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題名:中華職棒大聯盟打者薪資預測模型之建構
作者:朱柏璁
作者(外文):CHU, BO-TSUNG
校院名稱:國立體育大學
系所名稱:體育研究所
指導教授:葉公鼎
學位類別:博士
出版日期:2020
主題關鍵詞:薪資協商年齡整體攻擊指數勝利貢獻指數salary negotiationageOPSwin shares
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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利金、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。台灣職棒(中華職棒大聯盟)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。
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,建立薪資預測模型。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,最後再以前人研究中所提及的相關因子進行三因子的模式建立,並比較與其模型間的準確性。
扣除出賽次數過少的球員後,總計納入303名球員之資料進行模型建立,初步模型中分析出有9個因子與薪資有相關性,再依前人研究中與前測結果挑選出年紀、整體攻擊指數及勝利貢獻指數所建構的薪資預測模型,以平均絕對百分比誤差 (MAPE)驗證發現這個模型具有高度的準確性,且薪資被高估及被低估的人數相仿;不同年間的誤差也都落於高準確度及良好準確度之間,而在所有薪資區間中,模型預測的能力也接近相同。且在預測能力方面,2017及2018兩年的資料都將接近高準確度,且所有的球員的預估薪資都落在合理的預估範圍內,且約半數的球員都落在高準度範圍內。而預估薪資稍微高於實際薪資,表示依據球員的表現,球團應給予球員更高的薪資,這也反映了和往年相比,2017和2018年野手薪資成長率的下降。而為了進一步比較三因子是否足以預估薪資,由相同取樣年間的前人研究中所挑選的十個因子進行120組的模型比較,本研究所挑選的三個因子預估能力準確度仍較高。
本研究所得之薪資預測模型雖並不複雜,但仍保有高準確度,方便使用,此外隨著時間推移準確度改變的幅度很小,因此可供未來參考。由於本研究所得之薪資預測模型,主要考量打者的表現參數,惟諸如明星魅力、球團戰績以及球團預算等變數,建議後續研究仍可加以探討。此外,本研究結果適用對象並不包括投手薪資,故針對投手的薪資預測模型亦仍待後續研究者探討。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,政府也可以促使專業的運動經紀人發展,以利職業棒球市場蓬勃興旺。
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.
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. Finally, the relevant factors mentioned in previous studies are used to establish a three-factor model and compare the accuracy among these models.
After deducting the batters who played limited games, a total of 303 batters were included for model building. The preliminary model indicated there are 9 factors correlated with salary. Then, based on previous research and preliminary results, the salary estimation model constructed by age, OPS, and Win Shares are highly accurate and verified by Mean Absolute Percentage Error (MAPE), this model is highly accurate. And the number of batters whose salary is overestimated or underestimated is similar. The MAPE in different years also falls between high accuracy and good accuracy. In all salary ranges, the estimation ability of the model is also similar. In terms of predictive ability, the data for 2017 and 2018 are near high accuracy. The estimated salary of all batters falls within reasonable accuracy, and about half of the estimated salary of batter fall within the high accuracy range. The estimated salary is slightly higher than the actual salary, indicating that based on the performance of the players, the team should give the players a higher salary. This phenomenon also reflects the decline in the salary growth rate of the batters in 2017 and 2018 compared with previous years. In order to further compare whether the three-factor model is sufficient to predict the salary, 120 sets of models, constructed by ten factors selected in previous studies in the same sampling year, were compared. The three factors selected in this study remain high accuracy.
Although the salary estimation model developed in this study is not complex, it still provides high accuracy and is convenient to refer. 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.
Besides, since the salary estimation model developed in this study does not take all factors into account for the decision of the salary, such as the player’s charisma, the performance of the club and the budget of the club. We suggest researchers in the future shall cover the above factors in this regard. In addition, the salary estimation model does not apply to the salary of pitchers, we suggest the relevant estimation model shall be developed as well.
Finally, the researcher of this study suggests that clubs must establish a fair, open, and transparent salary system 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; the government can also promote the development of professional sports agents to benefit the development of professional baseball market.
