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Projecting a Player Life Cycle...

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Rhythm FC (MMM) 28 November 2018, 18:50
Just a little series im going to be putting together to help people understand VM a little better. Some of you might already know this stuff but the next few installments will definitely give you a better idea of some of the fiddly bits of this game

I’m going to assume most of you know the basics of Training Scores, Rating calculations and Abilities on Virtual Manager so I’m not going to waste time blurting on about the basic stuff.
This article will be mainly based on what a player’s life cycle actually looks like on Virtual Manager.
We know that once a player reaches 28-29yo his stats start to decline. The older the player gets the more his stats decline every day. In addition, we also know that the player’s training scores are begin to decline in a similar way. But with this information what we don’t know is how the decline affects players.

So, let me shed some light on this for you…

Firstly, let’s look at what a player’s total abilities profile looks like in accordance with their age and training scores. This is factoring in decline in stats and training scores once the player is old enough. The age is decimal meaning 25 corresponds to when a player is 25.0 years old or 25(29) as displayed on VM. Training Scores are average and correspond to a player’s training score under non-decline conditions. Also, worth noting is that the higher a player’s stat, the more XP it takes to increase the stat further and this ranges from 50XP for 0 stat to 201XP for 100 stat.
Anyway, factoring everything in this is what an abilities profile looks like (using a few clever equations) and you can check this against what you can see on player’s training pages.



And in chart format it looks like this:



For the most part we can see that a player’s Total Abilities peak happens at roughly 31 years old and there is an exponential decline past that stage, due to decline in abilities and training scores (also noting decline in stamina->energy->training intensity). You can see that the lower the training score the flatter the curve which is to be expected.

But this is all information you kind of knew already. The real meat of this is how we can apply this to model a player’s rating over the course of his life cycle.

Let’s assume a player is trained ‘well’. This is not a training article so I’m not going to bother explaining what a ‘well’ trained player looks like but there’s plenty of information out there for you to get a good picture of what I’m talking about.

The only other thing worth noting for what I’m about to show you is that this is modelling a Forward. The models for most outfield positions would look fairly similar anyway, just Midfielders who’s rating curves would be flatter due to the way their rating calculations work out. We’ll talk about how to deal with that later

Again, here are the figures:



And here’s the chart for good measure:



Firstly we can see that the these charts look a lot like the charts for Total Abilities and that’s obviously because the two calculations are heavily linked to one another. The main difference is the regression for rating is steeper than that for abilities. Rating decreases faster because players are programmed to lose their key stats faster than other stats once the decline kicks in and that begins to snowball once a player reaches retirement.

Let’s disregard any training average above 250 because you’re never going to see a player like that anyway, especially one that is trained for rating not just even stat distribution anyway.
What does these figures actually show us? Well, for one, rating doesn’t fall off not nearly as fast as most people would expect. A player who can average 200% training (whilst he’s not old) can play top football for a very long time (8 months roughly).

This information can be used to optimise how you play the game. Like for me personally, I only start seriously thinking about selling player’s once they’re 32-33yo and that’s only because past 32 although their rating is only slightly off peak, the player’s stamina stat would be getting weak for a top division player due to that stat depleting faster than others. It’s barely noticeable on the chart because stamina has a very small effect on a Forward’s Rating calculation.

Im going to stop here for now. Some of you probably already knew all this stuff but part 2 will be looking at how you can apply this knowledge to actual running of your team. There’s a lot more to show you and discuss smiley

Whittall United (Grant) 28 November 2018, 19:05
Great work there mate.

Could we make this a sticky please smiley

Champione (Rich) 28 November 2018, 19:07
Whittall United wrote:
Great work there mate.

Could we make this a sticky please smiley
+1

Understated Excellence (Messiah) 28 November 2018, 20:28
Interesting. Alot of hard work gone into that

Rhythm FC (MMM) 28 November 2018, 20:50
Understated Excellence wrote:
Interesting. Alot of hard work gone into that
I mean its not too difficult or time consuming if you know how to model stuff like this to be honest. If people are interested in the equations I can show those too.

its interesting when you can project player stats -> training -> rating ->>>> model players / teams / club economics / build a better picture of how much a player is really worth and so on and so forth


Lowood Mohicans (Ewan) 28 November 2018, 23:06
That's a great piece of work - looking forward to the future posts. And for players like me who've progressed more by serendipity than design it's especially welcome.

Cong Vien Heo Sang (Potential Hunter) 29 November 2018, 06:52
Rhythm FC wrote:
Understated Excellence wrote:
Interesting. Alot of hard work gone into that
If people are interested in the equations I can show those too.

its interesting when you can project player stats -> training -> rating ->>>> model players / teams / club economics / build a better picture of how much a player is really worth and so on and so forth
Yeah, please. I like it very much.

Forest Fire (Marv) 29 November 2018, 09:59
Very nice work (thumbs up x10)

Bolton Wanderers (Paul) Forum moderator 29 November 2018, 11:04
Champione wrote:
Whittall United wrote:
Great work there mate.

Could we make this a sticky please smiley
+1
Yes smiley

SuDoku AFC (Crew Member of the year) Crew 30 November 2018, 00:28
Best forum thread so far this year!

I'm looking forward already to the next instalment ...
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