It's pretty much all about Personality (the more professional the better) and game time. Post 13 lists all the player personalities.

Share this post


Link to post
Share on other sites

Hmm, I'd like to know how those opinions/observations were arrived at. Will have a read of that thread when I get the time.

Share this post


Link to post
Share on other sites
Hmm, I'd like to know how those opinions/observations were arrived at. Will have a read of that thread when I get the time.

They came from Riz a while back.

Share this post


Link to post
Share on other sites

As he coded that area of the game I'll take the intent at face value however my testing nature would not take it as meaning that's how it actually works in game, never really tested that area for myself as it takes a lot of time to build up a sample large enough to factor out random variables .

Might take a closer look when FM16 is out.

Share this post


Link to post
Share on other sites

Its fairly simple to recreate or create a test to see for yourself. The hardest bit if the amount of time you need to sim the game.

Share this post


Link to post
Share on other sites
Its fairly simple to recreate or create a test to see for yourself. The hardest bit if the amount of time you need to sim the game.

No need to do that, check http://www.thedugout.net/content/articles/item,1,2,1,Player_Development_and_Tutoring_Guide.html

Im fairly sure that things haven't changed much since 2011. This test is only based on determination and professionalism.

Share this post


Link to post
Share on other sites
As he coded that area of the game I'll take the intent at face value however my testing nature would not take it as meaning that's how it actually works in game, never really tested that area for myself as it takes a lot of time to build up a sample large enough to factor out random variables.

A while back I pulled some regen data, to look at exactly this issue. This is data from a long-term save, looking at the progress of three years of regens over a period of 10 years. All regens (total of 168) started their careers at a Premier League club, and after the 10 years were at a club somewhere in the top six leagues in England. The regens were from 2015, 2016, and 2017. They were evaluated in 2025, 2026, and 2027 respectively. For each regen, I have their Det, all hidden attributes, starting CA, ending CA, and PA.

Take a look, the spread-sheet is here: https://docs.google.com/spreadsheets/d/14Rva5yIJWaXGqKZpq_V2r21VEPyEb6aYHXX7HX-Payc/edit?usp=sharing

I'm not a statistician, but I have a copy of R and some time on my hands, so I've taken a stab at doing some analysis. I've calculated how much each regen increased their CA, scaled by how much they *could* have increased. Then I ran a multivariate regression on the hidden attributes plus Det against the percentage increase.

Here's what R spat out:

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.2919795  0.1424770  -2.049 0.042140 *  
Det          0.0168426  0.0042602   3.953 0.000117 ***
Prof         0.0360109  0.0051025   7.057 5.53e-11 ***
Amb          0.0221242  0.0045349   4.879 2.66e-06 ***
Cont         0.0019950  0.0049314   0.405 0.686372    
Ada          0.0059487  0.0043033   1.382 0.168879    
Cons         0.0050925  0.0050956   0.999 0.319186    
Dirt         0.0004178  0.0043732   0.096 0.924006    
Imp.M       -0.0007775  0.0039183  -0.198 0.842971    
Inj.Pr      -0.0291618  0.0040486  -7.203 2.50e-11 ***
Loy          0.0052854  0.0044698   1.182 0.238858    
Pres        -0.0007325  0.0054872  -0.133 0.893976    
Spor        -0.0052793  0.0045982  -1.148 0.252715    
Temp         0.0066179  0.0049603   1.334 0.184131    
Vers         0.0054448  0.0054712   0.995 0.321217    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.1778 on 153 degrees of freedom
Multiple R-squared:  0.542,     Adjusted R-squared:    0.5 
F-statistic: 12.93 on 14 and 153 DF,  p-value: < 2.2e-16

The attributes flagged with *** are the significant ones, all the others are irrelevant. So Prof, Injury Proneness, Amb, and Det all have an effect on player development (in that order of importance). We're looking for high Prof, Amb, and Det, and low Inj Proneness.

Prof, Amb, and Injury Proneness work exactly as expected, but Det is a surprise. Based on earlier posts in this thread, and everything else I've read, I would not expect Det to have an effect.

