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    Comparative analysis of models of sports development management on example of football industry: international experience and russian peculiarities by Sh. M. Ramazanov

    Published 2018-03-01
    “…The mentioned above analysis indicated that the variant of model applied in Russia varies sufficiently from the American model and to a lesser extent from a European one. The author suggests possible directions of Russian football industry’s effectiveness and efficiency improvement which are: foundation of a unified center of management that would be in charge of professional football, increase of internal competition in Russian Football Premier League achieving both commercial and sports results. …”
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    Prediction of football injuries using GPS-based data in Iranian professional football players: a machine learning approach by Reza Saberisani, Amir Hossein Barati, Mostafa Zarei, Paulo Santos, Armin Gorouhi, Luca Paolo Ardigò, Hadi Nobari

    Published 2025-01-01
    “…IntroductionThe study aims to assess and compare the predictive effectiveness of football-related injuries using external load data and a decision tree classification algorithm by unidimensional approach.MethodsThe sample consisted of 25 players from one of the 16 teams participating in the Persian Gulf Pro League during the 2022--2023 season. …”
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    Nutritional Habits’ Review of Amateur and Professional Football Players by Fatma Nur Türkoğlu, Orhan Şener, Ahmet Çöndü

    Published 2019-09-01
    “…ABSTRACT The aim of our study is to investigate the dietary habits of amateur and professional football players and their differences.A hundred football players actively playing football during the 2013-2014 football season in 2nd League A Category, 2nd League B Category, 3rd League, 1st Amateur and 2nd Amateur Leagues participated in our study.  …”
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    Opinions of Football Referees on the VAR System and VAR Training by Ozer Yıldız, Muhammet Munir Dadı

    Published 2022-04-01
    “…Research data were collected through a semi-structured interview form developed by the researcher.The research group consists of 20 football referees who are actively working in different classifications determined by maximum diversity sampling, one of the purposive sampling methods, which is one of the non-probability sampling strategies. …”
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    The Examination of Sports Injury and Career Anxiety Levels of Football Players by Hülya Cin, Onur Sarı, Cosmin Damian

    Published 2023-08-01
    “…The aim of this study is to investigate the relationship between sport injury anxiety and career anxiety of amateur football players in Turkey. The study group of the research consists of 392 Amateur football players, 59 women and 333 men, who are actively participating in the competitions of the Turkish Football Federation in the 2021-2022 season. …”
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    Optimizing Scanning in Youth Female Football: The Role of Verbal Instructions by Mirjam Hintermann, Michael Romann, Dennis Lüdin, Wolfgang Taube, Jörg Fuchslocher

    Published 2025-01-01
    “…Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01 Eldridge, D., Pocock, C., Pulling, C., Kearney, P., & Dicks, M. (2022). …”
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    The Effect of Goal orientation and Motivation of Female Footballers in Sports on Resilience Power by Yeşim Bayrakdaroğlu, Ahmet Yilmaz Albayrak, Ali Tekin, Efecan Tezcan

    Published 2020-09-01
    “…The aim of this study is to investigate the effect of goal orientation and motivation of female footballers in sports on resilience power. In the study, there 183 female footballers based upon the leagues Süper Lig (Super League), PTT 1st League, 3rd League and Amateur League. …”
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    Leveraging the Chain on Goals Model in Football: Applications for Attack and Defensive Play by Blanca De-la-Cruz-Torres, Miguel Navarro-Castro, Anselmo Ruiz-de-Alarcón-Quintero

    Published 2025-01-01
    “…Results: Significant differences were observed between leagues in defensive performance (<i>p</i> = 0.03) and GSAA (<i>p</i> < 0.001). …”
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    The influence of meteorological factors on the technical performance of football teams during matches by Yonghan Zhong, Shaoliang Zhang, Qing Yi, Miguel Ángel Gómez Ruano

    Published 2024-04-01
    “…This study explored the impact of the meteorological factors air temperature, relative humidity, and wind speed on teams’ technical performance during the Union of European Football Associations Champions League (UCL). Technical match statistics were collected for five seasons (2016/2017–2020/2021). …”
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    Effect of public relations activities conducted in professional football clubs on fan satisfaction by Hakan Salim Caglayan, Celalettin Bayar

    Published 2017-04-01
    “…The research sample was composed of a total of 699 fans (nmale=535 and nfemale=164) including 200 Fenerbahçe fans (nmale=179 and nfemale=21), 100 Beşiktaş Fans (nmale=2 and nfemale=98), 201 Galatasaray Fans (nmale=178 and nfemale=23) and 198 Gençlerbirliği Fans (nmale=176 and nfemale=22), who were selected with random sampling method from football teams played in Super Toto Super League at Turkey Football Federation 2011-2012 Football Season. …”
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    Injury characteristics, mechanisms, and game circumstances in junior community-level Australian football by Indianna L. Franke, Andrea B. Mosler, Brooke E. Patterson, Kay M. Crossley, Patrick Clifton, Steven McPhail, Mark J. Scholes, Matthew G. King

    Published 2025-06-01
    “…Objective: Describe the injury characteristics, game circumstances, and immediate action and management of injuries sustained by boys and girls participating in junior community Australian football. Design: Cohort Study. Methods: All community junior Australian football players from one Victorian-based league were eligible to participate if they were injured during a game and presented to the gameday first aid medics. …”
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    Severe Injuries of Former Portuguese Football Players: A Post-Career Burden? by Eduardo Teixeira, Carlos Silva, Félix Romero, Mauro Miguel, António Vicente

    Published 2025-01-01
    “…This study found a statistically significant linear model (F(1.82) = 8.089, <i>p</i> < 0.006) that explains 7.9% of the variation in the physical domain of QoL (R2ajuste = 0.079). …”
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