"Quality vs quantity": Improved shot prediction in soccer using strategic features from spatiotemporal data
In this paper, we present a method which accurately estimates the likelihood of chances in soccer using strategic features from an entire season of player and ball tracking data taken from a professional league. From the data, we analyzed the spatiotemporal patterns of the ten-second window of play before a shot for nearly 10,000 shots. From our analysis, we found that not only is the game phase important (i.e., corner, free-kick, open-play, counter attack etc.), the strategic features such as defender proximity, interaction of surrounding players, speed of play, coupled with the shot location play an impact on determining the likelihood of a team scoring a goal. Using our spatiotemporal strategic features, we can accurately measure the likelihood of each shot. We use this analysis to quantify the efficiency of each team and their strategy.
© Copyright 2015 MIT Sloan Sports Analytics Conference 2015. Published by MIT. All rights reserved.
| Subjects: | |
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| Notations: | sport games technical and natural sciences |
| Tagging: | Big Data Strategie |
| Published in: | MIT Sloan Sports Analytics Conference 2015 |
| Language: | English |
| Published: |
Boston
MIT
2015
|
| Online Access: | https://www.disneyresearch.com/publication/quality-vs-quantity-improved-shot-prediction-in-soccer-using-strategic-features-from-spatiotemporal-data/ |
| Pages: | 1-9 |
| Document types: | congress proceedings |
| Level: | advanced |