Looking for an explanation, I noticed that there is a second order effect between Det and Injury Proneness. If we add this to the model (and get rid of all the un-interesting attributes), we get the following:

Residuals:
    Min       1Q   Median       3Q      Max 
-0.43410 -0.11319  0.00871  0.11658  0.47862 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.250665   0.160709   1.560  0.12077    
Det         -0.006877   0.009671  -0.711  0.47805    
Prof         0.036871   0.004676   7.886 4.36e-13 ***
Amb          0.022405   0.004328   5.177 6.60e-07 ***
Inj.Pr      -0.068780   0.013863  -4.961 1.75e-06 ***
Det:Inj.Pr   0.002979   0.001009   2.952  0.00363 ** 
---
Signif. codes:  
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.1736 on 162 degrees of freedom
Multiple R-squared:  0.5374,    Adjusted R-squared:  0.5232 
F-statistic: 37.64 on 5 and 162 DF,  p-value: < 2.2e-16

What this tells us is that Injury Proneness, Prof, and Amb are still significant, but Det is no longer considered significant. Rather, the interaction between Det and Injury Proneness (labeled Det:Inj.Pr) is significant.

What this *might* mean is that Det mitigates the effect of Injury Proneness. In game terms, perhaps a high Det modifies the probability that an injury will occur, representing the willingness of a player to "play through the pain". This would mean that a high Det regen would gain valuable playing time compared to his low Det counterpart.

So, if you want to improve a your regens chances of reaching their full potential, this data suggests doing the following:

  • Prioritize high Professionalism;
  • Focus on regens with low Injury Proneness;
  • Prioritize high Ambition, but not at the expense of high Professionalism;
  • If you have an Injury Prone regen, prioritize high Determination.

Share this post


Link to post
Share on other sites

Very neat, especially with investigating the Determination*Injury Proneness interaction. I'd also wonder if Adaptability might have some input that is masked by this sample of regens who stay within their country of origin?

Share this post


Link to post
Share on other sites
A while back I pulled some regen data, to look at exactly this issue. This is data from a long-term save, looking at the progress of three years of regens over a period of 10 years. All regens (total of 168) started their careers at a Premier League club, and after the 10 years were at a club somewhere in the top six leagues in England. The regens were from 2015, 2016, and 2017. They were evaluated in 2025, 2026, and 2027 respectively. For each regen, I have their Det, all hidden attributes, starting CA, ending CA, and PA.

So you compiled the data by letting them loose in the wild, with the AI managing them? They'll have varying levels of involvement in matches and so on. The variables here cannot be ignored and so your results are flawed.

As said before, determination has no effect on development. Injury proneness only indirectly affects development as injury prone players are more prone to injury, so won't train or play if injured. It doesn't affect development itself if they're not injured though.

Share this post


Link to post
Share on other sites
I'm not a statistician, but I have a copy of R and some time on my hands, so I've taken a stab at doing some analysis. I've calculated how much each regen increased their CA, scaled by how much they *could* have increased. Then I ran a multivariate regression on the hidden attributes plus Det against the percentage increase.

Did they all play the exact same minutes in a match? Remember that playing time is the biggest single factor in terms of getting players to develop once they have a good personality type.

I'm also interested to see how you handled event based development and incorporated that into your test as they are instant CA rises and don't come from personality, training or game time.

Share this post


Link to post
Share on other sites
Did they all play the exact same minutes in a match? Remember that playing time is the biggest single factor in terms of getting players to develop once they have a good personality type.

I'm also interested to see how you handled event based development and incorporated that into your test as they are instant CA rises and don't come from personality, training or game time.

If the sample size is large enough you can still get a statistically relevant result despite not accounting for other variables. That is the whole point of testing large populations. If you can take every variable into account you would only need groups of n=1. That said if you take minutes played and minutes played at senior level into account during the analysis that would greatly increase the chances of getting a statistically significant result with a smaller sample size.

Looking at his results Professionalism and Injury proness have the most significant impact which makes sense (we have all experienced the great benefits of professionalism in talents and an injured talent isn't going to progress). The smaller impact of determination can just be a case of the AI managers more readily playing youngsters with a high determination stat as they value the attribute in game or a determined regen being more likely to also have high professionalism. It doesn't mean there is a direct relationship between determination and player development.

Share this post


Link to post
Share on other sites
So you compiled the data by letting them loose in the wild, with the AI managing them? They'll have varying levels of involvement in matches and so on. The variables here cannot be ignored and so your results are flawed.

Unfortunately, my browser glitched while I was typing up my analysis, and I lost about half of it. When I re-wrote it, I left out a really important caveat. So here it is...

The R value of the regression model is about 50%. That means that this model "explains" about 50% of the variability in the increase in CA. The other 50% is due to factors that are not modeled, such as playing time, quality of opposition, quality of coaching, and other factors. Looking at it another way, this model describes the affect of Prof, Amb, Det, and Injury Proneness on development, assuming that all other factors are constant (on average).

