研究生: |
張亞森 Zhang, Ya-Sen |
---|---|
論文名稱: |
從攻守數據分析籃球比賽之勝負,以奧運、世界盃為例 Analyzing the Outcome of Basketball Games from BOXSCORE, Taking the Olympics and the World Cup as Examples |
指導教授: |
朱文增
Chu, Wen-Tseng |
口試委員: |
李建興
Li, Jian-Xing 黃煜 Huang, Yu 朱文增 Chu, Wen-Tseng |
口試日期: | 2023/06/09 |
學位類別: |
碩士 Master |
系所名稱: |
運動休閒與餐旅管理研究所 Graduate Institute of Sport, Leisure and Hospitality Management |
論文出版年: | 2023 |
畢業學年度: | 111 |
語文別: | 中文 |
論文頁數: | 173 |
中文關鍵詞: | 奧運會 、世界盃 、攻守數據分析 、球權 、籃球 |
英文關鍵詞: | Olympics, Basketball World Cup, Statistical Analysis, Possession, Basketball |
研究方法: | 次級資料分析 |
DOI URL: | http://doi.org/10.6345/NTNU202301622 |
論文種類: | 學術論文 |
相關次數: | 點閱:139 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
奧運會與世界盃被視為體育界最高等級的短期賽事,球隊必須在較短的時間內磨合,而教練亦須參考攻守數據分析,瞭解球隊優勢與劣勢,並以此設計相應的戰術。對於競爭激烈的短期賽事而言,奧運會與世界盃的攻守數據分析則最具代表性。目的:瞭解2016里約奧運會、2020東京奧運會,2014世界盃、2019世界盃單節與全場比賽之攻守數據。並探討攻守數據在單節比賽與全場比賽不同進攻節奏的差異,以及攻守數據影響比賽勝負的情形。方法:描述性統計、k平均數集群分析、獨立樣本t檢定、單因子變異數分析與邏輯斯迴歸分析。結果:攻守數據在不同進攻節奏下產生顯著差異,顯示出在不同的節奏下單節與全場比賽表現存在差異,而這些差異也進一步呈現出現代籃球節奏逐漸加快的趨勢。防守籃板、抄截、失誤轉換得分以及最大領先分數則會顯著影響比賽勝負。這些數據不僅反應了球隊的表現,更關係著在場上的選擇與執行,從而決定了比賽的最終結果。結論:透過更多的防守籃板、抄截以及利用對手失誤,能夠打出更多進攻機會,藉由靠近籃框的攻擊,有效提升得分效率,並透過拉開分數來提高獲勝機會。應全面提升球員的個人技術、強化團隊默契、挑選適合球員,並注重攻守數據分析應用和健康管理,以上這些方法將有助於幫助國家隊在短期且競爭激烈的比賽中獲得勝利。
The Olympic Games and the World Cup are regarded as the pinnacle short-term sporting events in the world of sports, with each country sending their best athletes to compete, intensifying the level of competition in these events. Teams must quickly integrate within a shorter period of time, and coaches must refer to offensive and defensive data analysis to understand the team's strengths and weaknesses, designing corresponding tactics based on this analysis. For fiercely competitive short-term events, the offensive and defensive data analysis of the Olympic Games and the World Cup is most representative. Purpose:The aim of this study was to comprehend the offensive and defensive data from the 2016 Rio Olympics, 2020 Tokyo Olympics, 2014 World Cup, and 2019 World Cup. Furthermore, it sought to explore the disparities in offensive and defensive data between single quarters and entire games, as well as the impact of these data on match outcomes. Method:Various statistical techniques were employed, including descriptive statistics, k-means cluster analysis, independent samples t-tests, one-way analysis of variance (ANOVA), and logistic regression analysis. Result:The findings indicated substantial disparities in offensive and defensive data under different offensive tempos. This suggested differences in performance between single quarters and full games under varying rhythms, and these variances further exhibited the prevailing trend of modern basketball games becoming progressively faster-paced. Defensive rebounds, steals, points scored from turnovers, and the largest lead score significantly influenced match outcomes. These data not only mirrored team performance but also influenced decision-making and execution on the court, ultimately determining the culmination of the match. Conclusion:Generating more offensive opportunities through increased defensive rebounds, steals, and capitalizing on opponent turnovers allowed teams to enhance scoring efficiency. Employing an attacking strategy near the basket effectively boosted scoring efficiency and widening the point differential to heighten the likelihood of victory. To excel in short-term and fiercely competitive matches, a comprehensive approach encompassing players' individual skill enhancement, fortified team cohesion, appropriate player selection, and a focus on the application of offensive and defensive data analysis and health management was essential. These methods contributed to aiding national teams in securing triumphs in short-term and highly competitive matches.
