Understanding draws in Elo rating algorithm
| Autor: | Aymen Djebbi, Leszek Szczecinski |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
2019-20 coronavirus outbreak
Coronavirus disease 2019 (COVID-19) Computer science Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 05 social sciences Probabilistic logic Binary number Probability and statistics 01 natural sciences Interpretation (model theory) Moment (mathematics) 010104 statistics & probability 0502 economics and business Decision Sciences (miscellaneous) 0101 mathematics Algorithm Social Sciences (miscellaneous) 050205 econometrics |
| Zdroj: | Journal of Quantitative Analysis in Sports. 16:211-220 |
| ISSN: | 1559-0410 2194-6388 |
| DOI: | 10.1515/jqas-2019-0102 |
| Popis: | This work is concerned with the interpretation of the results produced by the well known Elo algorithm applied in various sport ratings. The interpretation consists in defining the probabilities of the game outcomes conditioned on the ratings of the players and should be based on the probabilistic rating-outcome model. Such a model is known in the binary games (win/loss), allowing us to interpret the rating results in terms of the win/loss probability. On the other hand, the model for the ternary outcomes (win/loss/draw) has not been yet shown even if the Elo algorithm has been used in ternary games from the very moment it was devised. Using the draw model proposed by Davidson in 1970, we derive a new Elo-Davidson algorithm, and show that the Elo algorithm is its particular instance. The parameters of the Elo-Davidson are then related to the frequency of draws which indicates that the Elo algorithm silently assumes games with 50% of draws. To remove this assumption, often unrealistic, the Elo-Davidson algorithm should be used as it improves the fit to the data. The behaviour of the algorithms is illustrated using the results from English Premier League. |
| Databáze: | OpenAIRE |
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