方進義、鄭志富、林欣慧 (2013)。中華職棒野手球員的國籍、年資、球隊效果與換隊頻率對其績效之影響:1990年到2010年。體育學報,46(3),291-302。doi:10.6222/pej.4602.201309.0909
方妙玲(2008)。高階主管薪資與財務績效及社會績效之關聯性:代理理論及利害關係人理論觀點。企業管理學報, 77,47-80。
何吉星、高俊雄(1996)。台灣地區職業棒球隊運動員甄選、評估、發展及酬勞之研究。國立體育學院論叢,8(1),39-52。
李俞麟、施致平、黃蕙娟(2011)。美國職業棒球大聯盟球隊績效評估之研究。 臺灣體育運動管理學報,11(4),317-335。
李志峰、陳玠宇(2019)。中華職棒薪資仲裁制度的若干建議
—從美日職棒經驗出發。全國律師,2月號,38-59。
吳泰毅 (2000)。我國職棒薪資決定因素之探討 (碩士學位論文)。國立臺灣師範大學,臺北市。
林瑞宸 (2008)。中華職棒球員薪資決定因素初探 (碩士學位論文)。國立政治大學,臺北市。
林房儹(2010)。美國運動產業產值分析與產業發展相關策略暨條例。「行政院體育委員會各國運動產業產值與租稅優惠政策研討會」發表之論文。國立體育大學。
洪麗雯(2005)。總額預算、薪資公平與薪資滿足對醫師工作態度之相關性影響與探討。人力資源管理學報,5(1), 135-161。
胡林煥、康正男(2019)。中華職棒聯盟球員複數合約簽約前後效率分析。體育學報,52(1),95-107。
孫順吉、陳世哲(1998)。影響組織內部勞動市場因素之研究。交大管理學報,18(1),43-77。
梁功斌(2016)。影響中華職棒選手薪資與績效表現因子之探討 (碩士學位論文)。國立臺灣大學,臺北市。
曹士昌(2006)。TWbaseball info. Handbook。取自http://twb.tolink.com.tw/
陳志成、陳天賜(2016)。(計畫編號:MOST 104-2410-H-156-013-)。 臺北市:國科會。
陳冠語(2010)。薪資結構對組織績效的影響-以NBA及MLB為例 (博士學位論文)。國立中央大學,桃園市。
陳德璘、方信淵 (2009)。職業運動聯盟獲利經營策略剖析:以超級籃球聯賽與中華職棒大聯盟為例。大專體育 (103),48-55。
陳逸政(2012)。美國職業棒球大聯盟球隊薪資結構與績效之探討。運動教練科學,28,37-48。
程紹同(2001)。第5促銷元素:運動贊助行銷新風潮。大專體育(55),139-139。
黃瑞雯(2016)。薪資與績效之關聯性研究-以中華職棒為例 (博士學位論文)。東海大學,臺中市。
雷文谷、吳靜怡(2010)。美國職棒大聯盟球隊薪資與球隊戰績之相關研究。嘉大體育健康休閒期刊,9(2),14-25。
蔡孟娟、雷文谷、謝春宣(2012)。戰力或負擔?中華職棒外籍與本國籍野手績效之比較。運動休閒管理學報,9(2),202-216。
廖清海、楊世達(2010)。運動表現與薪資之關聯性探討-以中華職棒大聯盟十九年為例。運動與遊憩研究,4(3),57-67。
劉必然(2011)。日本職棒打者表現與年齡分析(碩士學位論文)。國立臺灣體育運動大學,臺中市。
連淑君、余德成(2004)。薪資制度、責任感與工作績效之研究。 人力資源管理學報,4(2),47-59。
陳光華、黃榮鵬(2005)。建構最佳的旅行業業務員薪資結構制度。 戶外遊憩研究,18(4),69-92。
劉振家、陳育成、黃德舜(2009)。職業運動選手薪資及其影響因素分析—美國、日本、韓國、臺灣職業棒球聯盟之比較。休閒事業研究,7(2),87-105。
鄭桂玫、徐茂洲(2012)。結構方程模型的統計檢定力計算及樣本數決定在《大專體育學刊》之運用。大專體育(123),25-34。
闕維正、林顯丞(2003)。淺論運動明星的價值。大專體育(65),103-108。
蘇皇瑋(2015)。棒球勝場貢獻值之研究-以中華職棒23年至25年為例(碩士學位論文)。國立臺灣師範大學,臺北市。
胡林煥、林華韋、吳忠政(2016)。中華職棒球隊經營效率研究。運動教練科學(44),47-55。
曹國雄(2000)。變動式薪資對薪資滿足的影響。中原學報,28(4):1-11。
陳光華、黃榮鵬(2005)。建構最佳的旅行業業務員薪資結構制度。戶外遊憩研究,18(4),69-92。
Albert, J., Glickman, M. E., Swartz, T. B., & Koning, R. H.(Eds.). (2017). Handbook of statistical methods and analyses in sports. Boca Raton, FL: CRC Press..
