The Business End of the Season: A Comparison Between Playoff and Regular-Season Workloads in Professional Basketball Players

in International Journal of Sports Physiology and Performance
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Purpose: To quantify and compare the internal workloads experienced during the playoffs and regular season in basketball. Methods: A total of 10 professional male basketball players competing in the Italian first division were monitored during the final 6 weeks of the regular season and the entire 6-week playoff phase. Internal workload was quantified using the session rating of perceived exertion (s-RPE) method for all training sessions and games. A 2-way repeated-measures analysis of variance (day type × period) was utilized to assess differences in daily s-RPE between game days, days within 24 hours of games, and days >24 hours from games during the playoffs and regular season. Comparisons in weekly training, game, and total workloads were made between the playoffs and regular season using paired t tests and effect sizes. Results: A significant interaction between day and competitive period for s-RPE was found (P = .003, moderate). Lower s-RPE was apparent during playoff and regular-season days within 24 hours of games than all other days (P < .001, very large). Furthermore, s-RPE across days >24 hours from playoff games was different than all other days (P ≤ .01, moderate–very large). Weekly training (P = .009, very large) and total (P < .001, moderate) s-RPE were greater during the regular season than playoffs, whereas weekly game s-RPE was greater during the playoffs than the regular season (P < .001, very large). Conclusions: This study presents an exploratory investigation of internal workload during the playoffs in professional basketball. Players experienced greater training and total weekly workloads during the regular season than during the playoffs with similar daily game workloads between periods.

Ferioli and Rampinini are with the Human Performance Laboratory, MAPEI Sport Research Center, Olgiate Olona, Varese, Italy. Scanlan is with the Human Exercise and Training Laboratory, School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, Australia. Conte is with the Inst of Sport Science and Innovations, Lithuanian Sports University, Kaunas, Lithuania. Tibiletti is with Pallacanestro Reggiana S.R.L., Reggio Emilia, Italy.

Ferioli (ferio89@hotmail.it) is corresponding author.
  • 1.

    Mujika I, Halson S, Burke LM, Balagué G, Farrow D. An integrated, multifactorial approach to periodization for optimal performance in individual and team sports. Int J Sports Physiol Perform. 2018;13(5):538561. PubMed ID: 29848161 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Ferioli D, Bosio A, Bilsborough JC, La Torre A, Tornaghi M, Rampinini E. The preparation period in basketball: training load and neuromuscular adaptations. Int J Sports Physiol Perform. 2018;13(8):991999. PubMed ID: 29345555 doi:

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

    Ferioli D, Bosio A, Zois J, La Torre A, Rampinini E. Seasonal changes in physical capacities of basketball players according to competitive levels and individual responses. PLoS One. 2020;15(3):e0230558. PubMed ID: 32191740 doi:

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

    Fox JL, Scanlan AT, 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:

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

    Impellizzeri FM, Marcora SM, Coutts AJ. Internal and external training load: 15 years on. Int J Sports Physiol Perform. 2019;14(2):270273. PubMed ID: 30614348 doi:

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

    Ferioli D, Bosio A, La Torre A, Carlomagno D, Connolly DR, Rampinini E. Different training loads partially influence physiological responses to preparation period in basketball. J Strength Cond Res. 2018;32(3):790797. PubMed ID: 28146032 doi:

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

    Weiss KJ, Allen SV, McGuigan MR, Whatman CS. The relationship between training load and injury in men’s professional basketball players. Int J Sports Physiol Perform. 2017;12(9):12381242. PubMed ID: 28253031 doi:

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

    Ferioli D, Schelling X, Bosio A, La Torre A, Rucco D, Rampinini E. Match activities in basketball games: comparison between different competitive levels. J Strength Cond Res. 2020;34(1):172182. PubMed ID: 30741861 doi:

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

    Edwards T, Spiteri T, Piggott B, Bonhotal J, Haff GG, Joyce C. Monitoring and managing fatigue in basketball. Sports. 2018;6(1):E19. doi:

  • 10.

