| Beyond the selected completely at random assumption for learning from positive and unlabeled data J Bekker, P Robberechts, J Davis Joint European conference on machine learning and knowledge discovery in …, 2019 | 118 | 2019 |
| Choke or shine? Quantifying soccer players’ abilities to perform under mental pressure L Bransen, P Robberechts, J Van Haaren, J Davis Proceedings of the 13th MIT sloan sports analytics conference, 1-25, 2019 | 45 | 2019 |
| How data availability affects the ability to learn good xG models P Robberechts, J Davis Machine Learning and Data Mining for Sports Analytics: 7th International …, 2020 | 39 | 2020 |
| Valuing on-the-ball actions in soccer: a critical comparison of XT and VAEP T Decroos, J Davis Proceedings of the AAAI-20 Workshop on Artifical Intelligence in Team Sports …, 2020 | 37 | 2020 |
| A bayesian approach to in-game win probability in soccer P Robberechts, J Van Haaren, J Davis Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 33 | 2021 |
| Tibial acceleration-based prediction of maximal vertical loading rate during overground running: a machine learning approach R Derie, P Robberechts, P Van den Berghe, J Gerlo, D De Clercq, ... Frontiers in bioengineering and biotechnology 8, 33, 2020 | 33 | 2020 |
| Leaving goals on the pitch: Evaluating decision making in soccer M Van Roy, P Robberechts, WC Yang, L De Raedt, J Davis arXiv preprint arXiv:2104.03252, 2021 | 26 | 2021 |
| Valuing the art of pressing P Robberechts StatsBomb Innovation in Football Conference 11, 2019 | 22 | 2019 |
| Forecasting the FIFA World Cup–Combining result-and goal-based team ability parameters P Robberechts, J Davis Machine Learning and Data Mining for Sports Analytics: 5th International …, 2019 | 19 | 2019 |
| Who will win it? An in-game win probability model for football P Robberechts, J Van Haaren, J Davis arXiv preprint arXiv:1906.05029 4, 2019 | 18 | 2019 |
| Predicting gait events from tibial acceleration in rearfoot running: a structured machine learning approach P Robberechts, R Derie, P Van den Berghe, J Gerlo, D De Clercq, ... Gait & Posture 84, 87-92, 2021 | 16 | 2021 |
| Query log analysis: Detecting anomalies in DNS traffic at a TLD resolver P Robberechts, M Bosteels, J Davis, W Meert ECML PKDD 2018 Workshops: DMLE 2018 and IoTStream 2018, Dublin, Ireland …, 2019 | 15 | 2019 |
| Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned. J Davis, L Bransen, L Devos, W Meert, P Robberechts, J Van Haaren, ... EBeM@ IJCAI, 2022 | 13 | 2022 |
| un-xPass: Measuring Soccer Player's Creativity P Robberechts, M Van Roy, J Davis Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and …, 2023 | 11 | 2023 |
| Automating feature construction for multi-view time series data A De Brabandere, P Robberechts, T Op De Beéck, J Davis ECMLPKDD Workshop on Automating Data Science, 1-16, 2019 | 11 | 2019 |
| A Markov framework for learning and reasoning about strategies in professional soccer M Van Roy, P Robberechts, WC Yang, L De Raedt, J Davis Journal of Artificial Intelligence Research 77, 517-562, 2023 | 10 | 2023 |
| Learning a markov model for evaluating soccer decision making M Van Roy, P Robberechts, WC Yang, L De Raedt, J Davis Reinforcement Learning for Real Life (RL4RealLife) Workshop at ICML 2021, 2021 | 10 | 2021 |
| Measuring the effectiveness of pressing in soccer S Merckx, P Robberechts, Y Euvrard, J Davis Workshop on Machine Learning and Data Mining for Sports Analytics, 2021 | 9 | 2021 |
| Wannesm/Dtaidistance: v2. 3.5 K Wannesm, A Yurtman, P Robberechts, D Vohl, E Ma, G Verbruggen, ... Zenodo: Genève, Switzerland, 2022 | 8 | 2022 |
| Dtaidistance (version v2) TVCPRW Meert, K Hendrickx, T Van Craenendonck, P Robberechts last Accessed, 04-14, 2023 | 5 | 2023 |
