Research Article
[Retracted] Model for Evaluating the Technical and Tactical Effectiveness of Tennis Matches Based on Machine Learning
Table 3
List of effects of Federer’s game techniques and tactics.
| Match | S1 | S2 | S3 | S4 | S5 |
| 2017 Australian Open final | 0.9377 | 0.5413 | 0.4511 | 0.3311 | 0.3751 | 2017 Australian Open semifinals | 0.9377 | 0.5723 | 0.4067 | 0.3058 | 0.3216 | 2016 Australian Open semifinals | 0.9654 | 0.4523 | 0.3102 | 0.1864 | 0.2943 | 2015 year-end finals | 0.8891 | 0.6363 | 0.3146 | 0.1057 | 0.3479 | 2015 year-end finals and semifinals | 0.8321 | 0.6571 | 0.7512 | 0.3101 | 0.5021 | 2015 US Open finals | 0.8801 | 0.5253 | 0.3575 | 0.3407 | 0.4533 | 2015 US Open semifinals | 0.9297 | 0.7025 | 0.4167 | 0.3311 | 0.6666 | 2014 year-end finals and semifinals | 0.9742 | 0.5687 | 0.3078 | 0.3311 | 0.3687 | 2014 US Open semifinals | 0.9652 | 0.4653 | 0.3311 | 0.2396 | 0.3311 | 2014 Australian Open semifinals | 0.9611 | 0.4910 | 0.4801 | 0.2534 | 0.2754 | 2013 year-end finals and semifinals | 0.9375 | 0.5426 | 0.4517 | 0.3311 | 0.3751 | 2013 Australian Open semifinals | 0.9543 | 0.6356 | 0.2727 | 0.210 | 0.3001 |
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