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Dissertations / Theses on the topic 'Football Prediction'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Ota, Karson L. "Football play type prediction and tendency analysis." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113120.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (page 33).<br>In any competition, it is an advantage to know the actions of the opponent in advance. Knowing the move of the opponent allows for optimization of strategy in response to their move. Likewise, in football, defenses mu

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2

Philp, Fraser Derek. "Validating models of injury risk prediction in football players." Thesis, Keele University, 2018. http://eprints.keele.ac.uk/4993/.

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Association football (soccer) is a popular sport and there is a high risk of injury for participants. Within the context of professional clubs, the risk of injury is also associated with the risk of financial costs. Therefore, injury reduction processes are considered important, and previous studies have sought to identify and model injury risk factors. Although formal screening tests e.g. The Functional Movement Screen (FMS) and monitoring procedures e.g. Union of European Football Associations (UEFA) have been developed for modelling and predicting injuries, the processes in current use, lac

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3

Rossi, A. "PREDICTIVE MODELS IN SPORT SCIENCE: MULTI-DIMENSIONAL ANALYSIS OF FOOTBALL TRAINING AND INJURY PREDICTION." Doctoral thesis, Università degli Studi di Milano, 2017. http://hdl.handle.net/2434/495229.

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Due to the fact that team sports such as football have a complex multidirectional and intermittent nature, an accurate planning of the training workload is needed in order to maximise the athletes’ performance during the matches and reduce their risk of injury. Despite the evaluation of external workloads during trainings and matches has become more and more easier thanks to the advent of the tracking system technologies such as Global Position System (GPS), the planning of the best training workloads aimed to obtain the higher performance during the matches and a lower risk of injury during s

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4

Anners, Carl, and Stefan Saarm. "The More the Merrier? : A Study Measuring Relative Efficiency of Two Prediction Markets." Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242132.

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Our aim of this paper was to create a method for comparing the overall relative efficiency of a prediction market for the English football league Premier League and a prediction market for the Swedish football league Allsvenskan. The purpose of this was to see how the overall turnover of a prediction market affects the efficiency of it. We conclude that while the implied probability of the two markets on average corresponds well to the win frequency, the Premier League prediction market has statistically significant lower variation than Allsvenskan. The method we created can also be used to te

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5

Falkstein, David Lawrence. "Prediction of Athletic Injury and Postinjury Emotional Response in Collegiate Athletes: A Prospective Study of an NCAA Division I Football Team." Thesis, University of North Texas, 1999. https://digital.library.unt.edu/ark:/67531/metadc278163/.

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Previous research has examined factors that predispose collegiate football players to injury (e.g., Petrie, 1993a, 1993b) as well as factors that influence athletes' psychological adjustment to being injured (e.g., Brewer, 1993; Leddy, Lambert, & Ogles, 1994). Despite the reports of the NCAA Injury Surveillance System that the greatest number of football injuries occur during the spring preseason (NCAA, 1997), studies have only examined injury during the regular season. Thus, the purpose of this study was to investigate the antecedents and consequences of injury in collegiate football players

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6

Long, Joseph. "Development of a Prediction Model for the NCAA Division-I Football Championship Subdivision." Thesis, North Dakota State University, 2013. https://hdl.handle.net/10365/27103.

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This thesis investigates which in-game team statistics are most significant in determining the outcome in a NCAA Division-I Football Championship Subdivision (FCS) game. The data was analyzed using logistic and ordinary least squares regression techniques to create models that explained the outcome of the past games. The models were then used to predict games where the actual in-game statistics were unknown. A random sample of games from the 2012 NCAA Division-I Football Championship Subdivision regular season was used to test the accuracy of the models when used to predict future games. Vario

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7

Carin, Yann. "La faillite des clubs français de football : un secteur spécifique." Thesis, Limoges, 2019. http://www.theses.fr/2019LIMO0040/document.

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Le football européen en général et le football français en particulier font état de difficultés financières et de faillites récurrentes de clubs professionnels. Sur la seule période de 1975 à 2018, 81 clubs français de football engagés dans les championnats des quatre premières divisions ont connu une faillite. Le sujet de la faillite d’entreprises a été largement traité pour les secteurs courants de l’économie. De nombreuses recherches se sont attachées à construire des modèles de prédiction, puis progressivement d’autres travaux se sont concentrés sur le processus et les différentes trajecto

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8

Mortensen, Bartley B. "Can a Preseason Screen Predict Injury or Performance over Three Years of College Football?" BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7339.

