Review Article Others

Methodological examination of methods for analyzing factors that affect home team advantage: from univariate analysis to multivariate correlation models and causal models

While most researchers agree that home advantage (HA) exists in soccer, baseball, field hockey, basketball, and other sports regardless of whether they are collegiate or professional, there is no common view on the relationship between “travel,” “familiarity with the game environment,” and “spectator effect” and the factors derived from them and home advantage. However, there is no common view on the relationship between “travel,” “familiarity with the game environment,” “spectator effect,” and their derived factors, and HA. In other words, unless there are new factors that are not addressed here, it is more appropriate to think of the factors that affect HA, which clearly exists, as “multiple factors that relate to each other and affect it comprehensively,” rather than as “factors that affect it independently. Therefore, a possible methodology for examining HA factors is the use of multivariate analysis, such as multiple regression analysis or logistic regression analysis. Then, when illustrating the findings obtained from correlation analysis, one-way arrows are used to show the relationship between the factors, and the focus shifts from the correlation relationship to the search for causal relationships. When the scope of correlation analysis is extended to include causal relationships, path analysis is used to examine not only direct effects but also indirect effects. Furthermore, as a natural development of the methodology of causal analysis, a new direction is considered to be the analysis of covariance structure, which examines the causal relationships between factors, rather than only the observed variables.

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Review Article Others

A statistical examination into the structure of plays and its relationship to wins/losses in basketball games played by excellent players from the standpoint of STATS

We reviewed and summarized the findings from some kinds of perspectives. This allowed us to realize that no consistent findings can be obtained in terms of what plays/factors contribute most to wins/losses and the sequence of plays leading to scoring, that discriminant analysis is commonly used in the studies, and that for structural analysis, no rotational technique was used. Based on these findings, we devised the following new proposals: 1) Researchers need to exert more effort to analyze various kinds of games in the future, 2) We can recommend logistic regression analysis, but not only discrimination analysis. 3) For structural analysis, to make the research findings useful, the rotation of axes or principal components should be actively utilized.

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