李春欣、李致美 (2015)。利用人工類神經網路建構臺灣大專籃球運動聯賽勝隊預測模式之研究-以99學年度至101學年度大專甲二級女子籃球聯賽為例。休閒運動健康評論,6(1),2-14。https://www.airitilibrary.com/Publication/alDetailedMesh?docid=a0000591-201506-201601070008-201601070008-2-14
林雅俐、林宜劭 (2014)。美國籃球聯盟比賽勝負之關鍵因素採礦研究。觀光與休閒管理期刊,2,95-103。http://doi.org10.6510/JTLM.2(S).09
陳宥杰 (2021)。籃球攻守數據分析勝負關鍵因素-以美國職籃為例 [未出版碩士論文]。國立臺灣體育運動大學。
蘇昱禎 (2020)。預測 NBA 隊伍能否進季後賽之結果 [未出版碩士論文]。國立屏東大學。
Almeida, M. B., Canuto, S. C., Lima, G. S., & Oliveira, W. G. (2022). Performance Analysis in Elite Basketball Differentiating Game Outcome And Gender. European Journal of Human Movement, 49(1), 105-117. https://doi.org/10.21134/eurjhm.2022.49.7
Baghal, T. (2012). Are the" four factors" indicators of one factor? an application of structural equation modeling methodology to NBA data in prediction of winning percentage. Journal of Quantitative Analysis in Sports, 8(1), 1-14. https://doi.org/10.1515/1559-0410.1355
Breard, J. (2017, September 22). The Dream that Came True: The Story of the 1992 US Olympic Basketball “Dream Team”. StMU Research Scholars. Retrieved September 22, 2022, from https://stmuscholars.org/the-dream-that-came-true-the-story-of-the-1992-us-olympic-basketball-dream-team/
Cabarkapa, D., Deane, M. A., Fry, A. C., Jones, G. T., Cabarkapa, D. V., Philipp, N. M., & Yu, D. (2022). Game statistics that discriminate winning and losing at the NBA level of basketball competition. Plus One, 17(8), 1-12. https://doi.org/10.1371/journal.pone.0273427
Csataljay, G., O’Donoghue, P., Hughes, M., & Dancs, H. (2009). Performance indicators that distinguish winning and losing teams in basketball. International Journal of Performance Analysis in Sport, 9(1), 60-66. https://doi.org/10.1080/24748668.2009.11868464
Csataljay, G., Hughes, M., James, N., & Dancs, H. (2011). Pace as an influencing factor in basketball. Research Methods and Performance Analysis, 7(2), 178-187. https://www.researchgate.net/publication/303238844_Pace_as_an_influencing_factor_in_basketball
Çene, E. (2018). What is the difference between a winning and a losing team: insights from Euroleague basketball. International Journal of Performance Analysis in Sport, 18(1), 55-68. https://doi.org/10.1080/24748668.2018.1446234
Courel, J., Suárez, E., Ortega, E., Piñar, M., & Cárdenas, D. (2013). Is the inside pass a performance indicator ? Observational analysis of elite basketball teams. Revista de Psicologia del Deporte, 22(1), 191-194. https://ddd.uab.cat/record/114124
Fédération Internationale de Basketball (n.d.a). 2014 FIBA Basketball World Cup. FIBA basketball. Retrieved September 22, 2022, from https://www.fiba.basketball/basketballworldcup/2014
Fédération Internationale de Basketball (n.d.b). 2019 FIBA Basketball World Cup. FIBA basketball. Retrieved September 22, 2022, from https://www.fiba.basketball/basketballworldcup/2019
Fédération Internationale de Basketball (n.d.c). Rio 2016 - Olympic Basketball Tournament (Men) – FIBA. FIBA basketball. Retrieved September 22, 2022, from https://www.fiba.basketball/olympics/2016
Fédération Internationale de Basketball (n.d.d). Tokyo 2020 Men's Olympic Basketball Tournament – FIBA. FIBA basketball. Retrieved September 22, 2022, from https://www.fiba.basketball/olympics/2020
Fédération Internationale de Basketball (n.d.e). History - FIBA.basketball. FIBA basketball. Retrieved September 22, 2022, from https://www.fiba.basketball/history
Fédération Internationale de Basketball (2012, January 26). PR N°1 - FIBA Basketball World Cup officially launched in Madrid. FIBA basketball. https://www.fiba.basketball/basketballworldcup/2014/news/PR-N-1-FIBA-Basketball-World-Cup-officially-launche
FLASHSCORE (n.d.a). FLASHSCORE BASKETBALL. FLASHSCORE. Retrieved September 22, 2022, from https://www.flashscore.com/basketball/
