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Network-based Measures for Predicting the Outcomes of Football Games

Paolo Cintia, Salvatore Rinzivillo, Luca Pappalardo
2015 European Conference on Principles of Data Mining and Knowledge Discovery  
We model a the game of a team as a network and extract simple network measures, showing the value of our approach on predicting the outcomes of a long-running tournament such as Italian major league.  ...  Standard approaches in evaluating and predicting team performance are based on history-related factors such as past victories or defeats, record in qualification games and margin of victory in past games  ...  We also must thank Max Pezzali and Edoardo Galeano for the useful suggestions about the nature of football.  ... 
dblp:conf/pkdd/CintiaRP15 fatcat:bf6voq3z3bfv5hb7nfmwtpvcxa

Sports Data Mining: Predicting Results for the College Football Games

Carson K. Leung, Kyle W. Joseph
2014 Procedia Computer Science  
Our approach makes predictions based on a combination of four different measures on the historical results of the games.  ...  In many real-life sports games, spectators are interested in predicting the outcomes and watching the games to verify their predictions.  ...  Acknowledgements This project is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Manitoba.  ... 
doi:10.1016/j.procs.2014.08.153 fatcat:cwk2axvudfbrvevusqelf5pzre

A New Application of Linear Modeling in the Prediction of College Football Bowl Outcomes and the Development of Team Ratings

Brady T West, Madhur Lamsal
2008 Journal of Quantitative Analysis in Sports (JQAS)  
have been proposed for predicting the outcomes of future football games.  ...  Building on this literature, the paper then presents a straightforward application of linear modeling in the development of a predictive model for the outcomes of college football bowl games, and identifies  ...  Some researchers (Ong and Flitman 1997; Pardee 1999) have considered applications of neural networks in an effort to predict future outcomes of football games, building networks based on past information  ... 
doi:10.2202/1559-0410.1115 fatcat:wcvavtywz5hmpkfqlugvdiqxoa

A Neuro-fuzzy Logic Model Application for Predicting the Result of a Football Match

Uzochukwu C. Onwuachu, Promise Enyindah
2022 European Journal of Electrical Engineering and Computer Science  
In this research, a Neuro-fuzzy logic model for forecasting the outcome of a football match is proposed.  ...  The results show that the Neurofuzzy logic technique is an effective tool for forecasting the outcome of a football match.  ...  [11] worked on fuzzy rules, neural networks, and genetic programming approaches to develop soft computing algorithms for predicting the outcome of football games.  ... 
doi:10.24018/ejece.2022.6.1.400 fatcat:xgihqwrrq5ggdbd7ozwt7irwzi

Professional Clubs as Platforms in Multi-Sided Markets in Times of COVID-19: The Role of Spectators and Atmosphere in Live Football

Elisa Herold, Felix Boronczyk, Christoph Breuer
2021 Sustainability  
Based on the presence of network effects, implications to sustainably adapting professional football clubs' business models based on stakeholders' different interests can be given.  ...  Thus, the main aims of this study are to examine the influence of missing in-stadium spectators for professional clubs by investigating network effects on (1) TV viewers' emotional arousal and (2) TV viewers  ...  KG for sponsoring the participants' incentives. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su13042312 fatcat:ydxjatmuobcy7gtm4x5co3wfpu

Prediction of Attendance Demand in European Football Games: Comparison of ANFIS, Fuzzy Logic, and ANN

Mehmet Şahin, Rızvan Erol
2018 Computational Intelligence and Neuroscience  
An artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS) models, and fuzzy rule-based system (FRBS) models are developed to predict the attendance demand in European football games  ...  Finally, the results emphasize that the proposed ANN model can be effectively used for prediction purposes.  ...  Conflicts of Interest e authors declare that there are no conflicts of interest regarding the publication of this article.  ... 
doi:10.1155/2018/5714872 pmid:30158960 fatcat:mcu7o4wwrfcr7b5bk34ytgance

Modeling of Football Match Outcomes with Expected Goals Statistic

Adan Partida, Anastasia Martinez, Cody Durrer, Oscar Gutierrez, Filippo Posta
2021 Journal of student research  
The use of a probabilistic model based solely on expected goals score statistic can provide some meaningful insight into forecasting the outcome of a football match and can develop useful betting strategies  ...  Our research examined the predictive capabilities of mathematical models that are solely based on the expected goal statistics obtained from a publicly available database. Method.  ...  The idea behind this approach to predicting football math outcomes is not new.  ... 
doi:10.47611/jsr.v10i1.1116 fatcat:566v56on6jhm5gs3hdm5yxknua

Learning the Value of Teamwork to Form Efficient Teams

Ryan Beal, Narayan Changder, Timothy Norman, Sarvapali Ramchurn
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Based on our model, we devise a number of network metrics to capture the contribution of interactions between agents.  ...  In this paper we describe a novel approach to team formation based on the value of inter-agent interactions.  ...  Acknowledgements This research is sponsored by the EPSRC NPIF doctoral training grant number EP/S515590/1.  ... 
doi:10.1609/aaai.v34i05.6192 fatcat:tb4vdt7wabglrh4aidbuyt3zz4

