>  Maybe this was clear to Don already, but his message sounds a little
like it would be possible to estimate >  rating from winning rate and
average opponent. It is not.

No, I didn't mean to imply this. 

- Don



Rémi Coulom wrote:
> Don Dailey wrote:
>> Another example I found is the impressive Valkyria program.   Version
>> 2.7 won 92% of it's games,  more than even the top rated greenpeep0.5.1.
>>
>> However,  the average rating of Valkyria's opponents was only 1722. 
>> This is quite a difference.   So Valkyria is rated only 2222 compared to
>> greenpeep 2621 despite the fact that it wins more!  
>> Of course 2222 is still impressive and Valkyria is number 17  out of all
>> the programs that have played over 200 games  (over 200 of them.) 
>> - Don
> Hi,
>
> I would like to add a note to this discussion to explain that the
> computed rating is not a function of winning rate and average
> opponent. Simply take this simple example into consideration:
>
> player A:
> 1 win and 1 loss against a player of rating 1500
> 1 win against a player of rating 500
> 1 loss against a player of rating 4500
> -> 50% against an average of 2000
>
> player B:
> 1 win and 1 loss against a player of rating 2000
> 1 win against a player of rating 1000
> 1 loss against a player of rating 3000
> -> 50% against an average of 2000
>
> Although they have the same average opponent, and the same winning
> rate, player A's evaluation should be much lower than player B's.
>
> Maybe this was clear to Don already, but his message sounds a little
> like it would be possible to estimate rating from winning rate and
> average opponent. It is not.
>
> Some rating algorithms try to do it anyway (like EloStat, and the
> rating system of the French Chess Federation), but they are very badly
> flawed. Real-life examples where they fail badly can be found on
> bayeselo's page:
> http://remi.coulom.free.fr/Bayesian-Elo/
> (look for "average of ratings" in the page)
>
> Rémi
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>
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