Sports Ed 3.5

[eyouso]

Title

Sports Ed 3.5: Establishing the value of data-driven sports
development programs for universities through machine
learning models

URL

https://dl.acm.org/doi/10.1145/3446999.3447009

Summary

Article shows how machine learning can be used to develop players

Key Points

Citation

@inproceedings{10.1145/3446999.3447009,
author = {Mendoza Torralba, Edwin},
title = {Sports Ed 3.5: Establishing the value of data-driven sports development programs for universities through machine learning models},
year = {2021},
isbn = {9781450388559},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3446999.3447009},
doi = {10.1145/3446999.3447009},
abstract = {Sports have evolved from the exposition of athletes’ pure talent to an industry that generates jobs and entertainment. In the Philippines, athletes from different Universities and Colleges are the primary source of talents in amateur and professional leagues especially in the field of volleyball and basketball. As such, schools are developing their physical and athletic programs to establish their respective competitive advantage. However, student-athletes from universities with insufficient resources are often neglected due to inadequate exposure. Furthermore, there is no framework that secures the statistical data of student-athletes which can be used for future appraisal of player's talent and athletic skills. This study aims to propose a conceptual framework of “Sports Ed 3.5” for universities and collegiate athletic associations to develop an athlete information system for sports analytics. In addition, the framework aims to define the philosophy that will govern all the stakeholders in the utilization of an athlete's information for flexible decision-making. Players’ dataset from the Philippine Basketball Association's website was retrieved to demonstrate on how an athletic information system can support the athletes, coaches, and stakeholders of sports. Supervised algorithms were used to illustrate the value of data and machine learning models in athletic development programs. Future research direction and challenges are discussed to implement the proposed “Sports Ed 3.5” model for Philippine schools and universities.},
booktitle = {Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City},
pages = {51–57},
numpages = {7},
location = {Xi'an, China},
series = {ICIT '20}
}

Repo link