Ranking and prediction of collegiate wrestling

Bigsby, Kristina Gavin; Ohlmann, Jeffrey W.

doi:10.3233/jsa-160024

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…It is measured how often the model favoured team could win the match. It has already been shown by Bigsby & Ohlmann (2017), who evaluated the results of college wrestling matches in their studies, that meaningful predictions can be made with the Elo method in sports.…”

Section: Evaluation Of the Resultsmentioning

confidence: 99%

A football player rating system

Wolf

Schmitt

Schuller

2020

Journal of Sports Analytics

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Association football (soccer) is the most popular sport in the world, resulting in a large economic interest from investors, team managers, and betting agencies. For this reason, a vast number of rating systems exists to assess the strength of football teams or individual players. Nevertheless, most of the existing approaches incorporate deficiencies, e. g., that they depend on subjective ratings from experts. The objective of this work was the development of a new rating system for determining the playing strength of football players. The Elo algorithm, which has established itself as an objective and adaptive rating system in numerous individual sports, has been expanded in accordance with the requirements of team sports. Matches from 16 different European domestic leagues, the UEFA Champions and Europa Leagues have been recorded, with more than 17 000 matches played in recent years, and 12 400 different players. The developed rating system produced promising results, when evaluating the matches based on its predictions. A high relevance of the created system results from the fact that only the associated match report is needed and thus—in relation to existing valuation models—significantly more football players can be assessed.

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Section: Evaluation Of the Resultsmentioning

confidence: 99%

A football player rating system

Wolf

Schmitt

Schuller

2020

Journal of Sports Analytics

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“…This result may be explained by the effect of the knock out matches the other tournament data. In another study, Bigsby and Ohlmann (2017) have been compared to a traditional ranking system with PageRank and Elo Rating method for wrestlers from all weight class [14]. Findings of…”

Section: Discussionmentioning

confidence: 99%

Untitled

2019

IJAEP

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Application of network-based algorithms to the sports metrics is addressed to several disciplines. PageRank algorithm has been used for both team sports and individual players performance assessments whereas there is no study to handball team rankings. Purpose of this study is to investigate the differences between the traditional ranking system and PR algorithm in handball. Total 306 game results, scores made, conceding goals, offense and defense-related match statistics that played in Bundesliga 2017-18 season were collected from DKB Bundesliga official web page. We estimated four different PR values by name PageRankstraight, PageRankoffence, PageRankdefense, and PageRankdifference. The official points and normalized PR scores and provide the team standings changed by using the PR algorithm. A positive correlation was found between official system ranking and PageRankstraight, PageRankoffence, PageRankdefense, and PageRankdifference respectively r=0,932, p=0,000; r=0,915, p=0,000; r=0,711, p=0,001; and r=0,926, p=0,000. In this study, the PR algorithm presented a novel approach to ranking handball teams. Further researches needed to investigate alternative ranking methods which allow objective evaluation of a team's performance, not just game results. Finally, we do not conceive the substitute traditional system within the PR algorithm for league standings, but it could be regarded as a method of assessment team market values and distributions of income.

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“…The classic argument goes as follows: "my team A beat team B, who in turn beat your team C -therefore, my team is better than your team." This argument makes intuitive sense and also increases predictive accuracy when implemented in similar ranking systems for wrestling [2], tennis [24], and American football [25] so we choose to incorporate it as the central tenet of our models.…”

Section: How Can It Be Improved?mentioning

confidence: 99%

Dynamic Network 3 -- 0 FIFA Rankings: Replacing an inaccurate, biased, and exploitable ranking system

Abernethy¹

2018

Preprint

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We explore the advantages of representing international football results as a directed network in order to give each team a rank. Two network-based models -Static and Dynamic -are constructed and compared with the FIFA Rankings. The Dynamic Model outperforms the FIFA Rankings in terms of World Cup predictive accuracy, while also removing continental bias and reducing the vulnerability of the FIFA Rankings to exploitation.

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Ranking and prediction of collegiate wrestling

Cited by 5 publications

References 7 publications

A football player rating system

A football player rating system

Untitled

Dynamic Network 3 -- 0 FIFA Rankings: Replacing an inaccurate, biased, and exploitable ranking system

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