Working Overtime: The Effects of Overtime Periods on Game Demands in Basketball Players

in International Journal of Sports Physiology and Performance

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Aaron T. Scanlan
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Robert Stanton
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Charli Sargent
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Cody O’Grady
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Michele Lastella
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Jordan L. Fox
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Purpose: To quantify and compare internal and external workloads in regular and overtime games and examine changes in relative workloads during overtime compared with other periods in overtime games in male basketball players. Methods: Starting players for a semiprofessional male basketball team were monitored during 2 overtime games and 2 regular games (nonovertime) with similar contextual factors. Internal (rating of perceived exertion and heart-rate variables) and external (PlayerLoad and inertial movement analysis variables) workloads were quantified across games. Separate linear mixed-models and effect-size analyses were used to quantify differences in variables between regular and overtime games and between game periods in overtime games. Results: Session rating-of-perceived-exertion workload (P = .002, effect size 2.36, very large), heart-rate workload (P = .12, 1.13, moderate), low-intensity change-of-direction events to the left (P = .19, 0.95, moderate), medium-intensity accelerations (P = .12, 1.01, moderate), and medium-intensity change-of-direction events to the left (P = .10, 1.06, moderate) were higher during overtime games than during regular games. Overtime periods also exhibited reductions in relative PlayerLoad (first quarter P = .03, −1.46, large), low-intensity accelerations (first quarter P = .01, −1.45, large; second quarter P = .15, −1.22, large), and medium-intensity accelerations (first quarter P = .09, −1.32, large) compared with earlier periods. Conclusions: Overtime games disproportionately elevate perceptual, physiological, and acceleration workloads compared with regular games in starting basketball players. Players also perform at lower external intensities during overtime periods than earlier quarters during basketball games.

The authors are with the School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, Australia. Scanlan and Fox are also with the Human Exercise and Training Laboratory at the university. Stanton, Sargent, and Lastella are also with the Appleton Inst for Behavioural Science, Central Queensland University, Wayville, SA, Australia.

Scanlan (a.scanlan@cqu.edu.au) is corresponding author.
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  • 1.

    Kubatko J, Oliver D, Pelton K, Dan R. A starting point for analyzing basketball statistics. J Quant Anal Sports. 2007;3(3):122.

  • 2.

    Gómez M, Lorenzo A, Ibañez S, Sampaio J. Ball possession effectiveness in men’s and women’s elite basketball according to situational variables in different game periods. J Sports Sci. 2013;31(14):15781587. doi:10.1080/02640414.2013.792942

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Conte D, Kolb N, Scanlan A, Santolamazza F. Monitoring training load and well-being during the in-season phase in National Collegiate Athletic Association Division I men’s basketball. Int J Sports Physiol Perform. 2018;13(8):10671074. PubMed ID: 29431544 doi:10.1123/ijspp.2017-0689

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Scanlan A, Dascombe B, Reaburn P, Dalbo VJ. The physiological and activity demands experienced by Australian female basketball players during competition. J Sci Med Sport. 2012;15(4):341347. PubMed ID: 22244965 doi:10.1016/j.jsams.2011.12.008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Montgomery P, Pyne D, Minahan C. The physical and physiological demands of basketball training and competition. Int J Sports Physiol Perform. 2010;5(1):7586. PubMed ID: 20308698 doi:10.1123/ijspp.5.1.75

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Svilar L, Castellano J, Jukic I. Comparison of 5vs5 training games and match-play using microsensor technology in elite basketball. J Strength Cond Res. 2019;33(7):18971903. doi:10.1519/JSC.0000000000002826

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Fox J, Scanlan A, Stanton R. A review of player monitoring approaches in basketball: current trends and future directions. J Strength Cond Res. 2017;31(7):20212029. PubMed ID: 28445227 doi:10.1519/JSC.0000000000001964

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Harper L, Clifford T, Briggs M, et al. The effects of 120 minutes of simulated match play on indices of acid-base balance in professional academy soccer players. J Strength Cond Res. 2016;30(6):15171524. PubMed ID: 26605809 doi:10.1519/JSC.0000000000001271

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Russell M, Sparkes W, Northeast J, Kilduff LP. Responses to a 120 min reserve team soccer match: a case study focusing on the demands of extra time. J Sports Sci. 2015;33(20):21332139. PubMed ID: 26148212 doi:10.1080/02640414.2015.1064153

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Gómez M, Silva R, Lorenzo A, Kreivyte R, Sampaio J. Exploring the effects of substituting basketball players in high-level teams. J Sports Sci. 2017;35(3):247254. doi:10.1080/02640414.2016.1161217

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Dalton-Barron N, McLaren S, Black C, Gray M, Jones B, Roe G. Identifying contextual influences on training load: an example in professional rugby union [published online ahead of print July 2, 2018]. J Strength Cond Res. doi:10.1519/JSC.0000000000002706

