Positional differences in anticipation timing, reaction time and dynamic balance of American football players
DOI:
https://doi.org/10.15561/26649837.2020.0503Keywords:
american football, coinciding anticipation timing, dynamic balance, reaction timeAbstract
Purpose: The aim of this study was to compare the coinciding anticipation timing (CAT), reaction time and dynamic balance performances of American football players according to their playing positions. Material: Thirty-five American football players, who train at least 3 days a week, and compete in Universities Protected Football 1st League, participated in this study, voluntarily. The players were divided into two playing positions: offensive (17 players, mean age: 20.76 ± 1.30 years) and defensive (18 players, mean age: 21.94 ± 2.87 years). The CAT at different stimulus speeds (6 mph, 12 mph), reaction time (visual, auditory, mixed), and dynamic balance performance (anterior-posterior, medial-lateral, perimeter lenght) were measured in the laboratory environment. The CAT, reaction time, and dynamic balance performance of players were determined by Bassin Anticipation Timer, Newtest 1000, and Technobody Prokin-200, respectively. Results: The data obtained were analyzed in SPSS (20.0) program. Firstly, the raw data for CAT performance (6mph, 12 mph) were converted to absolute error score. According to Shapiro-Wilk test result, the all data showed normal distribution. Independent Sample t test was used to determine the differences between the two playing positions. In addition, the effect size between the two playing positions was calculated in parameters with showing significant differences, and Cohen’s d (1988) values were taken into account. Compared with the defensive players (20.15±3.81 ms), the absolute error scores at fast stimulus speeds (12 mph) of offensive players (17.45±3.48 ms) was found to be significantly lower (t(33) =-2.181, p=.036). The visual reaction time of offensive players (318.11± 17.47 ms) was significantly shorter than defensive players (340.58± 32.60 ms, t(26322) =-2.560, p=.017). In terms of dynamic balance parameters such as perimeter lenght, anterior-posterior, and medial-lateral, there was no statistically significant difference between the playing positions (p>0.05). Conclusions: Perceptual-cognitive characteristics such as CAT, and reaction time performance differ according to the playing positions, and this difference may be related to the physical, and cognitive demands required by their playing positions.Downloads
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References
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16. Runswick OR, Green R, North JS. The effects of skill-level and playing-position on the anticipation of ball-bounce in rugby union. Human Movement Science. 2020;69:102544.
https://doi.org/10.1016/j.humov.2019.102544
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18. Zwierko T. Selected aspects of anticipation of soccer players. Studies in Physical Culture and Tourism. 2006;13:186–191.
19. Schmidt RA, Lee T. Motor Learning and Performance From Principles Application. 6nd. ed. USA: Human Kinetics; 2020.
20. North JS, Hope E, Williams AM. The relative importance of different perceptual-cognitive skills during anticipation. Human Movement Science. 2016;49:170–171.
https://doi.org/10.1016/j.humov.2016.06.013
21. North JS, Williams AM, Hodges N, Ward P, Ericsson KA. Perceiving patterns indynamic action sequences:Investigating theprocesses underpinning stimulus recognition and anticipation skill. Applied Cognitive Psychology. 2009;23:878–894.
https://doi.org/10.1002/acp.1581
22. Sors F, Murgia M, Santoro I, Prpic V, Galmonte A, Agostini T. The contribution of early auditory and visual information to the discrimination of shot power in ball sports. Psychology of Sport and Exercise. 2017;31:44–51.
https://doi.org/10.1016/j.psychsport.2017.04.005
23. Atan T, Akyol P. Reaction times of different branch athletes and correlation between reaction time parameters. Procedia-Social and Behavioral Sciences. 2014;116:2886–2889.
https://doi.org/10.1016/j.sbspro.2014.01.674
24. Kalberer D, Zagelbaum A, Hersh P, Mellody J, Montgomery K, Sison CP, et al. Peripheral awareness and visual reaction time in professional football players in the national football League (N.F.L.). Optom.Vis.Perform. 2017;5(4):158–163.
25. Reid B, Schreiber K, Shawhan J, Stewart E, Burch R, Reimann W. Reaction time assessment for coaching defensive players in NCAA division 1 American football: A comprehensive literature review. International Journal of Industrial Ergonomics. 2020;77:102942.
https://doi.org/10.1016/j.ergon.2020.102942
26. Mankowska M, Poliszczuk T, Poliszczuk D, Johne M. Visual perception and its effect on reaction time and time-movement anticipation in elite female basketball players. Polish Journal of Sport and Tourism. 2015;22(1):3–8.
https://doi.org/10.1515/pjst-2015-0008
27. Sheppard JM, Young WB. Agility literature review: Classifications, training and testing. Journal of Sports Sciences. 2006;24(9):919–932.
https://doi.org/10.1080/02640410500457109
28. Butler RJ, Southers C, Gorman PP, Kiesel KB, Plisky PJ. Differences in soccer players’ dynamic balance across levels of competition. Journal of Athletic Training. 2012;47(6):616– 620.
https://doi.org/10.4085/1062-6050-47.5.14
29. Johnston W, Duignan C, Coughlan GF, Caulfield B. Dynamic balance performance varies by position but not by age group in elite Rugby Union players–a normative study. Journal of Sports Sciences. 2019;37(11):1308–1313.
https://doi.org/10.1080/02640414.2018.1557360
30. Olchowik G, Czwalik A. Effects of soccer training on body balance in young female athletes assessed using computerized dynamic posturography. Applied Sciences. 2020;10(3):1003.
https://doi.org/10.3390/app10031003
31. Loughran GJ, Vulpis CT, Murphy JP, Weiner DA, Svoboda SJ, Hinton RY, et al. Incidence of knee injuries on artificial turf versus natural grass in National Collegiate Athletic Association American football: 2004–2005 through 2013-2014 seasons. The American journal of Sports Medicine. 2019;47(6):1294–1301.
https://doi.org/10.1177/0363546519833925
32. Kerr ZY, Simon JE, Grooms DR, Roos KG, Cohen RP, Dompier TP. Epidemiology of football injuries in the National Collegiate Athletic Association, 2004-2005 to 2008-2009. Orthopaedic Journal of Sports Medicine. 2016;4(9):2325967116664500.
https://doi.org/10.1177/2325967116664500
33. Severo-Silveira L, Fritsch CG, Marques VB, Dornelles MP, Baroni BM. Isokinetic performance of knee flexor and extensor muscles in American Football players from Brazil. Revista Brasileira de Cineantropometria & Desempenho Humano. 2017;19(4):426–435.
https://doi.org/10.5007/1980-0037.2017v19n4p426
34. Sterczala AJ, Flanagan SD, Looney DP, Hooper DR, Szivak TK, Comstock BA, et al. Similar hormonal stress and tissue damage in response to national collegiate athletic association division i football games played in two consecutive seasons. The Journal of Strength & Conditioning Research. 2014;28(11):3234–3238.
https://doi.org/10.1519/JSC.0000000000000467
35. Wellman AD, Coad SC, Goulet GC, McLellan CP. Quantification of competitive game demands of NCAA division I college football players using global positioning systems. The Journal of Strength & Conditioning Research. 2016;30(1):11–19.
https://doi.org/10.1519/JSC.0000000000001206
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2020-10-30
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Ceylan H İ., Günay AR. Positional differences in anticipation timing, reaction time and dynamic balance of American football players. Pedagogy of Physical Culture and Sports. 2020;24(5):227-39. https://doi.org/10.15561/26649837.2020.0503
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