I'm definitely not suggesting that when we play the game we should ignore these other factors. They are crucially important to development.

As said before, determination has no effect on development. Injury proneness only indirectly affects development as injury prone players are more prone to injury, so won't train or play if injured. It doesn't affect development itself if they're not injured though.

I agree, with one distinction. Based on the analysis, I would say that determination has no *direct* effect on development, but it does have an indirect effect. The Det*Inj.Pr term suggests that Det can modify the impact of Injury Proneness. And Injury Proneness, as you point out, has a clear indirect effect on development.

It is possible that both Det and Det*Inj.Pr are acting as a proxy variables for playing time, and that their significance would be reduced if playing time were added to the model. Unfortunately, extracting playing time data from the game is a bit tedious, which is why I omitted it from the model in the first place.

Share this post


Link to post
Share on other sites
Whats event based development?

A player scoring 3+ goals in a match, for instance, can get an immediate boost to CA.

Share this post


Link to post
Share on other sites
Unfortunately, my browser glitched while I was typing up my analysis, and I lost about half of it. When I re-wrote it, I left out a really important caveat. So here it is...

The R value of the regression model is about 50%. That means that this model "explains" about 50% of the variability in the increase in CA. The other 50% is due to factors that are not modeled, such as playing time, quality of opposition, quality of coaching, and other factors. Looking at it another way, this model describes the affect of Prof, Amb, Det, and Injury Proneness on development, assuming that all other factors are constant (on average).

I'm definitely not suggesting that when we play the game we should ignore these other factors. They are crucially important to development.

If you're looking at the overall picture, then yes, Inj Proneness has an indirect effect on development. Keep him injury free and it's no longer a problem. The point is, only game time, Ambition and Professionalism directly affect the rate of growth/development.

I agree, with one distinction. Based on the analysis, I would say that determination has no *direct* effect on development, but it does have an indirect effect. The Det*Inj.Pr term suggests that Det can modify the impact of Injury Proneness. And Injury Proneness, as you point out, has a clear indirect effect on development.

It is possible that both Det and Det*Inj.Pr are acting as a proxy variables for playing time, and that their significance would be reduced if playing time were added to the model. Unfortunately, extracting playing time data from the game is a bit tedious, which is why I omitted it from the model in the first place.

Determination is an attribute of no more significance than the other attributes. The test was very limited. Here's a theory, higher Balance (and maybe Agility) will see players get injured less often as he's better balanced to not get hurt in challenges or twisting awkwardly. I'm sure certain mental attributes will prevent him from getting into those situations in the first place, so they also affect development indirectly.

Share this post


Link to post
Share on other sites

I wouldn't rule out determination as a factor just because it doesn't fit with what Si have said should happen, a comparative test run with the attribute reduced to <5 for all players could provide a definitive answer.

Will take a closer look tonight & I'll be interested to see the development rate before the players turn 18 as playing time is not a factor until that age.

Share this post


Link to post
Share on other sites
Did they all play the exact same minutes in a match? Remember that playing time is the biggest single factor in terms of getting players to develop once they have a good personality type.

I'm also interested to see how you handled event based development and incorporated that into your test as they are instant CA rises and don't come from personality, training or game time.

A player scoring 3+ goals in a match, for instance, can get an immediate boost to CA.

Instanct CA increases from a single isolated event is news to me, I assume this has also been backed up with proven evidence?

Share this post


Link to post
Share on other sites
Instanct CA increases from a single isolated event is news to me, I assume this has also been backed up with proven evidence?

With all respect, training matters don't seem your strong point when it comes to FM, so it's no real surprise it might be news to you, compared to the other areas of the game you understand. If by having it confirmed by PaulC is classed as proven evidence then yes. It's been in the game since around 2007/8. If a player does something out of the ordinary compared to how he normally plays then he can see certain attributes rise instantly after the game. So for example if you had a midfielder who doesn't normally grab assists but in one game he somehow got 4 assists then he could see his passing or anticipation rise instantly by 1 visible attribute value and so on.

While its rare, if you play long enough and pay attention you can see this happen quite a few times during your stay at a club.

Share this post


Link to post
Share on other sites
With all respect, training matters don't seem your strong point when it comes to FM.
Which is why I'm asking the question.

Not sure I like the logic behind it, unless we're talking about a fraction of a single CA point in attribute development. Such a system must create a scenario where an exploitative tactic could/will have a double whammy of being able to boost attributes by putting players in a position that will increase the likelihood of high assist or goal numbers in a single match.