Annala, C. N., & Winfree, J. (2011). Salary distribution and team performance in Major League Baseball. Sport Management Review,14(2),167-175.
Balkin, D. B., & Gomez‐Mejia, L. R. (1990). Matching compensation and organizational strategies. Strategic Management Journal, 11(2), 153-169.
Berk, R. A. (2004). Regression analysis: A constructive critique. Thousand Oaks, CA: Sage..
Berri, D. J., Brook, S. L., & Schmidt, M. B. (2007). Does one simply need to score to score? International Journal of Sport Finance, 2(4), 190-205.
Berri, D. J., & Schmidt, M. B. (2013). On the evaluation of kickers in the National Football League. International Journal of Sport Finance, 8(4), 263-278.
Birrell, S. (1981). Sport as ritual: Interpretations from durkheim to goffman. Social Forces, 60(2), 354-376.
Burger, J. D., & Walters, S. J. K. (2003). Market Size, Pay, and Performance. Journal of Sports Economics, 4(2), 108-125.
Bowey, A., & Thorpe, R. (1989). Payment systems and performance improvement: Participation in payment system design. Employee Relations, 11(1), 17-20.
Bryson, A., Buraimo, B., & Simmons, R. (2011). Do salaries improve worker performance? Labour Economics, 18(4), 424-433.
Chuang, C. C., Chen, T. T., & Chen, C. C. (2018). Application of Grey Theory in the Construction of Impact Criteria and Prediction Model of Players’ Salary Structure. Mathematical Problems in Engineering, 2018, 1-9.
Costa, G. B., Huber, M. R., & Saccoman, J. T. (2009). Practicing sabermetrics: putting the science of baseball statistics to work. Jefferson, NC: McFarland & Company, Inc.
Davenport, C. (2004). About EqA. Baseball Prospectus.
De Myttenaere, A., Golden, B., Le Grand, B., & Rossi, F. (2016). Mean absolute percentage error for regression models. Neurocomputing, 192, 38-48.
Einolf, K. (2004). Is winning everything? A data envelopment analysis of Major League Baseball and National Football League. Journal of Sports Economics, 5(2), 127-151.
Hakes, J. K., & Sauer, R. D. (2006). An economic evaluation of the moneyball hypothesis. The Journal of Economic Perspectives, 20(3), 173-186.
Hakes, J. K., & Turner, C. (2011). Pay, Productivity and Aging in Major League Baseball. Journal of Productivity Analysis, 35(1), 61-74.
Hoban, M. (2007). Baseball's best: The true hall of famers - a mathematician examines the numbers. Bradenton, FL: Booklocker.com Incorporated..
Hoffman, M. G. (2014). Analysis of salary for major league baseball players (Unpublished master’s thesis), North Dakota State University, Fargo, North Dakota.
Houser, A. (2005). Which baseball statistic is the most important when determining team success? The Park Place Economist, 13, 29-36.
James, B. (2001). Introduction to win shares. SABR 31, Milwaukee, Wisconsin: Society for American Baseball Research..
James, B., & Henzler, J. (2002). Win shares. Morton Grove, IL: STATS Inc.
Jane, W.-J. (2010). Raising salary or redistributing it: A panel analysis of Major League Baseball. Economics Letters, 107(2), 297-299.
Keri, J., & Prospectus, B. (2007). Baseball between the numbers: Why everything you know about the game is wrong. New York, NY: Basic Books.
Kinnard, W. N., Geckler, M. B., & DeLottie, J. W. (1997). Team performance, attendance and risk for major league baseball stadiums: 1970-1994. Real Estate Issues, 22(1), 72-80.
Lanning, J. A. (2010). Productivity, discrimination, and lost profits during baseball's integration. The Journal of Economic History, 70(4), 964-988.
Lewis, C. D. (1982). Industrial and business forecasting methods: A practical guide to exponential smoothing and curve fitting. Lodon, UK: Butterworths Scientific.
