Tom Decroos
Impact in
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- Sports Performance and Training
- Economics and Econometrics top 10%
- Sports Analytics and Performance
Papers in
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- Sports Analytics and Performance 10
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- Time Series Analysis and Forecasting 6
- Co-authors
- Jesse Davis (12 shared papers)Jan Van Haaren (7 shared papers)Kurt Schütte (1 shared paper)Benedicte Vanwanseele (1 shared paper)Nick Vannieuwenhoven (1 shared paper)Patrick De Causmaecker (1 shared paper)Bart Demoen (1 shared paper)
- Journals
- Lecture notes in computer science (3 papers)Communications in computer and information science (1 paper)Advances in intelligent systems and computing (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Lirias (KU Leuven) (7 papers)
- Partner nations
- Belgium
In The Last Decade
Tom Decroos
14 papers receiving 183 citations
Peers
Comparison fields: 5 of 41
- Orthopedics and Sports Medicine 84
- Economics and Econometrics 142
- Signal Processing 57
- Computer Vision and Pattern Recognition 69
- Life-span and Life-course Studies 2
Countries citing papers authored by Tom Decroos
This map shows the geographic impact of Tom Decroos's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tom Decroos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Decroos more than expected).
Fields of papers citing papers by Tom Decroos
This network shows the impact of papers produced by Tom Decroos. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tom Decroos. The network helps show where Tom Decroos may publish in the future.
Co-authors
The 7 scholars most cited alongside Tom Decroos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 57 | |
| 2 | 2017 | 34 | |
| 3 | 2020 | 23 | |
| 4 | 2020 | 20 | |
| 5 | 2019 | 12 | |
| 6 | 2021 | 11 | |
| 7 | STARSS: A Spatio-Temporal Action Rating System for Soccer. | 2017 | 10 |
| 8 | Predicting the Potential of Professional Soccer Players. | 2017 | 8 |
| 9 | Soccer Analytics Meets Artificial Intelligence: Learning Value and Style from Soccer Event Stream Data | 2020 | 7 |
| 10 | 2020 | 5 | |
| 11 | 2019 | 2 | |
| 12 | 2015 | 1 | |
| 13 | Characterizing soccer players’ playing style from match event streams | 2018 | 1 |
| 14 | How does context affect player performance in football | 2020 | 1 |
About Tom Decroos
Tom Decroos is a scholar working on Economics and Econometrics, Signal Processing, Computer Vision and Pattern Recognition, Orthopedics and Sports Medicine and Artificial Intelligence, having authored 14 papers that have together received 192 indexed citations. Recurring topics across this work include Sports Analytics and Performance (10 papers), Time Series Analysis and Forecasting (6 papers), Sports Performance and Training (5 papers), Video Analysis and Summarization (3 papers), Human Pose and Action Recognition (2 papers), Sports, Gender, and Society (2 papers), Anomaly Detection Techniques and Applications (2 papers) and VLSI and FPGA Design Techniques (1 paper). The work is most often cited by research in Orthopedics and Sports Medicine (84 citations), Economics and Econometrics (142 citations), Signal Processing (57 citations), Computer Vision and Pattern Recognition (69 citations) and Life-span and Life-course Studies (2 citations). Tom Decroos has collaborated with scholars based in Belgium. Frequent co-authors include Jesse Davis, Jan Van Haaren, Kurt Schütte, Benedicte Vanwanseele, Nick Vannieuwenhoven, Patrick De Causmaecker and Bart Demoen. Their work appears in journals such as Lecture notes in computer science, Communications in computer and information science, Advances in intelligent systems and computing, Proceedings of the AAAI Conference on Artificial Intelligence and Lirias (KU Leuven).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.