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Delaney J, Thornton H, Duthie G, Dascombe BJ. Factors that influence running intensity in interchange players in professional rugby league. Int J Sports Physiol Perform. 2016;11(8):10471052. PubMed ID: 26999533 doi:10.1123/ijspp.2015-0559

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Aquino R, Carling C, Palucci Vieira LH, et al. Influence of situational variables, team formation, and playing position on match running performance and social network analysis in Brazilian professional soccer players [published online ahead of print July 4, 2018]. J Strength Cond Res. doi:10.1519/JSC.0000000000002725

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Mangan S, Malone S, Ryan M, et al. Influence of team rating on running performance in elite Gaelic football. J Strength Cond Res. 2018;32(9):25842591. PubMed ID: 29120985 doi:10.1519/JSC.0000000000002316

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Castellano J, Blanco-Villaseñor A, Álvarez D. Contextual variables and time-motion analysis in soccer. Int J Sports Med. 2011;32(6):415421. PubMed ID: 21590641 doi:10.1055/s-0031-1271771

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Boyd L, Ball K, Aughey R. The reliability of MinimaxX accelerometers for measuring physical activity in Australian football. Int J Sports Physiol Perform. 2011;6(3):311321. PubMed ID: 21911857 doi:10.1123/ijspp.6.3.311

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Luteberget L, Holme B, Spencer M. Reliability of wearable inertial measurement units to measure physical activity in team handball. Int J Sports Physiol Perform. 2018;13(4):467473. PubMed ID: 28872371 doi:10.1123/ijspp.2017-0036

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Scanlan A, Fox J, Poole J, et al. A comparison of traditional and modified summated-heart-rate-zones models to measure internal training load in basketball players. Meas Phys Educ Exerc Sci. 2018;22(4):303309. doi:10.1080/1091367X.2018.1445089

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Berkelmans D, Dalbo V, Fox J, et al. Influence of different methods to determine maximum heart rate on training load outcomes in basketball players. J Strength Cond Res. 2018;32(11):31773185. PubMed ID: 30540282 doi:10.1519/JSC.0000000000002291

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Foster C . Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sports Exerc. 1998;30(7):11641168. PubMed ID: 9662690 doi:10.1097/00005768-199807000-00023

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Fox J, Stanton R, Scanlan A. A comparison of training and competition demands in semiprofessional male basketball players. Res Q Exerc Sport. 2018;89(1):103111. PubMed ID: 29334021 doi:10.1080/02701367.2017.1410693

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Hopkins W, Marshall S, Batterham A, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):313. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Scanlan AT, Fox JL, Borges NR, Dascombe BJ, Dalbo VJ. Cumulative training dose’s effects on interrelationships between common training-load models during basketball activity. Int J Sports Physiol Perform. 2017;12(2):168174. PubMed ID: 27197090 doi:10.1123/ijspp.2015-0708

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Gómez M, Lorenzo A, Jiménez S, Navarro RM, Sampaio J. Examining choking in basketball: effects of game outcome and situational variables during last 5 minutes and overtimes. Percept Mot Skills. 2015;120(11):111124. doi:10.2466/25.29.PMS.120v11x0

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Manzi V, D’Ottavio S, Impellizzeri FM, Chaouachi A, Chamari K, Castagna C. Profile of weekly training load in elite male professional basketball players. J Strength Cond Res. 2010;24(5):13991406. PubMed ID: 20386474 doi:10.1519/JSC.0b013e3181d7552a

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Akenhead R, Hayes PR, Thompson KG, French D. Diminutions of acceleration and deceleration output during professional football match play. J Sci Med Sport. 2013;16(6):556561. PubMed ID: 23333009 doi:10.1016/j.jsams.2012.12.005

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Newham DJ, Mills KR, Quigley BM, Edwards RH. Pain and fatigue after concentric and eccentric muscle contractions. Clin Sci. 1983;64:5562. PubMed ID: 6822050 doi:10.1042/cs0640055

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Sekulic D, Pehar M, Krolo A, et al. Evaluation of basketball-specific agility: applicability of preplanned and nonplanned agility performances for differentiating playing positions and playing levels. J Strength Cond Res. 2017;31(8):22782288. PubMed ID: 27662488 doi:10.1519/JSC.0000000000001646

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Svilar L, Castellano J, Jukic I. Load monitoring system in top-level basketball team: relationship between external and internal training load. Kinesiology. 2018;50(1):2533. doi:10.26582/k.50.1.4

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Scanlan AT, Tucker PS, Dascombe BJ, Berkelmans DM, Hiskens MI, Dalbo VJ. Fluctuations in activity demands across game quarters in professional and semiprofessional male basketball. J Strength Cond Res. 2015;29(11):30063015. PubMed ID: 25932983 doi:10.1519/JSC.0000000000000967

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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