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Purpose: To investigate if the Functional Movement Screen (FMSâ„¢) total score, individual component test scores or number of asymmetries can predict noncontact injury risk or player performance over three consecutive seasons of NCAA Division I football. Methods: As football teams are comprised of individuals with vastly different physical characteristics and playing responsibilities, we divided the subjects into three homogeneous groups based on position (Big, Combo and Skill). Each FMSâ„¢ score was assessed with regard to the total team score as well as by individual position groups. For our

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9

Schroeder, Brian L. "Prediction equations as an alternative to 1-RM strength testing in division I college football players." Thesis, University of Hawaii at Manoa, 2003. http://hdl.handle.net/10125/7010.

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The purpose of this investigation was to develop a new prediction equation for 1RM bench press performance in Div. I college football players using both submaximal lifts and anthropometric variables. One repetition maximum (1-RM), 5-RM, reps at 225 lbs, and various anthropometric variables were collected on 85 Div. I college football players. Mean and SD were found for the following variables: height 182.3 cm ± 7.2; weight 102.0 kg ± 21.5; age 19.8 yrs ± 1.3; 1-RM 308.9 lbs ± 59.2; 5-RM 261.8 lbs ± 51.2; 225lb repetitions 14.1 reps ± 8.1; upper arm length 37.9 cm ± 2; CSA 125.5 cm2 ± 24.8; and

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10

Rudin, Pierre. "Football result prediction using simple classification algorithms, a comparison between k-Nearest Neighbor and Linear Regression." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187659.

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Ever since humans started competing with each other, people have tried to accurately predict the outcome of such events. Football is no exception to this and is extra interesting as subject for a project like this with the ever growing amount of data gathered from matches these days. Previously predictors had to make there predictions using there own knowledge and small amounts of data. This report will use this growing amount of data and find out if it is possible to accurately predict the outcome of a football match using the k-Nearest Neighbor algorithm and Linear regression. The algorithms

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11

Constantinou, Anthony Costa. "Bayesian networks for prediction, risk assessment and decision making in an inefficient Association Football gambling market." Thesis, Queen Mary, University of London, 2013. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8404.

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Researchers have witnessed the great success in deterministic and perfect information domains. Intelligent pruning and evaluation techniques have been proven to be sufficient in providing outstanding intelligent decision making performance. However, processes that model uncertainty and risk for real-life situations have not met the same success. Association Football has been identified as an ideal and exciting application for that matter; it is the world's most popular sport and constitutes the fastest growing gambling market at international level. As a result, summarising the risk and uncert

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12

Saul, William Robert. "Injury prediction in Division I college football players using a modified lower extremity version of the FMS." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1364489056.

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13

Sun, Jiong. "Football on mobile phones : algorithms, architectures and quality of experience in streaming video." Doctoral thesis, Umeå : Department of Applied Physics and Electronics, Umeå University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-831.

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14

Booysen, Conrad. "The application of discriminant analysis and logistical regression as methods of compilation in the prediction function in youth rugby." Diss., University of Pretoria, 2002. http://hdl.handle.net/2263/27250.

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15

Schweim, Jarrett Joshua. "Do any of a set of Lower Extremity Functional Assessment tests predict in the incidence of injury among a Cohort of collegiate freshmen football players? A Pilot Study." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1243851951.

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16

Kampakis, S. "Predictive modelling of football injuries." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1508067/.

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The goal of this thesis is to investigate the potential of predictive modelling for football injuries. This work was conducted in close collaboration with Tottenham Hotspurs FC (THFC), the PGA European tour and the participation of Wolverhampton Wanderers (WW). Three investigations were conducted: 1. Predicting the recovery time of football injuries using the UEFA injury recordings: The UEFA recordings is a common standard for recording injuries in professional football. For this investigation, three datasets of UEFA injury recordings were available: one from THFC, one from WW and one that was

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17

Urbanczyk, Martin. "Webový simulátor fotbalových lig a turnajů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403171.

