Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/151991
|
| Title: | 主場優勢對淨勝分之影響：以P-League為例
The Impact of Home-Court Advantage on Point Differential: Evidence from P-League Official Data |
| Authors: | 吳竹孟
WU, ZHU-MENG |
| Contributors: | 黃柏鈞
Huang, Po-Chun
吳竹孟
WU, ZHU-MENG |
| Keywords: | 運動經濟學
主場優勢
異質性分析
機器學習
因果森林
決策樹
Sport economic
Home advantage
Heterogeneity analysis
Machine learning
Causal forest
Decision tree |
| Date: | 2024 |
| Issue Date: | 2024-07-01 12:18:27 (UTC+8) |
| Abstract: | 本研究採用 P-League 2021-2022 和 2022-2023 賽季之官方網站的比賽記
錄和觀眾入場統計探討主場優勢與淨勝分及其他籃球數據的因果關係。本
文主要使用迴歸分析以及 Wager and Athey (2018) 提出之分析架構，透過
迴歸分析觀察主場優勢對各項統計數據 (如淨勝分、勝率) 的影響，再使用
因果森林方法處理高維度數據，檢驗異質性的處置效應。
首先，迴歸分析中，我們發現球隊在主場比賽，淨勝分平均會提高
3.5 分左右，勝率平均提高 8% 以上，交互作用的部分，在主場，勇士平均
會減少 2.020 次犯規，並提高二分命中率 4.240%，領航猿則增加 1.884 個
犯規、二分命中率下降 2.249%，鋼鐵人增加 1.366 個犯規，夢想家二分命
中率下降 0.476%。雖然整體上主場會為球隊帶來優勢，但主場優勢會根據
不同的球隊而改變，而非全體一致，甚至有些球隊在主場會表現更差。
接下來透過因果森林方法，我們發現觀眾、比賽間隔、球星數量和不
同球隊都會影響主場優勢的大小。觀眾越多，主場優勢越大；比賽間隔在
2-4 天之間，主場優勢最大；球星越多，主場優勢越小。
綜合分析上述兩種方法的分析結果，我們確立的主場優勢的存在，以
及其存在的原因和具體影響。雖然本文分析的是籃球上的主場優勢，但結
果可以延伸到其他種球類運動，進而讓球團思考如何經營球隊文化，以及
規劃球隊場館的建立，以最大化發揮自身球隊的主場優勢。
This study uses the official website’s game records and audience attendance
statistics of the P-League for the 2021-2022 and 2022-2023 seasons to explore the causal relationship between home advantage and net points as well
as other basketball statistics. This paper primarily employs regression analysis and the analytical framework proposed by Wager and Athey (2018) to
observe the impact of home advantage on various statistical data (such as net
points, winning percentage) through regression analysis, and then uses the
causal forest method to handle high-dimensional data to examine the heterogeneous treatment effects.
In the regression analysis, we found that teams playing at home on average increased their net points by more than 3.5 points and their winning
percentage by more than 8%. In terms of interaction effects, at home, the
Warriors on average committed 2.020 fewer fouls and increased their twopoint shooting percentage by 4.240%, while the Pilots increased their fouls
by 1.882 and decreased their two-point shooting percentage by 2.249%, and
the Steelers increased their fouls by 1.366, with the Dreamers experiencing a
decrease in their two-point shooting percentage by 0.476%. Although home
advantage generally benefits teams, it varies among different teams and is
not universally beneficial; indeed, some teams perform worse at home.
Next, using the causal forest method, we discovered that the number
of spectators, the interval between games, the number of star players, and
the specific teams all affect the magnitude of home advantage. The more
spectators, the greater the home advantage; the greatest home advantage is
observed when the interval between games is 2-4 days; the more star players
a team has, the smaller the home advantage.
By synthesizing the results of both methods, we confirm the existence
of home advantage, its causes, and its specific impacts. Although this analysis focuses on basketball, the results can be extended to other types of team
sports, thereby prompting teams to consider how to cultivate team culture
and plan the establishment of their venues to maximize their home advantage. |
| Reference: | Athey, S., Imbens, G. (2016). “Recursive partitioning for heterogeneous causal effects,” Proceedings of the National Academy of Sciences, 113(27), 7353-7360.
Balmer, N. J., Nevill, A. M., and Williams, A. M. (2001). “Home advantage in the Winter Olympics (1908-1998),” Journal of sports sciences, 19(2), 129-139.
Baumeister, R. F. (1984), “Choking under pressure: self-consciousness and paradoxical effects of incentives on skill-ful performance,” Journal of personality and social psychology, 46(3), 610–620.
Boudreaux, C. J., Sanders, S. D., and Walia, B. (2017), “A natural experiment to determine the crowd effect upon home court advantage,” Journal of Sports Economics, 18(7), 737-749.
Breiman, L., Friedman, J., Stone, C. J., and Olshen, R. A. (1984), “Classification and Regression Trees,” CRC press, 1234-1236.
