Article
Psychology, Multidisciplinary
Branimir Micovic, Bojan Leontijevic, Milivoj Dopsaj, Aleksandar Jankovic, Zoran Milanovic, Amador Garcia Ramos
Summary: The aim of this study was to analyze the attacking actions leading up to goal scoring in the 14 FIFA World Cups from 1966 to 2018. A total of 1881 goals scored in 732 matches were analyzed using observational methodology. The study found a statistically significant trend towards a higher frequency of goals from set plays and collective actions in open play over the years. The majority of goals were scored in the 76th to 90th minutes of a match, from open play, inside the penalty area, with one touch finishing, and through collective attacks.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Psychology, Multidisciplinary
Taeahn Kang, Jeongbeom Hahm, Hirotaka Matsuoka
Summary: This study examines the impact of the 2002 FIFA World Cup on football participation frequency in South Korea and Japan using the concept of points of attachment (POA). The findings suggest that a higher attachment to each POA during the event is associated with a higher frequency of football participation immediately after the event. However, only attachment to players and coaches leads to a higher frequency of present football participation.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Psychology, Multidisciplinary
Yeqin Zhang, Danyang Li, Miguel-Angel Gomez-Ruano, Daniel Memmert, Chunman Li, Ming Fu
Summary: This study investigates the impact of the video assistant referee (VAR) on refereeing decisions in women's football. The results demonstrate that after the implementation of VAR, playing time significantly increased, while the number of penalties, offsides, fouls, goals, corner kicks, yellow cards, and red cards did not vary significantly.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Psychology, Multidisciplinary
Jasper Beernaerts, Bernard De Baets, Matthieu Lenoir, Nico Van de Weghe
Summary: This paper explores the use of QTC(S) for analyzing team formations in football. Unlike quantitative methods, QTC(S) describes the relative positions between players qualitatively, reflecting their on-field positioning. The method can monitor how well a team adheres to a coach's predetermined formation and contribute to defining a team's playing style.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Computer Science, Information Systems
Mustafa A. Al-Asadi, Sakir Tasdemir
Summary: This article introduces a method for determining the market value of football players based on machine learning algorithms. By analyzing FIFA 20 video game data, the researchers used different regression models to predict the market value of players and identified the most important factors affecting the determination of market value.
Article
Multidisciplinary Sciences
Mu Fan, Fei Liu, Dong Huang, Hui Zhang
Summary: Over the past 30 years, the global influence of the FIFA World Cup has grown continuously. This study aims to understand international football development and gain a competitive advantage by analyzing data from 68 countries participating in the World Cup from 1994 to 2022. The findings reveal the significant impact of football tradition, national sporting strength, and the country's Human Development Index on World Cup performance.
Article
Psychology, Multidisciplinary
Hannes Lepschy, Alexander Woll, Hagen Waesche
Summary: The study found that during the 2018 and 2014 World Cup tournaments, defensive errors, goal efficiency, duel success, tackles success, and other defensive actions had a significant impact on winning matches, while ball possession, distance, and market value of the teams did not affect success. The results indicate that direct play and pressing were more effective strategies than possession play.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Hospitality, Leisure, Sport & Tourism
Svante Andersson, Linnea Bengtsson, Asa Svensson
Summary: This study examines the impact of mega-sport events on visitors' destination images and their intentions to attend such events. The research, conducted through a structured questionnaire on a Swedish football supporters group, found differences in destination images among supporters after attending events like the UEFA European Football Championship and the FIFA World Cup. Positive destination images were linked to the satisfaction of important factors when visiting a destination, indicating the need for Qatar to improve its destination image to align with supporters' perceptions.
JOURNAL OF DESTINATION MARKETING & MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Yuan Zhong, Hongyu Yang, Yanci Zhang, Ping Li
Summary: Continuous data streams mining poses challenges for machine learning. The ORB-RRF is an online rebuilding regression random forests model designed to adapt to dynamic data streams, showing significant improvements in adaptability and predictive accuracy through numerical experiments.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Biochemical Research Methods
Cansu Alakus, Denis Larocque, Aurelie Labbe
Summary: This study proposes a new method called Covariance Regression with Random Forests (CovRegRF) for estimating the covariance matrix of a multivariate response given covariates. The method utilizes a random forest framework to build decision trees with a specially designed splitting rule to maximize differences between sample covariance matrix estimates of child nodes. A significance test for the partial effect of a subset of covariates is also introduced. Simulation studies and an application to thyroid disease data demonstrate the accuracy and control of Type-1 error of the proposed method. CovRegRF is available as a free R package on CRAN.
BMC BIOINFORMATICS
(2023)
Article
Computer Science, Information Systems
A. Dmitry Devyatkin, G. Oleg Grigoriev
Summary: This paper proposes an algorithm for training kernel decision trees and random forests, which overcomes the limitations of traditional methods in dealing with multidimensional sparse data. Experimental results show that the proposed algorithm outperforms other methods in various tasks, and the selected regularization technique helps reduce overfitting.