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This thesis is about the creation of a simulator of football leagues and championships. I studied the problematics of football competitions and their systems and also about the base of machine learning. There was also an analysis of similar and existing solutions and I took inspiration for my proposal from them. After that, I made the design of the whole simulator structure and of all of its key parts. Then the simulator was implemented and tested. The application allows simulating top five competitions in UEFA club coefficients rating.

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18

Krause, Jacob Allen. "Predicting Offensive Success in the National Football League." Thesis, The University of Arizona, 2012. http://hdl.handle.net/10150/271608.

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19

Parikh, Neena (Neena S. ). "Interactive tools for fantasy football analytics and predictions using machine learning." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100687.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 83-84).<br>The focus of this project is multifaceted: we aim to construct robust predictive models to project the performance of individual football players, and we plan to integrate these projections into a web-based application for in-depth fantasy football analytics. Most existing statistical tools for the NFL are limited to the use of macro-level data; this research looks to explore st

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20

Spieler, Martin J. "Predicting starting status [electronic resource] : factors contributing to the success of collegiate football players /." Click here to access thesis, 2006. http://www.georgiasouthern.edu/etd/archive/spring2006/martin%5Fj%5Fspieler/spieler%5Fmartin%5Fj%5F200601%5Fms.pdf.

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Thesis (M.S.)--Georgia Southern University, 2006.<br>"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Science" ETD. Includes bibliographical references (p. 27-29) and appendices.

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21

Merritt, Kevin M. "Predicting the Success of Running Back Prospects in the National Football League." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10287281.

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<p> National Football League team’s analysts use statistics in a multitude of ways, including game planning, game day rosters, and incoming talent evaluation. Focusing on the running back position, we attempt to improve upon models designed to predict the future success of incoming collegiate players while introducing some models of our own. Focusing on running backs drafted from 1999 to 2013, we use data from the player’s college career, combine workouts, pro day workouts, and physical measurements. Using linear regression, recursive partitioning decision trees, principal componen

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22

Bigsby, Kristina Gavin. "From hashtags to Heismans: social media and networks in college football recruiting." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6371.

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Social media has changed the way that we create, use, and disseminate information and presents an unparalleled opportunity to gather large-scale data on the networks, behaviors, and opinions of individuals. This dissertation focuses on the role of social media and social networks in recruitment, examining the complex interactions between offline recruiting activities, online social media, and recruiting outcomes. Specifically, it explores how the information college football recruits reveal about themselves online is related to their decisions as well as how this information can diffuse and in

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23

Ford, Adam J. "Functional Movement Screening as a Predictor of Injury in Division One Collegiate Football Athletes." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1300728080.

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24

Vasilišin, Maroš. "Inteligentní manažer hry Fantasy Premier League." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417274.

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Hra Fantasy Premier League poskytuje miliónom hráčov po celom svete možnosť stať sa na chvíľu manažérom svojho vlastného klubu. Výsledky a bodové ohodnotenie v hre závisia na správnom predvídaní, ako sa budú hráči chovať v skutočných futbalových zápasoch. Ak by pri tomto rozhodovaní pomáhal software na predikciu a analýzu budúcich výkonov hráčov, výsledky v hre sa môžu rapídne zlepšiť. Táto diplomová práca sa zaoberá návrhom a implementáciou predikčného modelu, ktorý využíva neurónové siete na predikcie časových radov počas celej sezóny v hre. Boli použité metódy na spracovanie dát o hráčoch a

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25

Stout, Michael W. "Predicting Lower Extremity Injury in High School Football Players Using the Star Excursion Balance Test." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1333123544.

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26

Farrelly, Francis John. "A predictive model of sport sponsorship renewal in Australia." Title page, abstract and table of contents only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phf245.pdf.

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Bibliography: leaves 231-291. This thesis investigates key drivers of sponsorship renewal. The market orientation of sponsors, and their perception of their sponsored entity's (property's) market orientation, are analysed as antecedents of the trust invested by sponsors in the relationship, the level of commitment they exhibit and both the economic and non-economic satisfaction they derive from it. Sponsor economic and non-economic satisfaction and their commitment to the relationship are considered to be the ultimate drivers of the decision to renew. The argument is presented that sponsorship

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27

Pollock, Kristen M. "The Star Excursion Balance Test as a predictor of lower extremity injury in high school football players." Toledo, Ohio : University of Toledo, 2010. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=toledo1271092120.

