Showing 1 - 12 results of 12 for search 'Top League', query time: 0.05s Refine Results
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    Head in the game: the impact of cognitive abilities on performance of National Football League quarterbacks by R. Thomas Boone, Nicholas S. Zambrotta, Andrew M. Manocchio, James K. Bowman

    Published 2025-01-01
    “…American football is a multi-billion-dollar industry and source of social identity and national pride. Recruiting top level players is a priority for franchises, coaches, teams, and fans. …”
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    Content analysis of food and beverage marketing in global esports: sponsorships of the premier events, leagues, teams and players by Robin Ireland, John William Long, Sara Jordan Maksi, Francisco Javier López Frías, Travis D Masterson

    Published 2024-07-01
    “…Of the top 10 events and leagues, 6 events and 2 leagues were held or located outside the USA, reflecting the global popularity of esports. …”
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    Data-driven understanding on soccer team tactics and ranking trends: Elo rating-based trends on European soccer leagues. by Dong Hee Jung, Jason J Jung

    Published 2025-01-01
    “…Using a dataset comprising matches from the top five European soccer leagues, we analyzed team performance trends over time using the Elo rating system and rolling regression. …”
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    East Asian expatriate football players and national team success: Chinese, Japanese, and South Korean players in Europe (2000–2024) by Le Luo, Yangke Tang, Xiaohan Li, Ge Sun, Enkai Guo, Hanbing Xu

    Published 2025-01-01
    “…The results demonstrated a significant correlation between the number of expatriate players, particularly in top-tier leagues, and national team rankings. Notably, Japanese and South Korean players exhibited longer durations of participation and higher rates of advancement to elite European leagues compared to Chinese players. …”
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    Sugarcane Cultivars Descriptive Fact Sheet: CP 96-1252, CP 01-1372 and CP 00-1101 by Hardev Sandhu, Wayne Davidson

    Published 2017-01-01
    “… Sugarcane cultivars CP 96-1252, CP 01-1372 and CP 00-1101 are the top three commercial sugarcane cultivars in Florida occupying >43% of total sugarcane area (400,551 acres) (VanWeelden et al. 2016). …”
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    Sugarcane Cultivars Descriptive Fact Sheet: CP 96-1252, CP 01-1372 and CP 00-1101 by Hardev Sandhu, Wayne Davidson

    Published 2017-01-01
    “… Sugarcane cultivars CP 96-1252, CP 01-1372 and CP 00-1101 are the top three commercial sugarcane cultivars in Florida occupying >43% of total sugarcane area (400,551 acres) (VanWeelden et al. 2016). …”
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    Sugarcane Cultivars Descriptive Fact Sheet: CPCL 97-2730 and CPCL 00-4111 by Hardev Sandhu, Wayne Davidson

    Published 2017-10-01
    “…CPCL 97-2730 and CPCL 00-4111 were ranked among the top 10 sugarcane cultivars in Florida in 2015 sugarcane variety census (VanWeelden et al. 2016) based on their total acreage.  …”
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    Sugarcane Cultivars Descriptive Fact Sheet: CPCL 97-2730 and CPCL 00-4111 by Hardev Sandhu, Wayne Davidson

    Published 2017-10-01
    “…CPCL 97-2730 and CPCL 00-4111 were ranked among the top 10 sugarcane cultivars in Florida in 2015 sugarcane variety census (VanWeelden et al. 2016) based on their total acreage.  …”
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    MGIMO University Scientific Schools, 70th Anniversary by A. V. Torkunov

    Published 2014-10-01
    “…Th earticle out lines a program for getting MGIMO University to the top of world league tables. This goal is fairly new for Russian higher education; nevertheless it finds great support and encouragement on the part of Russian government in the form of laws and development programs. …”
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    Development and Evaluation of an AI-based Exergame Training System for Ice-Hockey Players: a Randomized Controlled Trial by Nicole Sieber, Simon Walser, Thomas Weber, Raphael Gubler, Hannes Badertscher, Patrick Eggenberger

    Published 2025-01-01
    “…To evaluate our novel exergame, 36 ice-hockey players from three male elite level teams (National League, U20, U17) and one female team (Swiss Women’s Hockey League B) of the SC Rapperswil-Jona Lakers participated. …”
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    A Hybrid Machine Learning Framework for Soccer Match Outcome Prediction: Incorporating Bivariate Poisson Distribution by Chen Zhong An

    Published 2025-01-01
    “…The author utilizes a comprehensive dataset from top European leagues (2014-2022) and employ models including Bivariate Poisson Distribution, Naive Bayes, Neural Networks, Support Vector Machines, Random Forests, and Gradient Boosting. …”
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