薪資差異與球隊勝率關係之研究-以中華職棒大聯盟與日本職業棒球聯盟為例

Abstract

本研究以薪資差異對球隊勝率的影響為核心，探討此關係在中華職棒大聯盟(CPBL) 與日本職業棒球聯盟 (NPB) 之間的異同。隨著全球職業運動市場的快速發展，球員薪資不僅是其能力的經濟體現，亦對球隊經營策略與聯盟發展方向有著深遠影響。過去薪資差異對球隊表現之影響的相關文獻，顯示了相互矛盾的結果，部分研究認為薪資差異擴大會提高競爭力，而另一些研究則指出薪資差異縮小更能促進球隊表現。因此，本研究針對 2013 至 2024 年間 CPBL 與 2013 至 2024 年間 NPB 的各球隊，進行薪資差異與球隊勝率關係的實證分析。研究採用變異係數、基尼係數與赫芬達指數量化薪資差異，並以總薪資、薪資差異、防禦率、整體攻擊指數、盜壘數、球員名單人數與平均年齡等七項自變項建構迴歸模型，搭配球隊勝率作為應變項進行迴歸分析。本研究資料來源涵蓋官方網站、專業媒體及相關文獻，結合多重來源以彌補薪資不完全公開的資訊不完整性。研究結果：在中職中總薪資呈顯著正相關，薪資差異與球員名單人數呈顯著負相關，整體攻擊指數與盜壘數呈正相關但不顯著，防禦率與平均年齡呈負相關但不顯著。在日職中整體攻擊指數呈顯著正相關，防禦率呈顯著負相關，總薪資、薪資差異與盜壘數呈正相關但不顯著，球員名單人數與平均年齡呈負相關但不顯著。

This study focuses on the impact of wage disparities on team winning percentages, exploring the similarities and differences between the Chinese Professional Baseball League (CPBL) and the Nippon Professional Baseball (NPB). With the rapid growth of the global professional sports market, player wages not only reflect their economic value but also significantly influence team management strategies and league development. Previous studies on the effect of salary disparities on team performance have yielded contradictory results. Some research suggests that increased salary disparities enhance competitiveness, while others argue that reducing salary disparities promotes better team performance. To address this, the study conducts an empirical analysis of the relationship between salary disparities and team winning percentages for CPBL and NPB teams from 2013 to 2024.The study employs coefficients of variation, Gini coefficients, and Herfindahl indices to quantify salary disparities. Seven independent variables—total wage, wage disparity, ERA, OPS, number of stolen bases, roster size, and average age—are used to construct regression models, with team winning percentage as the dependent variable. Data sources include official websites, professional media, and related literature, integrating multiple channels to address information gaps caused by the lack of complete salary transparency.Research Findings: In the CPBL, total wage is significantly positively correlated with win percentage, while wage disparity and roster size show a significant negative correlation. OPS and number of stolen bases are positively correlated but not significant. ERA and average age are negatively correlated but also not significant. In the NPB, OPS is significantly positively correlated with win percentage, and ERA is significantly negatively correlated. Total wage, wage disparity, and number of stolen bases are positively correlated but not significant. Roster size and average age are negatively correlated but not significant.