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ire_and_curses
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Try this, it's a system called Whole-History Rating. From the abstract:

Whole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational cost than traditional methods, but computation is still fast enough to be easily applied in real time to large-scale game servers (a new game is added in less than 0.001 second). Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions.

It's been used rather successfully by a game I play called ArimaaArimaa. For a tournament score, rather than a player skill rating, you will probably want to treat all games as being played simultaneously, as opposed to allowing the ratio to fluctuate over time.

Sorry for the primarily link-based answer. It's rather math-heavyIf it's source code you're after, and I'm not exactly sure how to display formulae properly onyou may find this sitepure Ruby implementation helpful. It can support any two player game, as long as the outcome is a simple win/loss.

Try this, it's a system called Whole-History Rating.

It's been used rather successfully by a game I play called Arimaa. For a tournament score, rather than a player skill rating, you will probably want to treat all games as being played simultaneously, as opposed to allowing the ratio to fluctuate over time.

Sorry for the primarily link-based answer. It's rather math-heavy, and I'm not exactly sure how to display formulae properly on this site.

Try this, it's a system called Whole-History Rating. From the abstract:

Whole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational cost than traditional methods, but computation is still fast enough to be easily applied in real time to large-scale game servers (a new game is added in less than 0.001 second). Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions.

It's been used rather successfully by a game I play called Arimaa. For a tournament score, rather than a player skill rating, you will probably want to treat all games as being played simultaneously, as opposed to allowing the ratio to fluctuate over time.

If it's source code you're after, you may find this pure Ruby implementation helpful. It can support any two player game, as long as the outcome is a simple win/loss.

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Sconibulus
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Try this, it's a system called Whole-History Rating.

It's been used rather successfully by a game I play called Arimaa. For a tournament score, rather than a player skill rating, you will probably want to treat all games as being played simultaneously, as opposed to allowing the ratio to fluctuate over time.

Sorry for the primarily link-based answer. It's rather math-heavy, and I'm not exactly sure how to display formulae properly on this site.