It also assumes that the system still exists nearly 8 years & a number of revamps later.

Share this post


Link to post
Share on other sites
Which is why I'm asking the question.

Not sure I like the logic behind it, unless we're talking about a fraction of a single CA point in attribute development. Such a system must create a scenario where an exploitative tactic could/will then have a double whammy of being able.

It also assumes that the system still exists nearly 8 years & a number of revamps later.

Why would it? It has to be something out of the ordinary for the player and not something he normally does.

Share this post


Link to post
Share on other sites

Edited my last post as it didn't correctly convey my thoughts when I read it back.

Corner & long throw exploit exploits spring to mind.

Share this post


Link to post
Share on other sites
Here's a theory, higher Balance (and maybe Agility) will see players get injured less often as he's better balanced to not get hurt in challenges or twisting awkwardly. I'm sure certain mental attributes will prevent him from getting into those situations in the first place, so they also affect development indirectly.

Interesting. It's relatively easy to extract the data to test that theory. I'll take a stab at it.

Share this post


Link to post
Share on other sites
Out of 17 votes so far, just one has voted 'Dermination stat'. I'd hate to be THAT guy. :D

:lol: Not sure what need for a poll; it is what it is. If 5000 users said Determination it wouldn't mean that it actuallymattered to development :)

Share this post


Link to post
Share on other sites
I didn't know that either. Very interesting. :thup:

Yeah, and it's cool when it happens. Have a young striker bang in a hat trick and look at finishing and composure possibly increase. Same as when you fine a player for a red card, you can see the aggression drop a point sometimes as well as what happens to the hidden stats like dirtiness.

Share this post


Link to post
Share on other sites
Yeah, and it's cool when it happens. Have a young striker bang in a hat trick and look at finishing and composure possibly increase. Same as when you fine a player for a red card, you can see the aggression drop a point sometimes as well as what happens to the hidden stats like dirtiness.

I find it fascinating too! Didn't know that! I only wonder if this can work the other way around. I mean that if a player does something out of the ordinary compared to how he normally plays then he can see certain attributes fall as well. For example a striker has a bad day at the office, hitting the woodwork 5 times in a match. After the match his composure and finishing will have fallen a point.

Share this post


Link to post
Share on other sites
I find it fascinating too! Didn't know that! I only wonder if this can work the other way around. I mean that if a player does something out of the ordinary compared to how he normally plays then he can see certain attributes fall as well. For example a striker has a bad day at the office, hitting the woodwork 5 times in a match. After the match his composure and finishing will have fallen a point.

I've not seen it where I noted specifically that an event was a cause of an attribute drop but I never thought to pay attention to it. You would think it would work that way, so I'll keep an eye and see if notice it in reverse :)

Share this post


Link to post
Share on other sites
Yeah, and it's cool when it happens. Have a young striker bang in a hat trick and look at finishing and composure possibly increase. Same as when you fine a player for a red card, you can see the aggression drop a point sometimes as well as what happens to the hidden stats like dirtiness.

Indeed, you can fine or warn every player who plays below a 6.4 rating. Warning him can increase his determination and/or workrate. Same for aggression, which drops a point every time you fine someone for 'violent behaviour' or any straight red card.

I have seen media handling style change after a red card. Player used to be volatile, then got a red card (warned him, since it was 2x yellow) and after he accepted his warning he got a "media friendly" as his media handling style.

Share this post


Link to post
Share on other sites
Interesting. It's relatively easy to extract the data to test that theory. I'll take a stab at it.

Not to hurry anyone but I'm kind of eager to see what your analysis of the data shows :)

-SnUrF

Share this post


Link to post
Share on other sites
Not to hurry anyone but I'm kind of eager to see what your analysis of the data shows :)

-SnUrF

Well, pulling the data proved to be more tedious than I'd expected, due to attribute masking. To simplify, I changed how I collected the data. Unfortunately, this introduced differences between the this data set and the previous one. These differences were quite big. For example, the model that explained 50% of the variance in the first data set only explains 30% of the variance in the second data set.

I'd planned to go back and really think through how to collect the data so as to eliminate collection biases. But then the FM16 Beta arrived, and I got... distracted. Actually, I doubt I'll go back now and re-do the data collection. We're stuck with this data, despite the dubious quality.

The theory we want to test is whether there are attributes that contribute to a player's development by affecting the amount of playing time he gets. Running a regression against all the attributes (visible and hidden) gives a model that explains 50-60% of the variance. I've pasted the full results below.

