Investigating and Forecasting Momentum Shift Effects on Strategy Development in Sports Competitions

Momentum shifts in competitive sports have a significant impact on game outcomes and strategy development, and despite their widely recognized importance, there is a relative lack of relevant systematic research. In this regard, this study quantified the relationship between momentum shifts and player success, using the metrics analysis method to analyze their correlation and stochasticity. The relevant metrics mainly comprised Spearman rank correlation analysis, and P-value test calculations, which yielded a strong correlation of 0.84 and a P-value less than 0.05. Furthermore, to predict and visualize possible shifts, our study used the LightGBM algorithm to build a predictive model, where we considered shifts to represent changes in strengths and weaknesses between players i.e. moments of change. Afterward, the researchers did an error test for our model, which had a low mean squared error of 0.0019. Finally, this research performed a features importance analysis to identify the most relevant factors such as GPCI, and SGD, and based on the results four ways were suggested for players to deal with new opponents.

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Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-08-12
DOI
https://doi.org/10.62051/avjdhz14
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigating and Forecasting Momentum Shift Effects on Strategy Development in Sports Competitions

Heng Hua, Wenqian Sun
Transactions on Computer Science and Intelligent Systems Research
Sports Analytics and Performance
article

Investigating and Forecasting Momentum Shift Effects on Strategy Development in Sports Competitions

Heng Hua, Wenqian Sun
article en

Abstract

Momentum shifts in competitive sports have a significant impact on game outcomes and strategy development, and despite their widely recognized importance, there is a relative lack of relevant systematic research. In this regard, this study quantified the relationship between momentum shifts and player success, using the metrics analysis method to analyze their correlation and stochasticity. The relevant metrics mainly comprised Spearman rank correlation analysis, and P-value test calculations, which yielded a strong correlation of 0.84 and a P-value less than 0.05. Furthermore, to predict and visualize possible shifts, our study used the LightGBM algorithm to build a predictive model, where we considered shifts to represent changes in strengths and weaknesses between players i.e. moments of change. Afterward, the researchers did an error test for our model, which had a low mean squared error of 0.0019. Finally, this research performed a features importance analysis to identify the most relevant factors such as GPCI, and SGD, and based on the results four ways were suggested for players to deal with new opponents.

Transactions on Computer Science and Intelligent Systems ResearchVol. 5
China University of Geosciences (Beijing) (CN)
Openalex Percentile: Top 84%
Sports Analytics and Performance
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