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Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data

Alina Bialkowski, Patrick Lucey, Peter Carr, Yisong Yue, Sridha Sridharan, Iain Matthews
2014 2014 IEEE International Conference on Data Mining  
Although the collection of player and ball tracking data is fast becoming the norm in professional sports, large-scale mining of such spatiotemporal data has yet to surface.  ...  In this paper, given an entire season's worth of player and ball tracking data from a professional soccer league (≈400,000,000 data points), we present a method which can conduct both individual player  ...  Abstract-Although the collection of player and ball tracking data is fast becoming the norm in professional sports, large-scale mining of such spatiotemporal data has yet to surface.  ... 
doi:10.1109/icdm.2014.133 dblp:conf/icdm/BialkowskiLCYSM14 fatcat:ktbmqmakmbhjlaezfdh74gcm6y

A Survey of Content-Aware Video Analysis for Sports

Huang-Chia Shih
2018 IEEE transactions on circuits and systems for video technology (Print)  
Sports data analysis is becoming increasingly large-scale, diversified, and shared, but difficulty persists in rapidly accessing the most crucial information.  ...  Previous surveys have focused on the methodologies of sports video analysis from the spatiotemporal viewpoint instead of a content-based viewpoint, and few of these studies have considered semantics.  ...  Similarly, in [80] , a large-scale spatiotemporal data analysis on role discovery and overall team formation for an entire season of soccer player tracking data is presented; the entropy of a set of player  ... 
doi:10.1109/tcsvt.2017.2655624 fatcat:rwqzu46sgfb7tpkcav4ysmh6ae

Discovering Team Structures in Soccer from Spatiotemporal Data

Alina Bialkowski, Patrick Lucey, Peter Carr, Iain Matthews, Sridha Sridharan, Clinton Fookes
2016 IEEE Transactions on Knowledge and Data Engineering  
In team sports like soccer, utilising tracking data for analysis is challenging due to the dynamic and multi-agent nature of the data.  ...  The utility of the approach is demonstrated on a full season of player and ball tracking data from a professional soccer league consisting of over 21.5 million frames of player tracking data. . biometrics  ...  This misalignment of the tracking data must be overcome to discover the true structure of a team and to perform large-scale spatiotemporal team analysis.  ... 
doi:10.1109/tkde.2016.2581158 fatcat:6r2yda7bqjckzgfzk4znz2oil4

Modelling team performance in soccer using tactical features derived from position tracking data

F R Goes, M Kempe, J van Norel, K A P M Lemmink
2021 IMA Journal of Management Mathematics  
With the current study, we aimed to quantitatively assess tactical performance by abstracting a set of spatiotemporal features from the general offensive principles of play in soccer using position tracking  ...  We therefore conclude that using only position tracking data, we can provide valuable feedback to coaches about how their team is executing the various principles of play, and how these principles are  ...  The current study is the first large-scale study using position tracking data to support the analysis of tactical behaviour and subsequent decision-making in relation to strategy in professional soccer  ... 
doi:10.1093/imaman/dpab006 fatcat:dwwbxuzbazempfgbyytior5p44

SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer [article]

Javier Fernández
2020 arXiv   pre-print
We present a fully convolutional neural network architecture that is capable of estimating full probability surfaces of potential passes in soccer, derived from high-frequency spatiotemporal data.  ...  The flexibility of this architecture allows its adaptation to a great variety of practical problems in soccer.  ...  Experiments and Results Dataset We use tracking-data, and event-data from 740 English Premier League matches from the 2013/2014 and 2014/2015 season, provided by STATS LLC.  ... 
arXiv:2010.10202v1 fatcat:4pflw3byzbhuvnxxwlsr4d37ji

Soccer object motion recognition based on 3D convolutional neural networks

Jiwon Lee, Do-Won Nam, Wonyoung Yoo, Yoonhyung Kim, Minki Jeong, Changick Kim
2018 Communication Papers of the 2018 Federated Conference on Computer Science and Information Systems  
In the sports field, especially in soccer games, it is also attempting quantitative analysis of players and games through deep learning or big data analysis technique.  ...  Due to the development of video understanding and big data analysis research field using deep learning technique, intelligent machines have replaced the tasks that people performed in the past in various  ...  In general, quantitative analysis of soccer game is consist of three steps: multi-object tracking, event analysis, and tactical analysis.  ... 
doi:10.15439/2018f48 dblp:conf/fedcsis/LeeNYKJK18 fatcat:molstxs6mng7vojwz72mkjncma

A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions

Javier Fernández, Luke Bornn, Daniel Cervone
2021 Machine Learning  
This is, to our knowledge, the first EPV approach in soccer that uses this decomposition and incorporates the dynamics of the 22 players and the ball through tracking data.  ...  We show we can learn from spatiotemporal tracking data and obtain calibrated models for all the components of the EPV.  ...  This paper employs two frequently used data types in sports analytics: event data and spatiotemporal tracking data.  ... 
doi:10.1007/s10994-021-05989-6 pmid:34759466 pmcid:PMC8570314 fatcat:6t74le6auvcvbnnqlbvbw7p66e

