Real Time Quantification of Dangerousity in Football Using Spatiotemporal Tracking Data
Author
Abstract
Suggested Citation
DOI: 10.1371/journal.pone.0168768
Download full text from publisher
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Daniel Linke & Daniel Link & Martin Lames, 2020. "Football-specific validity of TRACAB’s optical video tracking systems," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-17, March.
- Bruno Gonçalves & Diogo Coutinho & Juliana Exel & Bruno Travassos & Carlos Lago & Jaime Sampaio, 2019. "Extracting spatial-temporal features that describe a team match demands when considering the effects of the quality of opposition in elite football," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-20, August.
- Stijn Baert & Simon Amez, 2018.
"No better moment to score a goal than just before half time? A soccer myth statistically tested,"
PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
- Baert, Stijn & Amez, Simon, 2016. "No Better Moment to Score a Goal than Just Before Half Time? A Soccer Myth Statistically Tested," IZA Discussion Papers 9980, Institute of Labor Economics (IZA).
- Ali Cakmak & Ali Uzun & Emrullah Delibas, 2018. "Computational Modeling Of Pass Effectiveness In Soccer," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-28, May.
- Valerio Ficcadenti & Roy Cerqueti & Ciro Hosseini Varde’i, 2023. "A rank-size approach to analyse soccer competitions and teams: the case of the Italian football league “Serie A"," Annals of Operations Research, Springer, vol. 325(1), pages 85-113, June.
- Plattfaut, Ralf & Koch, Julian, 2021. "Preserving the legacy – Why do professional soccer clubs (not) adopt innovative process technologies? A grounded theory study," Journal of Business Research, Elsevier, vol. 136(C), pages 237-250.
- Yurko Ronald & Matano Francesca & Richardson Lee F. & Granered Nicholas & Pospisil Taylor & Pelechrinis Konstantinos & Ventura Samuel L., 2020. "Going deep: models for continuous-time within-play valuation of game outcomes in American football with tracking data," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(2), pages 163-182, June.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0168768. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.