Lewis, H. F., Sexton, T. R., & Lock, K. A. (2007). Player Salaries, Organizational Efficiency, and Competitiveness in Major League Baseball. Journal of Sports Economics, 8(3), 266-294. doi:10.1177/1527002506286776
Leeds, M. A., Sakata, S., & von Allmen, P. (2012). Labor Markets and National Culture: Salary Determination in Japanese Baseball. Eastern Economic Journal, 38(4), 479-494. doi:10.1057/eej.2011.25
Lin, H.-Y., & Yang, C.-H. (2016). Uncertainty, specific investment, and contract duration: evidence from the MLB player market. Empirical Economics, 50(3), 1009-1028. doi:10.1007/s00181-015-0963-6
Link, C. R., & Yosifov, M. (2012). Contract length and salaries compensating wage differentials in Major League Baseball. Journal of sports economics, 13(1), 3-19.
Magel, R., & Hoffman, M. (2015). Predicting salaries of Major League Baseball players. International Journal of Sports Science, 5(2), 51-58.
Meltzer, J. (2005). Average salary and contract length in major league baseball: When do they diverge? (Unpublished doctoral thesis). Stanford University, Stanford, California.
Mike, M., & Joel, M. (2009). The impact of salary dispersion and performance bonuses in NFL organizations. Management Decision, 47(1), 110-123.
Mills, B. M., & Salaga, S. (2011). Using tree ensembles to analyze National Baseball Hall of Fame voting patterns: an application to discrimination in BBWAA voting. Journal of Quantitative Analysis in Sports, 7(4).
Ng, K. (2017). Analyzing major league baseball player’s performance based on age and experience. Journal of Sports Economics & Management, 7(2), 78-100.
Nichol, M. (2012). Valuing professional Japanese baseball players and the role of statistics, economics, culture, and corporate governance. Journal of Japanese law, 17(33), 119-144.
Nicolas, S., Boris, H., Christophe, D., & Liliane, B. (2013). Determinants of professional sports firm values in the United States and Europe: A comparison between sports over the period 2004-2011. International Journal of Sport Finance, 8(4), 280-293.
Palmer, M., & King, R. (2006). Has salary discrimination really disappeared from Major League Baseball? Eastern Economic Journal, 32(2), 285-297.
Perry, D. (2004). Baseball prospectus basics: measuring offense. Baseball Prospectus. Retrieved from https://www.baseballprospectus.com/news/article/2562/baseball-prospectus-basics-measuring-offense/
Quirk, J., & Fort, R. D. (1992). Pay dirt: The business of professional team sports. NJ: Princeton University Press.
Rajabzadeh, R., Azimzadeh, S. M., Salimi, M., & Ghasemi, S. (2015). Study of status and comparison website content of football premier league clubs in Iran. European Journal of Experimental Biology, 5(12), 18-24.
Rau, B. L., & Feinauer, D. (2006). The role of internal agents in starting salary negotiations. Human Resource Management Review, 16(1), 47-66.
Schmidt, M. B., & Berri, D. J. (2002). Competitive balance and market size in Major League Baseball: A response to baseball's blue ribbon panel. [journal article]. Review of Industrial Organization, 21(1), 41-54.
Schumaker, R. P., Solieman, O. K., & Chen, H. (2010). Sports knowledge management and data mining. Annual Review of Information Science and Technology, 44(1), 115-157.
Sen, A. K., & Srivastava, M. S. (1990). Regression Analysis: Theory, Methods, and Applications. New York, NY: Springer-Verlag
Smith, L., & Downey, J. (2009). Predicting baseball hall of fame membership using a radial basis function network. Journal of Quantitative Analysis in Sports, 5(1), 1-21.
Small, G., & Wong, R. (2002, January). The validity of forecasting. In A Paper for Presentation at the Pacific Rim Real Estate Society International Conference, Christchurch, New Zealand.
Stankiewicz, K. (2009). Length of contracts and the effect on the performance of MLB players. The Park Place Economist, 17, 76-83.
Subekti, I., & Sumargo, D. K. (2015). Family management, executive compensation and financial performance of indonesian listed companies. Procedia - Social and Behavioral Sciences, 211, 578-584.
Watnik, M. R. (1998). Pay for play: Are baseball salaries based on performance? Journal of Statistics Education, 6(2).
Werner, S., & Mero, N. P. (1999). Fair or foul?: The effects of external, internal, and employee equity on changes in performance of Major League Baseball players. Human Relations, 52(10), 1291-1311.
White, M. H. and Sheldon, K. M. (2014). The contract year syndrome in the NBA and MLB: A classic undermining pattern. Motivation and Emotion, 38(2), 196–205.
William N Kinnard, J., Mary Beth, G., & Jake W, D. (1997). Team performance, attendance and risk for major league baseball stadiums: 1970-1994. Real Estate Issues, 22(1), 72-80.

 
 
 
 
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