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  1. 1

    Majority of NCAA Div. 1 football players at specific institute show patellar tendon blood flow post-exercise

    Schaugaard, B. T., Hinkle, L. J, Davidson, G., Mortensen, B. B., Johnson, A. W.
    Published in International Journal of Exercise Science Conference Proceedings (2025)
    “…METHODS: Preexisting ultrasound images and data from 133 Div. 1 college football players (Ht 189 ± 6.1 cm; Wt 105 ± 19.8 kg) were analyzed for PDI intensity using a previously validated clinical scale of 0-5. …”
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  2. 2

    Correlation between body weight and eccentric hamstring strength in american football players

    Hacking, T. K., Wilwand, M., Johnson, A. W., Mortensen, B. B.
    Published in International Journal of Exercise Science Conference Proceedings (2025)
    “…The average max force exerted from the right and left leg from 3 trials was recorded for data analysis. RESULTS: Overall, we noted a weak correlation between players BW and their max eccentric HS (r = 0.34, p = <0.0008, Force: 451.6 ± 83.5 N). …”
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  3. 3

    Künstliche Intelligenz und maschinelles Lernen in der Sportwissenschaft (Artificial intelligence and machine learning in sports science)

    D. Memmert
    Published 2025
    “…Durch die Integration von Big Data können Spielergebnisse, Fitnessparameter und individuelle Leistungen eingehend analysiert werden, was zu neuen Entwicklungen in der Forschung führt. …”
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  4. 4

    Lower extremity muscle volume as a prediction for sprint speed in collegiate football players

    Wilwand, M., Sponbeck, J., Allen, S. P., Snow, G., Hunter, I., Johnson, A. W.
    Published in International Journal of Exercise Science Conference Proceedings (2025)
    “…The study included NCAA Division I AF players aged 18 and older who were active on the roster and not injured at the time of data collection. Positions were grouped as follows: the combo group (linebackers and tight ends), the big group (offensive and defensive linemen), and the skill group (defensive backs, kickers, wide receivers, quarterbacks, and running backs). …”
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  5. 5

    Evaluating external load responses to cumulative playing time and position in the European Handball Federation Women`s Euro 2022 through an IoT and Big Data architecture approach

    Karcher, C., Font, R., Marcos-Jorquera, D., Gilart-Iglesias, V., Manchado, C.
    Published in Biology of Sport (2025)
    “…Auswertung externer Belastungsreaktionen auf kumulative Spielzeit und Position bei der Handball-Europameisterschaft der Frauen 2022 durch einen IoT- und Big-Data-Architekturansatz…”
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  6. 6

    Elite coaching personality analysis in competitive weightlifting

    Gibson, J. H., Bingham, G. E., Merrigan, J. J., Taber, C. B.
    Published in Journal of Trainology (2024)
    “…Abstract Objectives: This study examined the personality traits of weightlifting coaches of various competitive levels. The Big Five personality traits have been used in a wide variety of populations and settings throughout the world. …”
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  7. 7

    Monitoring external load during real competition in male handball players through big data analytics: Differences by playing positions

    Manchado, C., Tortosa-Martinez, J., Marcos-Jorquera, D., Gilart-Iglesias, V., Pueo, B., Chirosa-Rios, L. J.
    Published in Kinesiology (2024)
    “…Überwachung der externen Belastung während des realen Wettkampfs bei männlichen Handballspielern durch Big-Data-Analytik: Unterschiede nach Spielpositionen…”
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  8. 8

    How winning teams kick for success in Rugby Union: A big data approach

    Scott, G. A., Bezodis, N. E., Bennett, M., Church, S., Waldron, M., Kilduff, L. P., Brown, M. R.
    Published in 28th Annual Congress of the European College of Sport Science, 4-7 July 2023, Paris, France (2023)
    “…Wie siegreiche Teams im Rugby Union erfolgreich kicken: Ein Big-Data-Ansatz…”
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  9. 9

    Is markerless motion tracking a feasible approach for in field kinematic analysis of weightlifting?