Article
Computer Science, Information Systems
Denisse Martinez-Mejorado, Jose Emmanuel Ramirez-Marquez
Summary: Research on group performance in competitive environments has traditionally focused on specific factors, ignoring a multidimensional view. Limited research considers the co-dependence between group performance and its adversaries. This paper proposes a framework that incorporates context-specific, network-based, and individual attributes to identify successful group patterns. The framework characterizes performance patterns by searching for dominant attributes and employs a machine learning model to identify winning attributes.
Article
Forestry
T. J. Boettcher, Baburam Rijal, James Cook, Shuva Gautam
Summary: This study aimed to develop a predictive model for the occurrence and abundance of buckthorn in Wisconsin by establishing sample plots and constructing different types of regression models. The ZINB model was identified as the best model for estimating buckthorn presence and abundance, indicating that factors such as stem density, woody species diversity, and environmental variables were important for predicting buckthorn invasion.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Review
Orthopedics
Marcelo Bordalo, Toni Evans, Salwa Allenjawi, Stephen Targett, Peter Dzendrowskyj, Abdulaziz Jaham Al-Kuwari, Marco Cardinale, Pieter D'Hooghe
Summary: This article provides a comprehensive account of the radiological services implemented during the 2022 FIFA World Cup, including equipment and human resources deployment, the structuring of workflows to uphold athlete confidentiality, and initiatives aimed at enhancing communication.
SKELETAL RADIOLOGY
(2023)
Article
Business
Rodrigo Uribe, Cristian Buzeta, Enrique Manzur, Isabel Alvarez
Summary: This article examines the impact of national team participation on the audience size of football matches, finding that the home team effect is the most relevant predictor when the national team qualifies. Different predictors of audience behavior are detected when the national team fails to qualify. Comparing the scenarios reveals additional home team effects during the tournament and direct effects when the team is present on screen.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Statistics & Probability
Marius Oetting, Groll Andreas
Summary: The study presents a penalized likelihood approach for automated variable selection in hidden Markov models (HMMs), considering a large number of potentially correlated covariates. By quadratically approximating the non-differentiable penalty, the likelihood can be maximized numerically. The feasibility of the approach is assessed through simulation experiments and applied to investigate the 'hot shoe' effect in football penalty takers.
STATISTICAL MODELLING
(2022)
Article
Sport Sciences
Joel Mason, Anna Lina Rahlf, Andreas Groll, Kai Wellmann, Astrid Junge, Astrid Zech
Summary: The study found that in field hockey, a congested fixture schedule increases the risk of injuries. Matches played within 24 hours after a previous match showed significantly higher injury rates compared to matches played 3-7 days later, while higher match exposure in the preceding 7 and 14 days was associated with reduced injury rates.
INTERNATIONAL JOURNAL OF SPORTS MEDICINE
(2022)
Editorial Material
Orthopedics
R. Kyle Martin, Christophe Ley, Ayoosh Pareek, Andreas Groll, Thomas Tischer, Romain Seil
Summary: The application of artificial intelligence and machine learning in orthopaedic surgery is increasing rapidly, but the statistical jargon and techniques associated with AI may be unfamiliar to many clinicians. In order to bridge this knowledge gap and make these novel techniques more accessible to orthopaedic surgeons, we introduce the concepts of AI and machine learning and provide examples of their impact on clinical practice and patient care.
KNEE SURGERY SPORTS TRAUMATOLOGY ARTHROSCOPY
(2022)
Article
Statistics & Probability
Hendrik Van der Wurp, Andreas Groll
Summary: In this work, we propose an extension of the versatile joint regression framework for bivariate count responses by incorporating an (adaptive) LASSO-type penalty. The method enables variable selection and guarantees shrinkage and sparsity, making it particularly useful in high-dimensional count response settings. The proposal's empirical performance is investigated in a simulation study and an application on FIFA World Cup football data.
ASTA-ADVANCES IN STATISTICAL ANALYSIS
(2023)
Editorial Material
Orthopedics
Christophe Ley, R. Kyle Martin, Ayoosh Pareek, Andreas Groll, Romain Seil, Thomas Tischer
Summary: This editorial discusses the application of machine learning in orthopaedic surgery, addressing the differences between ML techniques and traditional statistics. It aims to familiarize readers with the new opportunities offered by the ML approach.
KNEE SURGERY SPORTS TRAUMATOLOGY ARTHROSCOPY
(2022)
Article
Health Care Sciences & Services
Andreas D. Meid, Lucas Wirbka, Andreas Groll, Walter E. Haefeli
Summary: Estimating individual treatment effects can assist in reducing the impact of strokes, major bleeding events, and their composite through model-assisted recommendations. The study findings suggest that model-assisted recommendations may improve treatment decisions and decrease adverse outcomes.
