The Role of Big Data Analytics (BDA) in Sport: Sports Data Mining

Background: Big Data Analytics (BDA) is urgently needed in Indonesian sports to improve evidence-based decision-making, athlete development, and organizational management. While BDA has transformed global sports through data-driven insights, its application in Indonesia remains limited and fragmented. The absence of integrated analytics between athlete performance and organizational quality management hinders the creation of sustainable, long-term development systems. Aims: This study investigates how BDA can enhance athlete development and organizational management by analyzing multidimensional data from athletes, coaches, referees, and sports infrastructures. It also aims to identify dominant predictors of athlete performance across various sports and to evaluate the quality management practices of the National Sports Committee of Indonesia (NSCI). Methods: A mixed-methods sequential explanatory design was applied. The quantitative phase involved 67 athletes from six sports: football, table tennis, weightlifting, pencak silat, basketball, and karate at the Sport Training Center. Data on anthropometry, fitness, and achievements were analyzed using descriptive statistics, ANOVA, Chi-Square, and regression tests. The qualitative phase involved interviews and observations with 8–12 stakeholders, while organizational quality was assessed using the Wilcoxon Signed Rank test. Result: Results revealed significant performance differences among sports (F = 4.927, p = 0.001). Each sport had unique dominant predictors: VO₂ max and anthropometry (soccer), agility (table tennis), muscle strength (weightlifting), endurance and height (basketball), and speed (karate). NSCI’s organizational analysis showed substantial deficiencies in management, facilities, and procedures (p < 0.001). Conclusion: This study confirms that BDA is crucial in advancing sustainable sports development. By identifying sport-specific performance predictors and systemic weaknesses, BDA provides a scientific foundation for designing targeted training, improving organizational quality, and building adaptive, data-driven sports ecosystems in Indonesia. The findings highlight the urgent need for national sports bodies to institutionalize BDA as part of long-term strategic planning.

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Journal
Journal of Coaching and Sports Science
Published
2025-10-29
DOI
https://doi.org/10.58524/jcss.v4i2.717
Primary Topic
Sports and Physical Education Research
Type
article
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article

The Role of Big Data Analytics (BDA) in Sport: Sports Data Mining

Mashud Mashud, Ahmad Nasrulloh, Soedjatmiko Soedjatmiko, Putra Sastaman B et al.
Journal of Coaching and Sports Science
Sports and Physical Education Research
article

The Role of Big Data Analytics (BDA) in Sport: Sports Data Mining

Mashud Mashud, Ahmad Nasrulloh, Soedjatmiko Soedjatmiko, Putra Sastaman B, Atip Nurcahyani
article en

Abstract

Background: Big Data Analytics (BDA) is urgently needed in Indonesian sports to improve evidence-based decision-making, athlete development, and organizational management. While BDA has transformed global sports through data-driven insights, its application in Indonesia remains limited and fragmented. The absence of integrated analytics between athlete performance and organizational quality management hinders the creation of sustainable, long-term development systems. Aims: This study investigates how BDA can enhance athlete development and organizational management by analyzing multidimensional data from athletes, coaches, referees, and sports infrastructures. It also aims to identify dominant predictors of athlete performance across various sports and to evaluate the quality management practices of the National Sports Committee of Indonesia (NSCI). Methods: A mixed-methods sequential explanatory design was applied. The quantitative phase involved 67 athletes from six sports: football, table tennis, weightlifting, pencak silat, basketball, and karate at the Sport Training Center. Data on anthropometry, fitness, and achievements were analyzed using descriptive statistics, ANOVA, Chi-Square, and regression tests. The qualitative phase involved interviews and observations with 8–12 stakeholders, while organizational quality was assessed using the Wilcoxon Signed Rank test. Result: Results revealed significant performance differences among sports (F = 4.927, p = 0.001). Each sport had unique dominant predictors: VO₂ max and anthropometry (soccer), agility (table tennis), muscle strength (weightlifting), endurance and height (basketball), and speed (karate). NSCI’s organizational analysis showed substantial deficiencies in management, facilities, and procedures (p < 0.001). Conclusion: This study confirms that BDA is crucial in advancing sustainable sports development. By identifying sport-specific performance predictors and systemic weaknesses, BDA provides a scientific foundation for designing targeted training, improving organizational quality, and building adaptive, data-driven sports ecosystems in Indonesia. The findings highlight the urgent need for national sports bodies to institutionalize BDA as part of long-term strategic planning.

Journal of Coaching and Sports ScienceVol. 4(2)
Tanjungpura University (ID), Yogyakarta State University (ID), State University of Semarang (ID), Chodang University (KR), Lambung Mangkurat University (ID)
Openalex Percentile: Top 51%
Sports and Physical Education Research
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