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| Title: | 頂尖女子網球選手比賽數據及勝負因素分析－以大坂直美為例
The Analysis of Gaming Statistics and Winning Factors for Top Women Tennis Professional Players- Take Naomi Osaka for Example |
| Authors: | 劉記帆
Liu, Chi-Fan
莊哲偉
Chuang, Che-Wei |
| Contributors: | 政大體育研究 |
| Keywords: | 比賽數據 ;贏球率 ;多元逐步迴歸
gaming statistics ;winning rate ;multiple stepwise regression |
| Date: | 2019-12 |
| Issue Date: | 2022-04-08 11:50:15 (UTC+8) |
| Abstract: | 目的：探討大坂直美在2018-2020年在WTA賽事及四大滿貫賽之比賽數據及勝負因素分析。方法：以Microsoft Office Excel 2013進行資料統計，以描述性統計呈現各項數據表現之情形，並以獨立樣本t檢定分析勝敗場之差異情形，最後以多元逐步迴歸分析在各技術變項與比賽勝負之相關情形。結果：一、在比賽數據平均上以四大滿貫賽事之數據表現最佳為Ace率9.15%、雙發失誤率2.83%、一發進球率60.09%、一發贏球率73.43%、二發贏球率50.28%、破發點救回57.95%、接發球贏率44.79%、接一發贏率38.57%、接二發贏率55.24%及破發點贏率52.94%。二、在WTA賽事及四大滿貫賽事勝敗場之差異情形，在Ace率、一發贏球率、二發贏球率、接發球贏率、接一發贏率及接二發贏率皆達顯著差異，勝場皆優於敗場。三、在多元逐步迴歸分析結果中，接發贏率、一發贏率、雙誤率、破發點贏率、二發贏率之預測變數對勝負的整體解釋力為59.9%，其中在個別解釋力為接發贏率36.8%、一發贏率15.9%、雙誤率3.8%、破發點贏率1.8%及二發贏率1.6%。結論：一、在比賽數據表現上，發球局最高皆為一發贏球率達73%以上、接發球局表現最高皆為接二發贏率達55%以上。二、在勝敗場之差異情形上，贏球率之技術因子皆達顯著差異，顯示在比賽中贏球率大於進球率之重要性。三、在比賽勝負之相關情形上，接發贏率解釋力為36.8%最佳、其次為一發贏率15.9%，加總聯合預測力達52.7%，建議在訓練上可針對這2項技術為優先訓練目標。
Purpose: The study analyzes Naomi Osaka`s gaming statistics and winning factors in WTA and the Grand Slams tournaments from 2018 to 2020. Methods: With Microsoft Office Excel 2013 to sort the data, the statistics was shown by descriptive statistics. In addition, independent sample t test was used to analyze the difference between winning games and losing games. The relation between techniques variables and game results was analyzed by multiple stepwise regression analysis. Results: 1. On average of all the games, the statistics of the Grand Slams is the best with the ace rate of 9.15%, the double faults rate of 2.83%, the first serve in rate of 60.09%, the first serve points won rate of 73.43%, the second serve points won rate of 50.28%, the break point opportunities saved rate of 57.95%, the return points won rate of 44.79%, the first serve return points won rate of 38.57%, the second serve return points won rate of 55.24% and the break point opportunities converted rate of 52.94%. 2. With regard to the difference in winning and losing games in WTA and the Grand Slams tournaments, there is significant difference across the ace rate, the first serve points won rate, the second serve points won rate, the return points won rate, the first serve return points won rate and the second serve return points won rate. Winning games are better than losing games. 3. The result of multiple stepwise regression analysis shows that the explanatory power of the overall model is 59.9% in terms of the predictor variable of the return points won rate, the first serve points won rate, the double faults rate, the break point opportunities converted rate and the second serve points won rate to the victory and defeat. The individual explanatory power are return points won rate of 36.8%, the first serve points won rate of 15.9%, the double faults rate of 3.8%, the break point opportunities converted rate of 1.8% and the second serve points won rate of 1.6%. Conclusion: 1. The gaming statisitcs revealed that the first serve points won rate is above 73%, which is the highest in the serve games and the second serve return points won rate is above 55%, which is the best in the return games. 2. As for the difference of the decision of a game, the technique factors of winning rate is significantly different. It suggests that winning rate is more important than scoring rate. 3. For the relation of the decision of a game, the explanatory power of the return points won rate of 36.8% is the best and second comes the first serve points won rate of 15.9%. The added conjoint predicted power is 52.7%. Therefore, it is suggested that the two techniques should be the two main goals in the training. |
| Relation: | 政大體育研究, 26, 67+69 - 80 |
| Data Type: | article |
| DOI 連結: | https://doi.org/10.30411/CTTYYC.201912_(26).0006 |
| DOI: | 10.30411/CTTYYC.201912_(26).0006 |
| Appears in Collections: | [政大體育研究] 期刊論文
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