MEDICAL DECISION MAKING
(2022)
Article
Computer Science, Information Systems
Alexander Gerharz, Carmen Ruff, Lucas Wirbka, Felicitas Stoll, Walter E. Haefeli, Andreas Groll, Andreas D. Meid
Summary: This study developed prediction models for readmissions based on routine data, specifically focusing on potentially inappropriate prescribing (PIP). The results showed that PIP effectively predicted readmissions for most diseases, suggesting the possibility for interventions to improve modifiable risk factors.
METHODS OF INFORMATION IN MEDICINE
(2022)
Review
Hospitality, Leisure, Sport & Tourism
Astrid Zech, Karsten Hollander, Astrid Junge, Simon Steib, Andreas Groll, Jonas Heiner, Florian Nowak, Daniel Pfeiffer, Anna Lina Rahlf
Summary: A systematic review and meta-analysis comparing injury rates between female and male team-sport players found that male players had higher overall injury rates, while female players had a higher rate of anterior cruciate ligament injuries. No significant sex-specific differences were found for match, training, severe injuries, concussions, or ankle sprains.
JOURNAL OF SPORT AND HEALTH SCIENCE
(2022)
Article
Rehabilitation
Andreas Stotz, Ebrahem Maghames, Joel Mason, Andreas Groll, Astrid Zech
Summary: This study highlights the importance of optimal joint angles in isometric strength assessment. Isometric contractions at the strongest joint angles can produce higher muscle torques than eccentric contractions in the lower body.
BMC SPORTS SCIENCE MEDICINE AND REHABILITATION
(2022)
Article
Psychology, Multidisciplinary
Philipp Doebler, Anna Doebler, Philip Buczak, Andreas Groll
Summary: Regression models with interaction terms are commonly used for moderating relationships. The hierarchical score model reduces the dimensionality of the interaction model and ensures interpretability. Regularization and residualization procedure help avoid spurious interactions. The ALOA algorithm with lasso penalty is an interpretable statistical learning technique for moderation.
PSYCHOLOGICAL METHODS
(2023)
Article
Statistics & Probability
Andreas Groll, Dominik Liebl
Summary: The advances in data gathering technologies have led to a growing interest in the use of statistical analysis, predictions, and modeling techniques in sports. This special issue aims to foster the development of statistics and its applications in sports, addressing various statistical problems and investigating the impacts of the SARS-CoV-2 pandemic on the sports framework.
ASTA-ADVANCES IN STATISTICAL ANALYSIS
(2023)
Article
Sport Sciences
Mathias Kolodziej, Andreas Groll, Kevin Nolte, Steffen Willwacher, Tobias Alt, Marcus Schmidt, Thomas Jaitner
Summary: The purpose of this study was to identify neuromuscular and biomechanical injury risk factors in elite youth soccer players and assess the predictive ability of a machine learning approach. Through various tests and measurements, it was found that knee extensor peak torque, hip transversal plane moment in the single-leg drop landing task, and center of pressure sway in the single-leg stance test are the three most important predictors for injury. However, the final model showed poor predictive performance and needs to be evaluated in larger samples.
SCANDINAVIAN JOURNAL OF MEDICINE & SCIENCE IN SPORTS
(2023)
Review
Health Care Sciences & Services
Sarah Friedrich, Andreas Groll, Katja Ickstadt, Thomas Kneib, Markus Pauly, Joerg Rahnenfuhrer, Tim Friede
Summary: This article reviews regularization approaches in data science for overcoming overfitting and improving prediction, and discusses their limited application in medical research. The authors suggest increased use of regularization approaches in medicine, despite the added complexity they bring to analyses. Proper investments in computing facilities and educational resources can help overcome these challenges.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2023)
Article
Mathematical & Computational Biology
Gunther Schauberger, Luana Fiengo Tanaka, Moritz Berger
Summary: Conditional logistic regression (CLR) is the standard method for matched case-control studies, but it has limitations in including non-linear effects and interactions of confounding variables. A novel tree-based modeling method is proposed to address this issue and provide a flexible framework for a more complex confounding structure. The proposed machine learning model is fitted within the CLR framework, allowing for the consideration of matched strata. Simulation results demonstrate the effectiveness of the method, and it is applied to a cervical cancer case-control study for illustration.
STATISTICS IN MEDICINE
(2023)
Article
Cardiac & Cardiovascular Systems
Sinann Al Najem, Andreas Groll, Axel Schmermund, Bernd Nowak, Thomas Voigtlaender, Ulrike Kaltenbach, Peter Dohmann, Dietrich Andresen, Juergen Scharhag
Summary: The study found that the number of steps taken by cardiac patients post-rehabilitation is related to the risk of cardiac hospitalization, with increased walking activity reducing the risk. Patients with lower EF values had higher risks.
CLINICAL MEDICINE INSIGHTS-CARDIOLOGY
(2022)