    Fox JL, Stanton R, Sargent C, Wintour SA, Scanlan AT. The association between training load and performance in team sports: a systematic review. Sports Med. 2018;48(12):27432774. PubMed ID: 30225537 doi:

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

    Ferioli D, Rampinini E, Martin M, et al. Influence of ball possession and playing position on the physical demands encountered during professional basketball games. Biol Sport. 2020;37(3):269276. doi:

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

    Svilar L, Castellano J, Jukic I, Casamichana D. Positional differences in elite basketball: selecting appropriate training-load measures. Int J Sports Physiol Perform. 2018;13(7):947952. PubMed ID: 29345556 doi:

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

    Clemente FM, Mendes B, Bredt SDGT, et al. Perceived training load, muscle soreness, stress, fatigue, and sleep quality in professional basketball: a full season study. J Hum Kinet. 2019;67(1):199207. PubMed ID: 31523318 doi:

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

    Conte D, Kolb N, Scanlan AT, 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:

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

    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:

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

    Berkelmans DM, Dalbo VJ, Kean CO, et al. Heart rate monitoring in basketball: applications, player responses, and practical recommendations. J Strength Cond Res. 2018;32(8):23832399. PubMed ID: 29140908 doi:

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

    Haddad M, Stylianides G, Djaoui L, Dellal A, Chamari K. Session-RPE method for training load monitoring: validity, ecological usefulness, and influencing factors. Front Neurosci. 2017;11:612. PubMed ID: 29163016 doi:

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

    Aoki MS, Ronda LT, Marcelino PR, et al. Monitoring training loads in professional basketball players engaged in a periodized training program. J Strength Cond Res. 2017;31(2):348358. PubMed ID: 27243913 doi:

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

    Fox JL, O’Grady CJ, Scanlan AT. Game schedule congestion affects weekly workloads but not individual game demands in semi-professional basketball. Biol Sport. 2020;37(1):5967. PubMed ID: 32205911 doi:

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

    Lewis M. It’s a hard-knock life: game load, fatigue, and injury risk in the national basketball association. J Athl Train. 2018;53(5):503509. PubMed ID: 29771139 doi:

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

    Ferioli D, Rampinini E, Bosio A, La Torre A, Maffiuletti NA. Peripheral muscle function during repeated changes of direction in basketball. Int J Sports Physiol Perform. 2019;14(6):739746. PubMed ID: 30427248 doi:

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

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109115. PubMed ID: 11708692

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

    Paulauskas H, Kreivyte R, Scanlan AT, Moreira A, Siupsinskas L, Conte D. Monitoring workload in elite female basketball players during the in-season phase: weekly fluctuations and effect of playing time. Int J Sports Physiol Perform. 2019;14(7):941948. PubMed ID: 30676809 doi:

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

    Borg G. Borg’s Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics; 1998.

  • 25.

    Richardson J. Eta squared and partial eta squared as measures of effect size in educational research. Educ Res Rev. 2011;6(2):135147. doi:

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

    Ferguson CJ. An effect size primer: a guide for clinicians and researchers. Prof Psychol. 2009;40(5):532538. doi:

  • 27.

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: L. Erlbaum Associates; 1988.

  • 28.

    Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):313. PubMed ID: 19092709 doi:

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

    Svilar L, Castellano J, Jukic I, Bok D. Short-term tapering prior to the match: external and internal load quantification in top-level basketball. Arch Med Deporte. 2019;36(5):288295.

    • Search Google Scholar
    • Export Citation
  • 30.

    Ferioli D, Rampinini E, Bosio A, La Torre A, Azzolini M, Coutts AJ. The physical profile of adult male basketball players: differences between competitive levels and playing positions. J Sports Sci. 2018;36(22):25672574. PubMed ID: 29697296 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Ben Abdelkrim N, Castagna C, El Fazaa S, El Ati J. The effect of players’ standard and tactical strategy on game demands in men’s basketball. J Strength Cond Res. 2010;24(10):26522662. PubMed ID: 20885192 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Calleja-González J, Terrados N, Mielgo-Ayuso J, et al. Evidence-based post-exercise recovery strategies in basketball. Phys Sportsmed. 2016;44(1):7478. PubMed ID: 26512912 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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