FLASHSCORE (n.d.b). FIBA 2019 World Cup. FLASHSCORE. Retrieved September 22, 2022, from https://www.flashscore.com/match/Kz62FHwQ/#/match-summary/match-statistics/1
FIBA 2019 World Cup. (n.d.a). FIBA BOXSCORE. FIBA 2019 World Cup. Retrieved September 22, 2022, from https://www.fiba.basketball/basketballworldcup/2019/game/3108/Angola-Serbia#|tab=boxscore
FIBA 2019 World Cup. (n.d.b). FIBA TEAM COMPARISON. FIBA 2019 World Cup. Retrieved September 22, 2022, from https://www.fiba.basketball/basketballworldcup/2019/game/3108/Angola-Serbia#|tab=team_comparison
García, J., Ibáñez, S. J., De Santos, R. M., Leite, N., & Sampaio, J. (2013). Identifying basketball performance indicators in regular season and playoff games. Journal of Human Kinetics, 36, 163-170. https://doi.org/10.2478/hukin-2013-0016
Grama, V., Manasses, I., & Maroti, Ş. (2010). Evolution of the men’s Olympic basketball tournaments using a geographical perspective. Palestrica of the third Millennium - Civilization and Sport, 16(2), 176-179. https://doi.org/10.26659/pm3
Huang, F., & Hong, F. (2015). Globalization and the governance of Chinese sports: the case of professional basketball. The International Journal of the History of Sport, 32(8), 1030-1043. https://doi.org/10.1080/09523367.2015.1035261
Ibáñez, S. J., Sampaio, J., Feu, S., Lorenzo, A., Gómez, M. A., & Ortega, E. (2008). Basketball game-related statistics that discriminate between teams’ season-long success. European Journal of Sport Science, 8(6), 369-372. https://doi.org/10.1080/17461390802261470
Junior, D. R. (2004). Statistical analysis of basketball performance indicators according to home/away games and winning and losing teams. Journal of Human Movement Studies, 47(4), 327-336. https://www.researchgate.net/publication/266384715_Statistical_analysis_of_basketball_performance_indicators_according_to_homeaway_games_and_winning_and_losing_teams
Leicht, A. S., Gómez, M. A., & Woods, C. T. (2017a). Explaining match outcome during the men’s basketball tournament at the Olympic Games. Journal of Sports Science & Medicine, 16(4), 468-473. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5721175/
Leicht, A. S., Gomez, M. A., & Woods, C. T. (2017b). Team performance indicators explain outcome during women’s basketball matches at the Olympic Games. Sports, 5(4), 96-103. https://doi.org/10.3390/sports5040096
Madarame, H. (2017). Game-related statistics which discriminate between winning and losing teams in Asian and European men’s basketball championships. Asian Journal of Sports Medicine, 8(2), 1-6. https://doi.org/10.3390/sports5040096
Mandić, R., Jakovljević, S., Erčulj, F., & Štrumbelj, E. (2019). Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000 to 2017. Plus One, 14(10), 1-17. https://doi.org/10.1371/journal.pone.0223524
Miljković, D., Gajić, L., Kovačević, A., & Konjović, Z. (2010). The use of data mining for basketball matches outcomes prediction. IEEE 8th International Symposium on Intelligent Systems and Informatics, 309-312. https://doi.org/10.1109/SISY.2010.5647440
Milanović, D., Uzelac, N., & Šalaj, S. (2019). Game Efficency Indicators of Olympic Basketball Performance. Acta Kinesiologica, 13(1), 17-21. https://www.semanticscholar.org/paper/GAME-EFFICIENCY-INDICATORS-OF-OLYMPIC-BASKETBALL-Milanovic-Uzelac/762dacf3218ac920a6c76251f546f43d27b2c509#citing-papers
Mateus, N., Gonçalves, B., Abade, E., Leite, N., Gomez, M. A., & Sampaio, J. (2018). Exploring game performance in NBA playoffs. Kinesiology, 50(1), 89-96. https://hrcak.srce.hr/ojs/index.php/kinesiology/article/view/6323
Mikołajec, K., Maszczyk, A., & Zając, T. (2013). Game indicators determining sports performance in the NBA. Journal of Human Kinetics, 37(1), 145-151. https://doi.org/10.2478/hukin-2013-0035
Oliver, D. (2004). Basketball on paper: rules and tools for performance analysis. Potomac Books.
