Key factors and tactical variations in Chinese national women's softball games: a machine learning-based identification

Feature importance analysis from the RF model indicates that P-ER and key batting metrics (e.g., OBP, AVG)are significantly associated with predicting game outcomes. These findings highlight their importance in predictive models, though further research is needed to confirm their practical impact.

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Publication Details

Journal
Frontiers in Sports and Active Living
Published
2025-11-21
DOI
https://doi.org/10.3389/fspor.2025.1701387
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
0.00

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article

Key factors and tactical variations in Chinese national women's softball games: a machine learning-based identification

Hanyao Li, Tianyu Zhang, Gang Cheng
Frontiers in Sports and Active Living
Sports Analytics and Performance
article

Key factors and tactical variations in Chinese national women's softball games: a machine learning-based identification

Hanyao Li, Tianyu Zhang, Gang Cheng
article en

Abstract

Feature importance analysis from the RF model indicates that P-ER and key batting metrics (e.g., OBP, AVG)are significantly associated with predicting game outcomes. These findings highlight their importance in predictive models, though further research is needed to confirm their practical impact.

Frontiers in Sports and Active LivingVol. 7
Nanjing Tech University (CN), Beijing Sport University (CN)
Government of Jiangsu Province
Openalex Percentile: Top 57%
Sports Analytics and Performance
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