Assessing team strategy using spatiotemporal data

Patrick Lucey, Dean Oliver, Peter Carr, Joe Roth, Iain Matthews
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  
In this paper, we give an overview of the types of analysis currently performed mostly with handlabeled event data and highlight the problems associated with the influx of spatiotemporal data.  ...  However, due to the continuous nature of the data and the lack of associated highlevel labels to describe it -this rich set of information has had very limited use especially in the analysis of a team's  ...  no spatiotemporal data (i.e. player or ball tracking information) has been used in their analysis yet.  ... 
doi:10.1145/2487575.2488191 dblp:conf/kdd/LuceyOCRM13 fatcat:evol4xgkgzegff5lby57hyswym

Identifying Team Style in Soccer Using Formations Learned from Spatiotemporal Tracking Data

Alina Bialkowski, Patrick Lucey, Peter Carr, Yisong Yue, Sridha Sridharan, Iain Matthews
2014 2014 IEEE International Conference on Data Mining Workshop  
We demonstrate the utility of our approach using an entire season of Prozone player tracking data from a top-tier professional soccer league.  ...  In this paper, we present a method which can accurately determine the identity of a team from spatiotemporal player tracking data.  ...  Having a method which can quantify these behaviors should be possible with the prevalence of spatiotemporal tracking data of player and ball movement being captured in most professional sports (e.g.,  ... 
doi:10.1109/icdmw.2014.167 dblp:conf/icdm/BialkowskiLCYSM14a fatcat:zgct6d2fbnbvhev5au4ymdrnsy

TechWare: Video-Based Human Action Detection Resources [Best of the Web

Junsong Yuan, Zicheng Liu
2010 IEEE Signal Processing Magazine  
Actions can be characterized by spatiotemporal patterns. Similar to the object detection, action detection finds the reoccurrences of such spatiotemporal patterns through pattern matching.  ...  The second type of interest point features is named dense and scale-invariant spatiotemporal interest point (DSI-STIP), which is developed by Willems et al.  ...  ., and a Fellow of the IEEE.  ... 
doi:10.1109/msp.2010.937496 fatcat:56rypucynneohale67doue3avy

The collection, analysis and exploitation of footballer attributes: A systematic review

Edward Wakelam, Volker Steuber, James Wakelam
2022 Journal of Sports Analytics  
We reviewed and considered the use of character trait attributes in the selected papers and discuss more formal approaches to their use.  ...  Focusing upon individual player performance analysis and prediction, we examined the body of research which considers different player attributes.  ...  Soccer from Spatiotemporal Data (Bialkowski et al., 2016) Transactions on Knowledge and Data Engineering Real time quantification of dangerousity in football using spatiotemporal tracking data (Link  ... 
doi:10.3233/jsa-200554 fatcat:kerf3jkppnhh3nhmyepvxhdpja

High-level representation sketch for video event retrieval

Yu Zhang, Xiaowu Chen, Liang Lin, Changqun Xia, Dongqing Zou
2016 Science China Information Sciences  
To test our approach, we collect a novel dataset of goal events in real soccer videos, which consists actions of multiple players and shows large variability in the evolution process of the events.  ...  To do this, event sketches are constructed on both the user queries and database videos, and compared under a novel graph-matching scheme based on data-driven Monta Carlo Markov chain (DDMCMC).  ...  Conflict of interest The authors declare that they have no conflict of interest.  ... 
doi:10.1007/s11432-015-5494-4 fatcat:ikakfwoxtzd4xn6bumuk7lspni

Explaining Soccer Match Outcomes with Goal Scoring Opportunities Predictive Analytics

Harm Eggels, Ruud van Elk, Mykola Pechenizkiy
2016 European Conference on Principles of Data Mining and Knowledge Discovery  
The expected result of a soccer match is determined by estimating the probability of scoring for the individual goal scoring opportunities.  ...  In elite soccer, decisions are often based on recent results and emotions. In this paper, we propose a method to determine the expected winner of a match in elite soccer.  ...  [12] ; the data from the soccer game FIFA is extracted from the web; and 3) spatiotemporal data about players tracked by Inmotio during matches with the help of cameras.  ... 
dblp:conf/pkdd/EggelsEP16 fatcat:og5ap4jizfbd3jly3qkelovenq

Distance Between Players During a Soccer Match: The Influence of Player Position

David Garrido, Daniel R. Antequera, Roberto López Del Campo, Ricardo Resta, Javier M. Buldú
2021 Frontiers in Psychology  
In this study, we analyse the proximity between professional players during a soccer match.  ...  Specifically, we are concerned about the time a player remains at a distance to a rival that is closer than 2 m, which has a series of consequences, from the risk of contagion during a soccer match to  ...  “Large-scale analysis of soccer matches using spatiotemporal tracking data,” in 2014 IEEE International Conference on Data Mining , 725–730.  ... 
doi:10.3389/fpsyg.2021.723414 pmid:34489828 pmcid:PMC8417069 fatcat:ikobvmqhs5gotbvph45wnkbffe

Towards Understanding the Analysis, Models, and Future Directions of Sports Social Networks

Zhongbo Bai, Xiaomei Bai, Hang-Hyun Jo
2022 Complexity  
With the rapid growth of information technology and sports, a large amount of sports social network data has emerged.  ...  Thirdly, we present and compare different sports social network models that have been used for sports social network analysis, modeling, and prediction.  ...  Based on the tactical features of position tracking data, a team performance model is proposed to assess the relationship between tactical behavior and match performance in the professional soccer match  ... 
doi:10.1155/2022/5743825 fatcat:vad6yfyzwfd5dklyo74ecsamqe
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