Özmen, M. U. (2016). Marginal contribution of game statistics to probability of winning at different levels of competition in basketball: Evidence from the Euroleague. International Journal of Sports Science & Coaching, 11(1), 98-107. https://doi.org/10.1177/1747954115624828
Peter, N (2023, June 28). History of basketball at Olympics: A tale of American domination. Olympics. https://olympics.com/en/news/olympic-basketball-history-dream-team-usa-soviet-union
Pojskić, H., Šeparović, V., & Užičanin, E. (2009). Differences between successful and unsuccessful basketball teams on the final Olympic tournament. Acta Kinesiologica, 3(2), 110-114. https://www.researchgate.net/publication/255719952_DIFFERENCES_BETWEEN_SUCCESSFUL_AND_UNSUCCESSFUL_BASKETBALL_TEAMS_ON_THE_FINAL_OLYMPIC_TOURNAMENT
Puente, C., Coso, J. D., Salinero, J. J., & Abián-Vicén, J. (2015). Basketball performance indicators during the ACB regular season from 2003 to 2013. International Journal of Performance Analysis in Sport, 15(3), 935-948. https://doi.org/10.1080/24748668.2015.11868842
Romarís, I. U., Refoyo, I., & Coterón, J. (2012). The completion of the possessions in basketball: study of the completion action. Cuadernos de Psicología del Deporte, 12(1), 45-49. https://www.researchgate.net/publication/316255942_The_completion_of_the_possessions_in_basketball_Study_of_the_completion_action
Refoyo, I., Romarís, I. U., & Sampedro, J. (2009). Analysis of men's and women's basketball fast-breaks. Revista de Psicología del deporte, 18(3), 439-444. https://www.researchgate.net/publication/290771736_Analysis_of_men's_and_women's_basketball_fast-breaks
Sampaio, J., & Janeira, M. (2003). Statistical analyses of basketball team performance: understanding teams’ wins and losses according to a different index of ball possessions. International Journal of Performance Analysis in Sport, 3(1), 40-49. https://doi.org/10.1080/24748668.2003.11868273
Sampaio, J., Lago, C., & Drinkwater, E. J. (2010). Explanations for the United States of America's dominance in basketball at the Beijing Olympic Games. Journal of Sports Sciences, 28(2), 147-152. https://doi.org/10.1080/02640410903380486
Štrumbelj, E., Vračar, P., Robnik-Šikonja, M., Dežman, B., & Erčulj, F. (2013). A decade of euroleague basketball: an Analysis of trends and recent rule change effects. Journal of Human Kinetics, 38, 183-189. https://doi.org/10.2478/hukin-2013-0058
Scanlan, T. A., Teramoto, M., Delforce, M., & Dalbo, J. V. (2016). Do better things come in smaller packages? Reducing game duration slows game pace and alters statistics associated with winning in basketball. International Journal of Performance Analysis in Sport, 16(1), 157-170. https://doi.org/10.1080/24748668.2016.11868878
Simović, S., Komić, J., Pajić, Z., Rađević, N., Guzina, B., & Grahovac, G. (2022). Modeling the influence of basketball game parameters on the final result in Tokyo 2020. Journal of Physical Education, 33(1), 3340. https://doi.org/10.4025/jphyseduc.v33i1.3340
Staffo, D. F. (1998). The Development of Professional Basketball in the United States,with an Emphasis on the History of the NBA to its 50th Anniversary Season in 1996-97. Physical Educator, 55(1), 9-18. https://0-www.proquest.com.opac.lib.ntnu.edu.tw/scholarly-journals/development-professional-basketball-united-states/docview/232989086/se-2
Stavropoulos, N. (2020). Relevant statistical observations in the basketball competitions of 2014 and 2019 Men's Basketball World Cups. Journal of Physical Education and Sport, 20(4), 1972-1983. https://doi.org/AAA10.7752/jpes.2020.04267
Sánchez, J. M., Castellanos, P., & Dopico, J. A. (2007). The winning production function: Empirical evidence from Spanish basketball. European Sport Management Quarterly, 7(3), 283-300. https://doi.org/10.1080/16184740701511177
Teramoto, M., & Cross, C. L. (2010). Relative importance of performance factors in winning NBA games in regular season versus playoffs. Journal of Quantitative Analysis in Sports, 6(3), 1-19. https://doi.org/10.2202/1559-0410.1260
USA Basketball (n.d.). 1936 RESULTS. 5x5 Men's Olympic History. Retrieved September 22, 2022, from https://www.usab.com/about/competitive-history-stats
Zhang, S., Gomez, M. Á., Yi, Q., Dong, R., Leicht, A., & Lorenzo, A. (2020). Modelling the relationship between match outcome and match performances during the 2019 FIBA Basketball World Cup: a quantile regression analysis. International Journal of Environmental Research and Public Health, 17(16), 5722. https://doi.org/10.3390/ijerph17165722