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Titlebook: Machine Learning and Data Mining for Sports Analytics; 8th International Wo Ulf Brefeld,Jesse Davis,Albrecht Zimmermann Conference proceedi

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31#
發(fā)表于 2025-3-26 21:13:40 | 只看該作者
32#
發(fā)表于 2025-3-27 04:23:33 | 只看該作者
33#
發(fā)表于 2025-3-27 06:16:26 | 只看該作者
Sensor-Based Performance Monitoring in?Track Cyclingormance assessment use cases. The first use case exposes imbalances within a madison rider pair, whereas the second use case employs power data to monitor the effort a single rider puts into the handsling.
34#
發(fā)表于 2025-3-27 13:18:31 | 只看該作者
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發(fā)表于 2025-3-27 23:49:53 | 只看該作者
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發(fā)表于 2025-3-28 04:12:29 | 只看該作者
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發(fā)表于 2025-3-28 08:19:03 | 只看該作者
Similarity of Football Players Using Passing Sequencescted from games from the top-5 European football leagues during the 2017/2018 season. We present two different approaches: first, we only count the motifs a player is involved in; then we also take into consideration the specific position a player occupies in each motif. We also present a new way to
40#
發(fā)表于 2025-3-28 12:00:18 | 只看該作者
The Interpretable Representation of Football Player Roles Based on Passing/Receiving Patternsr roles consisting of a linear combination of 12 common and interpretable passing/receiving patterns. Linear combinations are derived from the decomposition of players’ pitch passing and receiving networks using non-negative matrix factorization (NMF). Our model shows that 43. of the 1491 players st
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