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研究生: 卓致宇
Cho, Chih-Yu
論文名稱: 2023年大聯盟禁止守備佈陣是否影響拉打打者的表現?
How Do the 2023 MLB Defensive Shift Limits Impact the Performance of Pull-side Hitters?
指導教授: 林世昌
Lin, Eric S.
口試委員: Donald, Stephen G.
Donald, Stephen G.
Single, Louise E.
Single, Louise E.
曾雅雯
Tseng, Ya-Wen
祝若穎
Chu, Jo-Ying
學位類別: 碩士
Master
系所名稱: 科技管理學院 - 經營管理碩士在職專班
Business Administration
論文出版年: 2024
畢業學年度: 112
語文別: 英文
論文頁數: 25
中文關鍵詞: 棒球分析MLB規則變更守備佈陣拉打型打者場內球打擊率固定效應迴歸滾地球表現
外文關鍵詞: Baseball analytics, MLB rule changes, Defensive shift, Pull-side hitters, BABIP, Fixed effects regression, Ground ball performance
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  • 本研究調查了美國職業棒球大聯盟 (MLB) 2023 年限制守備佈陣規則對拉打型打者表現的影響。利用 2021 至 2023 年的面板數據,使用固定效應迴歸模型分析場內球打擊率(BABIP),並識別受規則變更影響的趨勢。分析著重於整體聯盟打擊表現和拉打型打者的具體表現。
    第一個模型檢查了打者表現的顯著趨勢變化是否與 2023 年多項規則變更相關。結果顯示,2021 和 2022 年間拉打型打者和非拉打型打者之間存在顯著的表現差距,這一差距在 2023 年縮小。在所有規則變更中,限制守備佈陣是最有可能是造成這一影響的原因,因為它降低了守備佈陣在面對拉打型打者時的優勢。
    第二個模型針對滾地球打擊表現和防守佈陣之間的關係進行探討。透過比較受佈陣和未受佈陣的滾地球表現,數據顯示守備佈陣顯著地降低了 2021 和 2022 年拉打型打者的表現。從數據中也觀察到2023 年限制守備佈陣規則的實施可能減輕了這些負面影響,支持了規則的改變影響拉打打者表現的假設。
    儘管兩個模型的目標和數據集不同,卻在兩組分析都發現2021 和 2022 年的總體表現趨勢皆略優於 2023 年,但拉打型打者在前兩年的表現卻不如 2023 年,這一發現呼應了限制守備佈陣會對拉打型打者表現產生正向影響的假設。
    然而,仍有若干無法被觀察的不確定因素潛在影響模型,如合約年份效應和面對防守佈陣的打擊策略變化所構成的限制。未來的研究應整合更多變量並完善模型以將這些動態因素納入考慮,更全面地了解規則變更的影響。此外,透過研究其他同時發生的規則變更(如限制投手出手時間和壘包大小改變)的影響,將可以更清晰地了解每項規則如何單獨或共同地對比賽及選手表現做出影響。


    This research investigates the impact of Major League Baseball's (MLB) 2023 defensive shift limit rule on the performance of pull-side hitters. Utilizing panel data from 2021 to 2023, fixed effects regression models were employed to analyze Batting Average on Balls in Play (BABIP) and discern trends influenced by the rule changes. The analysis focuses on overall league hitting performance and the specific performance of pull-side hitters.
    The first exercise examined whether notable trend changes in hitter performance were associated with the multiple rule changes in 2023. Results indicate a significant performance gap between pull-side hitters and non-pull-side hitters in 2021 and 2022, which narrowed in 2023. Among all the rule changes, the defensive shift limit is most likely to have caused this effect by reducing the strategic advantage previously held by defensive shifts against pull-side hitters.
    The second exercise explored the relationship between ground ball BABIP and defensive shifts. By comparing ground ball performance under shifted and non-shifted conditions, findings reveal that defensive shifts significantly decreased the performance of pull-side hitters in 2021 and 2022. The implementation of the shift limit rule in 2023 appears to have mitigated these negative effects, supporting the hypothesis that the rule change positively influenced hitter performance.
    Despite differing objectives and datasets, both exercises consistently reveal that the general performance trend in 2021 and 2022 showed notable variations compared to 2023, while pull-side hitters underperformed in the earlier years compared to 2023. This convergence of findings highlights the potential effect of defensive shift limits on pull-side hitter performance.
    However, several uncertain factors remain. Assumptions regarding the constancy of hitter traits over time and the exclusion of other potential influences, such as contract year effects and hitting strategy changes facing defensive shifts, pose limitations. Future work should integrate additional variables and refine models to account for these dynamic factors, offering a more comprehensive understanding of the rule changes' impact. Moreover, examining the effects of other concurrent rule changes, such as pitch timers and base sizes, will provide a clearer picture of how each rule individually and collectively influences the dynamics of the game.

    Table of Contents Chapter 1 Introduction 1 1.1 Research Motivation 1 1.2 Background 2 1.2.1 Baseball Game 2 1.2.2 Batter Types: Pull, Push, and Spray Hitters 2 1.2.3 Defensive Shift 2 1.2.4 The Emerge of Defensive Shift Limit 3 1.2.5 Batting Average on Ball In Play (BABIP) 4 Chapter 2 Literature Review 5 Chapter 3 Data Source and Research Method 8 3.1 Data Preparation 8 3.2 Data Collection 8 3.2.1 Dataset (1) - FanGraphs 8 3.2.2 Dataset (2) – Baseball Savant 9 3.3 Data Description 9 3.3.1 Dataset (1-1) 9 3.3.2 Dataset (1-2) 10 3.3.3 Dataset (2) 10 3.4 Research Design 10 3.5 Research Method 11 Chapter 4 Statistical Results 13 4.1 Exercise 1 13 4.2 Exercise 2 14 Chapter 5 Conclusion 16 5.1 Conclusion 16 5.2 Research Limitation and future work 16 References 18 Summary of the Statistics 20 List of Figures Figure 1: Illustrates the division of the infield by a designated baseline 19 List of Tables Table 1: Description of the variables 20 Table 2: Detail of Dataset 1 21 Table 3: Detail of Dataset 2 22 Table 4: Result of Exercise 1-1 23 Table 5: Result of Exercise 1-2 24 Table 6: Result of Exercise 2 25

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