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Thesis (M.S.E.S.)--University of Toledo, 2010.<br>Typescript. "Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Exercise Science." "A thesis entitled"--at head of title. Title from title page of PDF document. Bibliography: p. 37-40.

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Hedar, Sara. "Applying Machine Learning Methods to Predict the Outcome of Shots in Football." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-414774.

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The thesis investigates a publicly available dataset which covers morethan three million events in football matches. The aim of the study isto train machine learning models capable of modeling the relationshipbetween a shot event and its outcome. That is, to predict if a footballshot will result in a goal or not. By representing the shot indifferent ways, the aim is to draw conclusion regarding what elementsof a shot allows for a good prediction of its outcome. The shotrepresentation was varied both by including different numbers of eventspreceding the shot and by varying the set of features d

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29

Thomas, Kerry J. "Teaching Mathematical Modelling to Tomorrow's Mathematicians or, You too can make a million dollars predicting football results." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-83131.

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30

Woods, Carl T. C. "The development of an objective multi-dimensional approach to talent identification in junior Australian football." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1672.

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Talent identification (TID) is a pertinent component of the sports science discipline given the considerable influence it may have within the pursuit of excellence. Thus, research has attempted to identify the determinants of a talented performance through the use of objective testing procedures. However, many of these ‘traditional’ approaches have been operationalised by mono-dimensional objective physical performance tests that do not inherently account for the multi-dimensional requisites of game-play, particularly within a team sporting context. This is problematic when attempting to ident

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31

Thomas, Kerry J. "Teaching Mathematical Modelling to Tomorrow''s Mathematicians or, You too can make a million dollars predicting football results." Turning dreams into reality: transformations and paradigm shifts in mathematics education. - Grahamstown: Rhodes University, 2011. - S. 334 - 339, 2012. https://slub.qucosa.de/id/qucosa%3A1949.

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32

Gallagher, Michael. "A Better Predictor of NFL Success: Collegiate Performance or the NFL Draft Combine?" Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etd/3570.

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NFL teams spend massive sums to ensure they are prepared for the future, but how should they determine whom that future includes? This study set out to find what predicts NFL success more accurately – collegiate in-game performance or the NFL Draft Combine. In the sample of 2007-2012 first-round picks, 191 athletes were measured in three NFL Draft Combine drills, two physical components, and a varying amount of ingame collegiate and NFL performance statistical categories, dependent on position. Secondarily, this work examined Power 5 and non-Power 5 players to determine if attending a more pro

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33

Thomas, David Leary. "Recognition of predicted time series using chaotic and geometric features." Honors in the Major Thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1505.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Engineering and Computer Science<br>Computer Engineering

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Egidi, Leonardo. "Developments in Bayesian Hierarchical Models and Prior Specification with Application to Analysis of Soccer Data." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3427270.

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In the recent years the challenge for new prior specifications and for complex hierarchical models became even more relevant in Bayesian inference. The advent of the Markov Chain Monte Carlo techniques, along with new probabilistic programming languages and new algorithms, extended the boundaries of the field, both in theoretical and applied directions. In the present thesis, we address theoretical and applied tasks. In the first part we propose a new class of prior distributions which might depend on the data and specified as a mixture between a noninformative and an informative prior. The ge

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Martins, Bruno Gonçalo Pires. "Predicting the risk of injury of professional football players with machine learning." Master's thesis, 2019. http://hdl.handle.net/10362/62419.

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Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management<br>Sports analytics is quickly changing the way sports are played. With the rise of sensor data and new tracking technologies, data is collected at an unprecedented degree which allows for a plethora of innovative analytics possibilities, with the goal of uncovering hidden trends and developing new knowledge from data sources. This project creates a prediction model which predicts a player’s muscular injury in a prof

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36

Chang, Wen-Lung, and 張文龍. "Pattern Recognition and Neural Networks for Classification and Prediction of 2006 World Cup Football Game." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/27651584813970923633.