Cao, Z., Price, J., and Stone, D. F. (2011), “Performance under pressure in the NBA,” Journal of Sports Economics, 12(3), 231–252.
Carron, A. V., Loughhead, T. M., and Bray, S. R. (2005), “The home advantage in sport competitions: Courneya and Carron’s (1992) conceptual framework a decade later,” Journal of sports sciences, 23(4), 395-407.
Clarke, S. R., Norman, J. M. (1995), “Home advantage of individual clubs in English soccer,” Journal of the Royal Statistical Society: Series D (The Statistician), 44(4), 509-521.
Cottrell, N. B., Wack. D. L., Sekerak, G. J., and Rittle, R. H. (1968), “Social facilitation of dominant responses by the presence of an audience and the
mere presence of others,“ Journal of personality and social psychology, 9(3), 245-250.
Courneya, K. S., Carron, A. V. (1992), “The home advantage in sport competitions: A literature review,” Journal of Sport & Exercise Psychology, 14(1), 13-27.
Dohmen, T.J. (2008), “Do professionals choke under pressure?,” Journal of economic behaviour & organization, 65(3-4), 636-653.
Downward, P., Jones, M. (2007), “Effects of crowd size on referee decisions: Analysis of the FA Cup.” Journal of sports sciences, 25(14), 1541-1545.
Wager, S., Athey, S. (2018), “Estimation and inference of heterogeneous treatment effects using random forests,” Journal of the American Statistical Association, 113(523), 1228-1242.
Harb-Wu, K., Krumer, A. (2019), “Choking under pressure in front of a supportive audience: Evidence from professional biathlon.” Journal of Economic Behaviour & Organization, 166, 246–262.
Harris, A. R., Roebber, P. J. (2019), “NBA team home advantage: Identifying key
factors using an artificial neural network,” PLoS One, 14(7), 1–9.
Hill, D. M., Hanton S., Matthews N., and Fleming S. (2010), “Choking in sport:A review.” International Review of Sport and Exercise Psychology, 3(1), 24–39.
Jehue, R., Street, D., and Huizenga, R. (1993), “Effect of time zone and game time changes on team performance: National Football League.” Medicine and science in sports and exercise, 25(1), 127-131.
Kotecki, J. (2014), “Estimating the effect of home court advantage on wins in the NBA,” The Park Place Economist, 22(1), 49–57.
Price, M., Yan, J. (2021), “The effects of the NBA COVID bubble on the NBA Playoffs: A case study for home-court advantage,“ American Journal of Undergraduate Research, 18(4), 13-15.
Nevill, A. M., Holder, R. L. (1999), “Home advantage in sport: An overview of studies on the advantage of playing at home,” Sports Medicine, 28(4), 221-236.
Nevill, A. M., Balmer, N. J., and Williams, A. M. (2002), “The influence of crowd noise and experience upon refereeing decisions in football,” Psychology of
sport and exercise, 3(4), 261-272.
Pace, A., Carron, A. V. (1992), “Travel and the home advantage,” Canadian journal of sport sciences, 17(1), 60-64.
Pollard, R. (2006), “Home advantage in soccer:Variations in its magnitude and a literature review of the inter-related factors associated with its existence,” Journal of Sport Behavior, 29(2), 169-189.
Recht, L. D., Lew, R. A., and Schwartz, W. J. (2003), “Baseball teams beaten by jet-lag,” Nature, 377(6550), 583-583.
Sanna, L. J., Shotland, R. L. (1990), “Valence of anticipated evaluation and social facilitation,” Journal of Experimental Social Psychology, 26(1), 82-92.
Snyder, E. E., Purdy, D. A. (1985), “The home advantage in collegiate basketball,” Sociology of sport journal, 2(4), 352-356.
Stefani, R. (2007), “Measurement and interpretation of home advantage,” Statistical thinking in sports, 215-228.
Sutter, M., Kocher, M. G. (2004), “Favoritism of agents - the case of referees’home bias,” Journal of Economic Psychology, 25(4), 461-469.
Taylor, S.E., Seeman, T.E., Eisenberger, N.I., Kozanian, T.A., Moore, A.N., and Moons, W.G. (2010), “Effects of a supportive or an unsupportive audience on biological and psychological responses to stress,” Journal of personality and social psychology, 98(1), 47-56.
Moskowitz, T., Wertheim, L. J. (2011), “Scorecasting: The hidden influences behind how sports are played and games are won,” Crown Archetype, 137-197.
Zajonc, R. B. (1965), “Social Facilitation: A solution is suggested for an old unresolved social psychological problem,” Science, 149(3681), 269-274.
Zajonc, R. B. (1980), “Compresence. Psychology of group influence,” Psychology of group influence, 35-60. |
| Description: | 碩士
國立政治大學
經濟學系
110258011 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110258011 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 801101.pdf | | 1360Kb | Adobe PDF | 0 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
