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I have started building an app which collects all the players attributes and according to primary and secondary attributes it makes an estimate of how good that player is in all the combinations of Roles & Duties.

It is an arithmetic mean with the following contribution:

Primary attributes 60%

Secondary attributes 25%

Remaining attributes 10%

It is not a bible but gives me a quicker overview of which player has to play in a specific role or not. Would you do anything different?

 

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Sounds reasonable and something I have done to some degree in the past.

Not sure I would use the same % though and you'll also find you'll run into some issues.

The main issue is that you need to try and make every role/duty add up to the same amount else it unbalances the calculations and each role/duty requires a different number of key/secondary attributes.  So what you'll find is that without making an adjustment some roles/duties will inherently score higher than others and that some will be easier/harder to score higher in due to having less/more key/secondary attributes.

 

Outside of your calculations you also need to be aware of how the role/duty fits into the overall tactic of the team, just because a player is best playing as a defensive forward say it doesn't mean thats best for the team.

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I understand what you mean and that's true, there are a few roles where every player seems to be very good at.

As previously said, it is not a bible but just a point of reference if combined with the scouts/assistant manager report.

Which %s would you use though?

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Apart from the fact I use attribute masking, I like the idea and used to have a spreadsheet which applied a weighted average approach to attributes, but only for basic positions rather than roles as a few years ago. Genie Scout uses the same approach.

Also consider the Club DNA threads.

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1 hour ago, knap said:

Apart from the fact I use attribute masking, I like the idea and used to have a spreadsheet which applied a weighted average approach to attributes, but only for basic positions rather than roles as a few years ago. Genie Scout uses the same approach.

Also consider the Club DNA threads.

what do you mean by Club DNA threads?

 

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This is interesting enough but would only work for a specific league and only if you collect data for a very long period of time to draw out the average best player of the month in every position for your league.

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