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Authors: Keven Richly ; Tobias Rohloff ; Max Bothe and Christian Schwarz

Affiliation: University of Potsdam, Germany

Keyword(s): Football Analytics, Event Recognition, Spatio-Temporal Football Data, Supervised Machine Learning.

Abstract: In the world of football, performance analytics about a player’s skill level and the overall tactics of a match are supportive for the success of a team. These analytics are based on positional data on the one hand and events about the game on the other hand. The positional data of the ball and players is tracked automatically by cameras or via sensors. However, the events are still captured manually, which is time-consuming and error-prone. Therefore, this paper introduces an approach to identify compound events by analyzing the positional data of football matches. We trained and aggregated the machine learning algorithms Support Vector Machine, KNearest Neighbors and Random Forest, based on features, which were calculated on the basis of the positional data. To validate the feasibility of our approach we evaluated the quality of the results by comparing recall and precision. We demonstrated that it is possible to detect compound events from spatio-temporal football data. Neverthele ss, the choice of a specific algorithm has a significant impact on the quality of the predicted results. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Richly, K.; Rohloff, T.; Bothe, M. and Schwarz, C. (2016). Recognizing Compound Events in Spatio-Temporal Football Data. In Proceedings of the International Conference on Internet of Things and Big Data - IoTBD; ISBN 978-989-758-183-0, SciTePress, pages 27-35. DOI: 10.5220/0005877600270035

@conference{iotbd16,
author={Keven Richly. and Tobias Rohloff. and Max Bothe. and Christian Schwarz.},
title={Recognizing Compound Events in Spatio-Temporal Football Data},
booktitle={Proceedings of the International Conference on Internet of Things and Big Data - IoTBD},
year={2016},
pages={27-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005877600270035},
isbn={978-989-758-183-0},
}

TY - CONF

JO - Proceedings of the International Conference on Internet of Things and Big Data - IoTBD
TI - Recognizing Compound Events in Spatio-Temporal Football Data
SN - 978-989-758-183-0
AU - Richly, K.
AU - Rohloff, T.
AU - Bothe, M.
AU - Schwarz, C.
PY - 2016
SP - 27
EP - 35
DO - 10.5220/0005877600270035
PB - SciTePress