    Holzer, D., Hummel, C., Paternoster, F. K., Stöcker, F., Thiele, F.
    Published in 28th Annual Congress of the European College of Sport Science, 4-7 July 2023, Paris, France (2023)
    “…A marker-based approach (MB) is widely used to obtain kinematic data in weightlifting [1]. Yet, it is not suitable for in field activities such as competitions. …”
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  10. 10

    Worst-case scenario analysis of physical demands in elite men handball players by playing position through big data analytics

    Cartón-Llorente, A., Lozano, D., Iglisias, V. G., Jorquera, D. M., Manchado, C.
    Published in Biology of Sport (2023)
    “…Worst-Case-Szenario-Analyse der körperlichen Beanspruchung von Elite-Handballspielern nach Spielposition durch Big-Data-Analytik…”
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  11. 11

    Personality profile of amateur team handball referees

    Dodt, M., Fasold, F., Memmert, D.
    Published in German Journal of Exercise and Sport Research (2023)
    “…This study, therefore, examines the personality profile of amateur handball referees (n = 582) for the first time using the German version of the Big Five Inventory 2 (BFI-2). Current data from German handball referees at the expert level and the German general population were used to compare and discuss the results. …”
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  12. 12

    Metabolic power and success in men's handball in the European Championship

    Venzke, J., Schäfer, R., Niederer, D., Manchado, C., Platen, P.
    Published in 27th Annual Congress of the European College of Sport Science (ECSS), Sevilla, 30. Aug - 2. Sep 2022 (2022)
    “…During 65 matches of the EURO 2020, local positioning system data (Kinexon Precision Technologies) were collected (16.6 Hz), yielding 1853 datasets. …”
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  13. 13

    Zukunftsperspektive von Sportinformatik & Sporttechnologie im Leistungs- und Breitensport (Future prosepcts of sport informatics and sport technology im elite and grassroot sport)

    U. Fehr, V. Werner
    Published 2021
    “…Sports Innovation: Smart Equipment and Wearable Technology " Session Informations- und Feedbacksysteme " Sport-Informationssysteme - Review verschiedener Produkte basierend auf einem sportinformatischen Architekturkonzept " Effiziente Suche und Bewertung von Szenen in Spielsportarten " Überprüfung zeitlicher und räumlicher Genauigkeit im Trampolinturnen Validierung einer Web-Applikation zum Fern-Monitoring von Belastungs- und Erholungsparametern " Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im internationalen Spitzensport - zwischen Small und Big Data " Einsatz von Künstlicher Intelligenz im internationalen Spitzensport - Eine Erhebung des Status Quo " Darstellung von Informationen im Bereich des Peripheren Sehens bei Sportlern/innen " Session Messtechnik und Datenanalyse 1 " Eignet sich OpenPose zur 3-D-Analyse im Leistungssport? …”
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  14. 14

    A study on the competition of the World Women`s Handball Championship using bigdata : Focused on the top 5 teams of the 2007-2019 World Women`s Handball Championship

    Kang, Y.-G., Kwak, H.-P.
    Published 2021
    “…Eine Wettkampfanalyse der Handball-Weltmeisterschaft der Frauen mit Big Data: Fokus auf die 5 Top-Teams der Handballweltmeisterschaften 2007-2019…”
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  15. 15

    Calling an audible: COVID-19 and competitive sports

    Nallamothu, B. K.
    Published in Circulation (2020)
    “…In this issue of Circulation: Cardiovascular Quality & Outcomes, we publish a Cardiovascular Perspective by the Big Ten Cardiac Registry Steering Committee (CRSC). …”
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  16. 16

    The year-two effect: Evidence and antecedents for second season success in NCAA division I football

    David Pifer, N., Huml, M. R.
    Published in Journal of Sports Analytics (2020)
    “…Using two-way fixed effects panel regression models to analyze 11 seasons (2007-17) of data for 114 NCAA Division I Football Bowl Subdivision (FBS) programs, this study found support for the Year-Two Effect`s existence, particularly in situations where coaches were replacing a prior coach that had been fired for on-field performance reasons. …”
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  17. 17

    The Ivy League-Big Ten epidemiology of concussion study: A report on methods and first findings

    Putukian, M., D`Alonzo, B. A., Campbell-McGovern, C. S., Wiebe, D. J.
    Published in The American Journal of Sports Medicine (2019)
    “…Purpose: To describe methods of the Ivy League-Big Ten Epidemiology of Concussion Study and first epidemiologic findings. …”
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  18. 18

    Keeping it 100: Social media and self-presentation in college football recruiting

    Bigsby, K. G., Ohlmann, J. W., Zhao, K.
    Published in Big data (2019)
    “…Big data…”
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  19. 19

    Shaping analytics in rugby

    Collis, A.
    Published in Sports Performance & Tech (2017)
    “…Big Data…”
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  20. 20

    The situation success in the handball: review

    Vukosavljevic, J., Kocic, M., Beric, D., Stojic, M.
    Published in Facta Universitatis: Series Physical Education and Sport (2015)
    “…That way we obtain objective data of player efficiency. The parameters for the assessment of situational success, according to the rule, are collected during big competitions because they already have established methods for the registration of certain parameters on specific games and during the competition (official statistics IHF or EHF). …”
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