Fan Loyalty and Price Elasticity in Sport: Insights from Major League Baseball’s Post-Pandemic Recovery

The COVID-19 pandemic disrupted traditional patterns of sport consumption, raising questions about whether fans would return to stadiums and how sensitive they would be to ticket prices in the recovery period. This study reconceptualizes ticket price elasticity as a market-based indicator of fan loyalty and applies it to Major League Baseball (MLB) during 2021–2023. Using team–season attendance data from Baseball-Reference, primary-market ticket prices from the Team Marketing Report Fan Cost Index, and secondary-market prices from TicketIQ, we estimate log–log fixed-effects panel models to separate causal price responses from popularity-driven correlations. The results show a strongly negative elasticity of attendance with respect to primary-market prices (β ≈ −7.93, p < 0.001), indicating that higher ticket prices substantially reduce attendance, while secondary-market prices are positively associated with attendance, reflecting demand shocks rather than causal effects. Heterogeneity analyses reveal that brand strength, team performance, and game salience significantly moderate elasticity, supporting the interpretation of inelastic demand as revealed loyalty. These findings highlight the potential of elasticity as a Fan Loyalty Index, providing a replicable framework for measuring consumer resilience. The study offers practical insights for pricing strategy, fan segmentation, and engagement, while emphasizing the broader social role of sport in restoring community identity during post-pandemic recovery.

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Publication Details

Journal
Analytics
Published
2025-11-21
DOI
https://doi.org/10.3390/analytics4040034
Primary Topic
Sports, Gender, and Society
Type
article
Field-Weighted Citation Impact
0.00

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article

Fan Loyalty and Price Elasticity in Sport: Insights from Major League Baseball’s Post-Pandemic Recovery

Seung-Man Lee, Zheng Fang, S. Chan Choi
Analytics
Sports, Gender, and Society
article

Fan Loyalty and Price Elasticity in Sport: Insights from Major League Baseball’s Post-Pandemic Recovery

Seung-Man Lee, Zheng Fang, S. Chan Choi
article en

Abstract

The COVID-19 pandemic disrupted traditional patterns of sport consumption, raising questions about whether fans would return to stadiums and how sensitive they would be to ticket prices in the recovery period. This study reconceptualizes ticket price elasticity as a market-based indicator of fan loyalty and applies it to Major League Baseball (MLB) during 2021–2023. Using team–season attendance data from Baseball-Reference, primary-market ticket prices from the Team Marketing Report Fan Cost Index, and secondary-market prices from TicketIQ, we estimate log–log fixed-effects panel models to separate causal price responses from popularity-driven correlations. The results show a strongly negative elasticity of attendance with respect to primary-market prices (β ≈ −7.93, p < 0.001), indicating that higher ticket prices substantially reduce attendance, while secondary-market prices are positively associated with attendance, reflecting demand shocks rather than causal effects. Heterogeneity analyses reveal that brand strength, team performance, and game salience significantly moderate elasticity, supporting the interpretation of inelastic demand as revealed loyalty. These findings highlight the potential of elasticity as a Fan Loyalty Index, providing a replicable framework for measuring consumer resilience. The study offers practical insights for pricing strategy, fan segmentation, and engagement, while emphasizing the broader social role of sport in restoring community identity during post-pandemic recovery.

AnalyticsVol. 4(4)
Zhejiang International Studies University (CN), Hankyong National University (KR), Department of Education of Zhejiang Province (CN), Zhejiang University (CN)
Zhejiang University
Openalex Percentile: Top 56%
Sports, Gender, and Society
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Fan Loyalty and Price Elasticity in Sport: Insights from Major League Baseball’s Post-Pandemic Recovery — Seung-Man Lee, Zheng Fang, et al. · Analytics (2025) | TGRS Research Map | TGRS