year 10, Issue 1 (Spring 2022)                   Ann Appl Sport Sci 2022, 10(1): 0-0 | Back to browse issues page

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1- Department of Sports Science, Korea National Sport University, Seoul, Korea
2- Department of Sports Science, Korea National Sport University, Seoul, Korea ,
Abstract:   (1732 Views)
Background. There is a weakness that the win-loss ranking model in the MLB now is calculated based on the result of a win-loss game, so we assume that a ranking system considering the opponent’s team performance is necessary.
Objectives. This study aims to suggest the PageRank algorithm to complement the problem with ranking calculated with winning ratio in calculating team ranking of US MLB.
Methods. PageRank figure is calculated by using the result of 4,861 matches in the 2017 season (2,430 matches) and 2018 season (2,431 matches) in the MLB.
Results. There is a difference between ranking calculated in PageRank and ranking calculated with winning ratio both in the 2017 season and 2018 season, and there is a difference in performance per each district due to comparing performance per each league and district. In addition, as a result of calculating the predictive validity of PageRank and winning ratio ranking, it turns out that the ranking calculated with the PageRank algorithm has relatively high predictive validity.
Conclusion. This study confirmed the possibility of predictive in the US MLB by applying the PageRank algorithm.
Keywords: PageRank, MLB, Baseball, Ranking
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  • PageRank algorithm can evaluate team and player’s performance more reasonably. MLB’s data is used and applied in this study, but it is applicable in sports such as football, basketball, tennis, and others.
  • To apply it to many kinds of sports, it must confirm the PageRank algorithm’s validity considering each sport’s features.

Type of Study: Original Article | Subject: Motor Control and its Related Branches
Received: 2021/01/19 | Accepted: 2021/03/29 | Published: 2022/03/19 | ePublished: 2022/03/19

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