目的:球員是職業棒球運動的核心,也是球隊的資產,球員的表現好壞影響到球賽的結果,而以球賽輸贏作為收受電視轉播權金、販賣球票、促銷商品、招攬贊助、創造營收和品牌延伸主要訴求的球隊來說,球員便是他們的生財工具。而臺灣過去二十多年來勞資雙方因薪資爭議尋求仲裁的案件約有20件,不僅破壞雙方的形象,更會造成負面結果影響球員場上的表現。因此本研究的目的希望尋求一個客觀且科學的工具和模型,球員得以藉由表現估算合理價值,並藉以作為薪資協商的依據,使其得以專心於可以創造價值的球賽上。球隊也可以減少談薪的心力,而能在其預算範圍內,對球員依照建議模型進行論功行賞的標準。方法:本研究為了使大眾容易使用,先參考過去文獻,並進行前測篩選出影響中華職棒大聯盟2008至2016年打者薪資的重要參數,並以最容易被解讀且接受的迴歸分析計算出各個薪資影響參數的權重,建立薪資估算模型。再以模型預測之薪水與實際薪水比較去檢測模型準確性,而後將2017及2018年的資料帶入以檢驗模型之預估能力。結果:發現以年紀、整體攻擊指數及勝利貢獻指數所建構的薪資估算模型便具有高精確度,且在預測能力方面,2017及2018兩年的資料都將接近高精確度。結論:本研究所得之薪資估算模型雖並不複雜,但仍保有高精確度,方便使用,此外隨著時間精確度改變的幅度很小,因此可供未來參考。並建議球隊可以建立公平公正與公開的核薪機制,球員也應積極建立自我形象,以利職業棒球市場蓬勃發展。
Purpose: Players are the core of professional baseball games and assets to their clubs. The performance of players influences the results of games. Game results affect a baseball club's television broadcasting rights fees, tickets sales, goods promotion, sponsor attraction, revenue creation, and brand extension. Thus, players are financial tools to baseball clubs. In Taiwan, approximately 20 cases of salary arbitration disputes have occurred between baseball players and their clubs. Such disputes not only undermine the images of the club and players but also negatively influence players' performance on the field. Therefore, this study developed an objective and scientific model for baseball players to estimate their reasonable value according to their performance. Players can use the results of this study as a reference for salary negotiation and focus on their game scores to create higher values. Moreover, clubs can reduce their efforts in negotiating salaries and reward players according to the standard indicated by the proposed model within their budget range. Methods: This study referred to past research and conducted a pretest to select important parameters that affected the salaries of Chinese Professional Baseball League batters from 2008 to 2016. Regression analysis, a widely used and easily interpreted method, was adopted to identify the weight of each salary influencing parameter and establish the salary model for 2008-2016. The salary predicted by the model and the actual salary were compared to test the accuracy of the model. The data of 2017 and 2018 were also substituted into the model to examine its predictive ability. Results: The obtained results indicated that the developed salary prediction model, which uses the age, OPS, and Win Shares as parameters, exhibited high accuracy for the 2008-2016 data. The model also had a high predictive accuracy for the 2017 and 2018 data. Conclusion: Although the salary estimation model developed in this study is not complex, it still provides high accuracy and is convenient for use. In addition, the model exhibited only a small decrease in accuracy with the data for 2017 and 2018; therefore, it can be used in the future to determine appropriate salaries. To facilitate the development of a professional baseball market, clubs must establish a fair, open, and transparent salary system. Moreover, players should actively establish their self-image.