Next Article in Journal
The Mechanism of Resonant Amplification of One-Dimensional Detonation Propagating in a Non-Uniform Mixture
Next Article in Special Issue
High-Compression Crash Simulations and Tests of PLA Cubes Fabricated Using Additive Manufacturing FDM with a Scaling Strategy
Previous Article in Journal
Topology Optimization and Efficiency Evaluation of Short-Fiber-Reinforced Composite Structures Considering Anisotropy
Previous Article in Special Issue
Accelerating Multiple Sequence Alignments Using Parallel Computing
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics

by
Vangelis Sarlis
,
George Papageorgiou
and
Christos Tjortjis
*
School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Computation 2024, 12(2), 36; https://doi.org/10.3390/computation12020036
Submission received: 15 January 2024 / Revised: 5 February 2024 / Accepted: 14 February 2024 / Published: 16 February 2024
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Engineering)

Abstract

This research paper examines Sports Analytics, focusing on injury patterns in the National Basketball Association (NBA) and their impact on players’ performance. It employs a unique dataset to identify common NBA injuries, determine the most affected anatomical areas, and analyze how these injuries influence players’ post-recovery performance. This study’s novelty lies in its integrative approach that combines injury data with performance metrics and salary data, providing new insights into the relationship between injuries and economic and on-court performance. It investigates the periodicity and seasonality of injuries, seeking patterns related to time and external factors. Additionally, it examines the effect of specific injuries on players’ per-match analytics and performance, offering perspectives on the implications of injury rehabilitation for player performance. This paper contributes significantly to sports analytics, assisting coaches, sports medicine professionals, and team management in developing injury prevention strategies, optimizing player rotations, and creating targeted rehabilitation plans. Its findings illuminate the interplay between injuries, salaries, and performance in the NBA, aiming to enhance player welfare and the league’s overall competitiveness. With a comprehensive and sophisticated analysis, this research offers unprecedented insights into the dynamics of injuries and their long-term effects on athletes.
Keywords: basketball analytics; data analysis; data mining; data science; injury analytics; musculoskeletal injuries; sports analytics (SA) basketball analytics; data analysis; data mining; data science; injury analytics; musculoskeletal injuries; sports analytics (SA)

Share and Cite

MDPI and ACS Style

Sarlis, V.; Papageorgiou, G.; Tjortjis, C. Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics. Computation 2024, 12, 36. https://doi.org/10.3390/computation12020036

AMA Style

Sarlis V, Papageorgiou G, Tjortjis C. Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics. Computation. 2024; 12(2):36. https://doi.org/10.3390/computation12020036

Chicago/Turabian Style

Sarlis, Vangelis, George Papageorgiou, and Christos Tjortjis. 2024. "Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics" Computation 12, no. 2: 36. https://doi.org/10.3390/computation12020036

APA Style

Sarlis, V., Papageorgiou, G., & Tjortjis, C. (2024). Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics. Computation, 12(2), 36. https://doi.org/10.3390/computation12020036

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop