An Elo-based rating system for TopCoder SRM
This provides a domain-specific rating system for programming contest organizers and participants, but it is incremental as it adapts existing Elo methods to a new context.
The paper tackles the problem of rating programming contest participants in Topcoder SRMs by developing an Elo-based system with a logarithmic rank-based performance metric, showing improved rank predictions and rating progressions consistent with skill development.
This paper presents an Elo-based rating system for programming contests, specifically Topcoder's Single Round Matches (SRMs). We introduce a logarithmic rank-based performance metric that allows single-round, multi-player contest results to be incorporated into an Elo-style continuous rating framework. Model parameters and adjustment factors are calibrated empirically by minimizing absolute prediction error over historical data, accounting for experience level, initial ratings, and competition characteristics. The resulting system demonstrates improved rank predictions and rating progressions consistent with natural skill development over player careers.