Prediction of Team-Specific Attendance in the KBO League Through Time Series Analysis

This study analyses the attendance patterns of KBO League teams from 2022 to 2024, employing NeuralProphet to predict future trends over the next two years. The findings indicate a slight decline in overall attendance, although the projected figures are comparable to pre-2024 levels. Seasonal trends reveal an increase in attendance following the March season opening, a decline during June attributed to hot weather, and a resurgence from September driven by late season competition and rankings. Trend analysis shows a general decrease in attendance across most teams. These results underscore the significance of seasonality and team specific factors in shaping attendance patterns. The study provides essential insights for audience engagement strategies and serves as a foundational resource for marketing and revenue enhancement initiatives. Future research should incorporate multivariate approaches and explore advanced time series models to further enhance predictive accuracy and support strategic decision making.

Authors

Publication Details

Journal
Korean Journal of Sports Science
Published
2025-02-28
DOI
https://doi.org/10.35159/kjss.2025.2.34.1.161
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
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article

Prediction of Team-Specific Attendance in the KBO League Through Time Series Analysis

D Lee, Dae Seog Heo, Ji-Young Chung
Korean Journal of Sports Science
Diverse Approaches in Healthcare and Education Studies
article

Prediction of Team-Specific Attendance in the KBO League Through Time Series Analysis

D Lee, Dae Seog Heo, Ji-Young Chung
article en

Abstract

This study analyses the attendance patterns of KBO League teams from 2022 to 2024, employing NeuralProphet to predict future trends over the next two years. The findings indicate a slight decline in overall attendance, although the projected figures are comparable to pre-2024 levels. Seasonal trends reveal an increase in attendance following the March season opening, a decline during June attributed to hot weather, and a resurgence from September driven by late season competition and rankings. Trend analysis shows a general decrease in attendance across most teams. These results underscore the significance of seasonality and team specific factors in shaping attendance patterns. The study provides essential insights for audience engagement strategies and serves as a foundational resource for marketing and revenue enhancement initiatives. Future research should incorporate multivariate approaches and explore advanced time series models to further enhance predictive accuracy and support strategic decision making.

Korean Journal of Sports ScienceVol. 34(1)
Openalex Percentile: Top 93%
Diverse Approaches in Healthcare and Education Studies
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Prediction of Team-Specific Attendance in the KBO League Through Time Series Analysis — D Lee, Dae Seog Heo, et al. · Korean Journal of Sports Science (2025) | TGRS Research Map | TGRS