Automated Player Selection for Sports Team using Competitive Neural Networks

Rabah Al-Shboul, Tahir Syed, Jamshed Memon, Furqan Khan
2017 International Journal of Advanced Computer Science and Applications  
The use of data analytics to constitute a winning team for the least cost has become the standard modus operandi in club leagues, beginning from Sabermetrics for the game of basketball.  ...  This will help decide which team of 11 football players is best to play against a particular opponent, perform prediction of future matches and helps team management in preparing the team for the future  ...  ACKNOWLEDGEMENTS The authors appreciate support from M. Hani, M. Jhone, M. Raza.  ... 
doi:10.14569/ijacsa.2017.080859 fatcat:4zfujgzwu5gzff6pyhxmp7n6s4

The predictive power of ranking systems in association football

Jan Lasek, Zoltán Szlávik, Sandjai Bhulai
2013 International Journal of Applied Pattern Recognition  
We provide an overview and comparison of predictive capabilities of several methods for ranking association football teams. The main benchmark used is the official FIFA ranking for national teams.  ...  Being able to predict match outcomes better than the official method might have implications for, e.g., a team's strategy to schedule friendly games. general area of stochastic modelling and optimisation  ...  Acknowledgements The authors would like to thank Dr. Edward Feng for providing predictions which enabled to include his rating method into comparison.  ... 
doi:10.1504/ijapr.2013.052339 fatcat:ognqppunovapra3gibs5jzntju

Novel Architecture for Reducing Sports Injuries in Football

2021 International Journal of convergence in healthcare  
This paper proposes a novel architecture to reduce sports injury in the game of football.  ...  The inclusion of computer vision transforms the postures and gestures as semantic moves, which after processed using the proposed framework predicts the injury in advance depending upon the moves of the  ...  Then every part of the event recorded to enhance the footballplayer's outcome or predict for an injury beforehand.  ... 
doi:10.55487/ijcih.v1i1.5 fatcat:2zvqt26pqjb3rnznhnhxo4brxu

A network analysis of the 2010 FIFA world cup champion team play

Carlos Cotta, Antonio M. Mora, Juan Julián Merelo, Cecilia Merelo-Molina
2013 Journal of Systems Science and Complexity  
The effectiveness of the opposing team in negating the Spanish game is reflected in the change of several network measures over time, most importantly in drops of the clustering coefficient and passing  ...  A temporal analysis of the resulting passes network is also done, looking at the number of passes, length of the chain of passes, and to network measures such as player centrality and clustering coefficient  ...  It is quite clear that football is a game of two teams, whose networks clash.  ... 
doi:10.1007/s11424-013-2291-2 fatcat:44kf66evj5bfbbbnoxh5kmj7b4

Exploring Team Passing Networks and Player Movement Dynamics in Youth Association Football

Bruno Gonçalves, Diogo Coutinho, Sara Santos, Carlos Lago-Penas, Sergio Jiménez, Jaime Sampaio, Satoru Hayasaka
2017 PLoS ONE  
Understanding how youth football players base their game interactions may constitute a solid criterion for fine-tuning the training process and, ultimately, to achieve better individual and team performances  ...  A passing network approach within positioning-derived variables was computed to identify the contributions of individual players for the overall team behaviour outcome during a simulated match.  ...  Acknowledgments This work was supported by the Portuguese Foundation for Science and Technology (FCT) and European Social Fund (ESF), through a Doctoral grant endorsed to the first author  ... 
doi:10.1371/journal.pone.0171156 pmid:28141823 pmcid:PMC5283742 fatcat:3rxld5wchfatzofixnh6nma3xq

Football is becoming boring; Network analysis of 88 thousands matches in 11 major leagues [article]

Victor Martins Maimone, Taha Yasseri
2019 arXiv   pre-print
In this work we take a data-heavy network science approach to measure predictability of football over 26 years in major European leagues.  ...  Football is a major sport with worldwide popularity. In recent years excessive monetization of the game has been argued to have affected the quality of the match in different ways.  ...  The authors thank Luca Pappalardo for valuable discussions. TY was partially supported by the Alan Turing Institute under the EPSRC grant no. EP/N510129/1.  ... 
arXiv:1908.08991v1 fatcat:q3o26vg4h5awhjig6ab2p44guu

Fantasy Football Prediction [article]

Roman Lutz
2015 arXiv   pre-print
I used two different methods to predict the Fantasy Football scores of NFL players: Support Vector Regression (SVR) and Neural Networks.  ...  The ubiquity of professional sports and specifically the NFL have lead to an increase in popularity for Fantasy Football.  ...  Sierra, Fosco and Fierro [1] used classification methods to predict the outcome of an American Football match based on a limited number of game statistics excluding most scoring categories.  ... 
arXiv:1505.06918v1 fatcat:nstq7elb3vb7vpcswgiyeehn3q
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