As before, we see Injury Proneness is the biggest factor. Second is Stamina. Both of these seem like they are contributing to the player's development by affecting playing time. Natural Fitness is also a factor, which is another attribute that should affect playing time.

So, this seems to supports HUNT3R's theory that there are attributes that appear to contribute to player development, but in fact only do so indirectly, by affecting playing time.

And it interesting to note that Det is no longer a large contributing factor. It *may* be a proxy for playing time, but not to the degree that Injury Proneness, Stamina, and Natural Fitness are.

Seems to me we really need playing time data as part of this analysis. Which is really hard to get in an easily automated fashion.

Here's the data in full...

             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -6.216e-02  1.545e-01  -0.402  0.68800    
Prof         7.744e-03  3.486e-03   2.221  0.02784 *  
Amb          3.267e-03  3.407e-03   0.959  0.33918    
Inj.Pr      -1.635e-02  2.990e-03  -5.468 1.89e-07 ***
Cor          1.125e-02  4.611e-03   2.439  0.01590 *  
Cro          2.848e-03  3.589e-03   0.794  0.42874    
Dri         -7.161e-03  4.555e-03  -1.572  0.11808    
Fin         -1.973e-03  4.271e-03  -0.462  0.64476    
Fir         -9.463e-03  5.990e-03  -1.580  0.11629    
Fre          2.621e-03  4.356e-03   0.602  0.54835    
Hea         -4.877e-04  3.393e-03  -0.144  0.88589    
Lon          4.271e-03  4.027e-03   1.061  0.29063    
L.Th        -9.762e-04  3.665e-03  -0.266  0.79031    
Mar         -1.738e-03  4.832e-03  -0.360  0.71960    
Pas          2.526e-03  4.407e-03   0.573  0.56742    
Pen          1.559e-03  3.850e-03   0.405  0.68610    
Tac          6.974e-03  5.493e-03   1.270  0.20621    
Agg         -8.365e-04  2.560e-03  -0.327  0.74431    
Ant          1.011e-03  4.222e-03   0.240  0.81104    
Bra          1.331e-04  2.270e-03   0.059  0.95332    
Cmp          9.614e-03  4.540e-03   2.117  0.03590 *  
Cnt         -2.486e-03  4.468e-03  -0.556  0.57873    
Dec          3.370e-04  5.165e-03   0.065  0.94807    
Det         -1.628e-03  3.385e-03  -0.481  0.63118    
Fla          5.351e-03  3.626e-03   1.476  0.14220    
Ldr          4.586e-05  2.799e-03   0.016  0.98695    
OtB          9.063e-03  4.709e-03   1.925  0.05620 .  
Pos          7.134e-03  5.885e-03   1.212  0.22737    
Tea         -3.161e-03  3.586e-03  -0.882  0.37939    
Vis         -1.404e-02  4.879e-03  -2.879  0.00459 ** 
Acc          1.161e-02  4.750e-03   2.444  0.01569 *  
Agi          1.835e-03  6.057e-03   0.303  0.76241    
Bal          4.905e-03  4.346e-03   1.129  0.26087    
Jum         -3.353e-04  3.639e-03  -0.092  0.92672    
Nat          9.385e-03  4.001e-03   2.346  0.02033 *  
Pac          3.912e-03  6.473e-03   0.604  0.54654    
Sta          1.802e-02  5.152e-03   3.498  0.00062 ***
Str          9.417e-03  5.968e-03   1.578  0.11675    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.1153 on 148 degrees of freedom
Multiple R-squared:  0.609,     Adjusted R-squared:  0.5113 
F-statistic: 6.231 on 37 and 148 DF,  p-value: 3.447e-16

Share this post


Link to post
Share on other sites

I've always thought Determination played a minor role in player development, but professionalism has always been the main one, and I'm fairly certain Ambition helps as well. I tended to have it pegged at roughly 60/30/10 for Professionalism, Ambition and Determination respectively, but looking at the experiment data, it's probably two thirds professionalism and one third Ambition. Put it simply, personalities with high professionalism (fairly professional, professional, model professional, resolute, perfectionist) and that player should have not problems developing provided he gets game time.

Share this post


Link to post
Share on other sites

Join the conversation

You can post now and register later. If you have an account, sign in now to post with your account.

Guest
Reply to this topic...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.


  • Recently Browsing   0 members

    No registered users viewing this page.

×
×
  • Create New...