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碩士<br>國立交通大學<br>電機學院碩士在職專班電機與控制組<br>95<br>There are two main research aspects in this thesis. The first research aspect is that we use 4 unsupervised clustering methods to analyze the team level of 2006 FIFA World Cup Football Games. These clustering methods include K-means clustering algorithm, Fuzzy C-means clustering algorithm, hierarchical clustering algorithm, and self-organizing feature map algorithm. Furthermore, we use 3 clustering validity methods to verify whether these football statistical data possesses a clustering property. The second research aspect is that we use the supervised

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37

Almeida, Sofia de Sousa. "Performance assessment and prediction of football players: Tailoring an architecture with spatiotemporal positional and physiological features." Master's thesis, 2017. https://repositorio-aberto.up.pt/handle/10216/107499.

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Almeida, Sofia de Sousa. "Performance assessment and prediction of football players: Tailoring an architecture with spatiotemporal positional and physiological features." Dissertação, 2017. https://repositorio-aberto.up.pt/handle/10216/107499.

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Brewer, Ronald. "A case study of the relationship between collegiate football student-athletes' background and their athletic and academic success at a major division I-A institution." 2005. http://oregonpdf.org/index.cfm.

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Kassem, Lael. "The assessment of perceptual-cognitive and decision-making abilities for the prediction of talent in Australian rules football." Thesis, 2020. http://hdl.handle.net/1959.7/uws:67312.

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Talent identification (TID) is a vital component within the recruitment process for all sporting bodies and organisations. Given the considerable influence it may have on the success of a team, substantial resources are invested in identifying young athletes with the most potential for the development of expertise. Successful performance in team sports requires an athlete to have a unique combination of physical, technical and tactical skills. Such a combination allows athletes to compensate for different areas of weaknesses in the dynamic nature of game play. However, traditional TID does not

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Hickmann, Sara A. "Impulsivity as a predictor of athletic success and negative consequences in NFL football players." 2004. http://www.oregonpdf.org.

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Thesis (Ph. D.)--University of Massachusetts at Amherst, 2004.<br>Includes bibliographical references (leaves 129-139). Also available online (PDF file) by a subscription to the set or by purchasing the individual file.

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Lavrador, Rúben Filipe Caldeira. "Previsões em Futebol." Master's thesis, 2017. http://hdl.handle.net/10316/84755.

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Dissertação de Mestrado em Métodos Quantitativos em Finanças apresentada à Faculdade de Ciências e Tecnologia<br>Esta dissertação é dedicada ao estudo de modelos de Poisson univariados e bivariados que permitem estudar probabilidades e odds relativas a jogos de futebol. São estimadas estas quantidades para alguns jogos do campeonato português e do campeonato inglês. Neste trabalho estudamos modelos já conhecidos como o modelo de Poisson univariado tradicional, Poisson bivariado, Poisson bivariado inflacionado na diagonal e o modelo de Poisson inflacionado em zero. Desenvolvemos novos modelos t

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Palinggi, Denny Asarias. "Predicting soccer outcome with machine learning based on weather condition." Master's thesis, 2019. http://hdl.handle.net/10362/64182.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies<br>Massive amounts of research have been doing on predicting soccer matches using machine learning algorithms. Unfortunately, there are no prior researches used weather condition as features. In this thesis, three different classification algorithms were investigated for predicting the outcomes of soccer matches by using temperature difference, rain precipitation, and several other historical match statistics as features. The dataset consists of statistic informa

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Chao, Jung-Jui, and 趙榮瑞. "The Bioelectrical Impedance Analysis with Newly Predictive Equations for Measuring Segments Body Composition of Elite Male Football Players in Taiwan." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/42452962603493166531.

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博士<br>國立屏東科技大學<br>食品科學系所<br>100<br>To establish the appropriate predictive equations of body segments by bioelectrical impedance analysis (BIA) in Taiwan elite male football players, 26 disciplined players at first grade in collegiate league, have been recruited in this study. The measurement data by our newly developed predictive equation was compared with which by Tanita BC-418 to confirm the greater performance in prediction of body composition in our equation. The actual analyzed data of segments body composition by dual-energy X-ray absorptiometry (DXA) was taken as reference one. Both of

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