The perceptual,heart rate and technical-tactical characteristics of 3 × 3 basketball

Abstract

The aim of this study was to investigate the perceptual, heart rate and technical-tactical characteristics of elite male and female 3 × 3 basketball games. Eleven male and twenty-two female elite basketball players were monitored using heart rate telemetry, Ratings of Perceived Exertion (RPE) and video analysis across three 3 × 3 basketball tournaments. Linear mixed models were performed to determine the influence of round (pool game, quarter-final, semi-final, final, classification game) and sex on all dependent variables (alpha = 0.05). There was no difference between sexes for heart rate variables (p = 0.53 - 0.85). The greatest percentage (56.9 ± 20.1%) of game time was spent in heart rate zone 5 (90-100% peak heart rate). Overall RPE was higher in semi-finals (7.2 ± 1.5, p ≤ 0.001, ES: 1.27) and finals (7.7 ± 1.6 p ≤ 0.001, ES: 1.67) compared to pool games (5.1 ± 1.5). An analysis of the technical-tactical actions revealed that there were less steals in semi-finals (p = 0.01, ES = 0.56) and finals (p = 0.01, ES = 0.71) compared to pool games, with no sex-related differences present (p = 0.06 - 0.97). Players generally spent one minute on the bench for every three minutes on the court, creating a 3:1 work to rest ratio. Physical preparation programs for elite 3 × 3 basketball athletes should include exposure to high-intensity activity in which heart rates ≥80% of peak heart rate are reached for periods of time similar to that experienced during gameplay. A 3:1 work-to-rest ratio may be beneficial during conditioning training for this population.

Keywords

Performance analysis rating of perceived exertion (RPE)small-sided games sport physiology substitute players

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References

FIBA. 3x3 Introduction, http://www.fiba.basketball/3x3/introduction (2019, accessed 13 September 2019).

FIBA. Federation ranking, https://fiba3x3.com/en/rankings/federation.html (2019, accessed 13 September 2019).

Statler

Brown

Facility policies, procedures and legal issues. In: Haff

Triplett

(eds) Essentials of strength training and conditioning. 4th ed. Champaign, IL: Human Kinetics, 2015.

Henderson

Harries

Poulos

, et al. Rugby sevens match demands and measurement of performance: a review. Kinesiology 2018; 50: 49–59.

Naser

Ali

Macadam

Physical and physiological demands of futsal. J Exerc Sci Fit 2017; 15: 76–80.

FIBA. FIBA 3x3 official rules of the game, https://fiba3x3.com/en/rules.html (2019, accessed 13 September 2019).

Conte

Straigis

Clemente

, et al. Performance profile and game-related statistics of FIBA 3x3 basketball World Cup 2017. Biol Sport 2019; 36: 149–154.

Erčulj

Vidic

Leskošek

Shooting efficiency and structure of shooting in 3x3 basketball compared to 5x5 basketball. Int J Sports Sci Coach 2020; 15: 91–98.

Koh

Wang

CKJ

Mallett

CJ.

Discriminating factors between successful and unsuccessful elite youth Olympic female basketball teams. Int J Perf Anal Sport 2012; 12: 119–131.

10.

Koh

Wang

CKJ

Mallett

CJ.

Discriminating factors between successful and unsuccessful teams: a case study in elite youth Olympic basketball games. J Quant Anal Sport 2011; 7.

11.

Montgomery

Maloney

BD.

3x3 basketball: performance characteristics and changes during elite tournament competition. Int J Sports Physiol Perform 2018; 13: 1349–1356.

12.

Montgomery

Maloney

BD.

Three-by-three basketball: inertial movement and physiological demands during elite games. Int J Sports Physiol Perform 2018; 13: 1169–1174.

13.

Kraemer

Ratamess

French

DN.

Resistance training for health and performance. Curr Sports Med Rep 2002; 1: 165–171.

14.

Gamble

Principles of specificity and transfer of training effects. In: Gample

(ed), Strength and conditioning for team sports: Sport-specific physical preparation for high performance. Abingdon, Oxon: Routledge, 2013, pp. 1–9.

15.

Schuster

Howells

Robineau

, et al. Physical-preparation recommendations for elite rugby sevens performance. Int J Sports Physiol Perform 2018; 13: 255–267.

16.

Reid

Schneiker

Strength and conditioning in tennis: current research and practice. J Sci Med Sport 2008; 11: 248–256.

17.

Hedrick

Sport-specific: strength and power training for basketball. Natl Strength Conditioning Assoc J 1993; 15: 31–36.

18.

Bazanov

Integrative approach of the technical and tactical aspects in basketball coaching. PhD Thesis, Tallinn University, Estonia, 2007.

19.

Klusemann

Pyne

Foster

, et al. Optimising technical skills and physical loading in small-sided basketball games. J Sports Sci 2012; 30: 1463–1471.

20.

McGee

Coaching basketball technical and tactical skills. Champaign, IL: Human Kinetics, 2007.

21.

Clemente

FM.

Small-sided and conditioned games in basketball training: a review. Strength Cond J 2016; 38: 49–58.

22.

Berkelmans

Dalbo

Kean

, et al. Heart rate monitoring in basketball: applications, player responses, and practical recommendations. J Strength Cond Res 2018; 32: 2383–2399.

23.

Stojanović

Stojiljković

Scanlan

, et al. The activity demands and physiological responses encountered during basketball match-play: a systematic review. Sports Med 2018; 48: 111–135.

24.

Klusemann

Pyne

Hopkins

, et al. Activity profiles and demands of seasonal and tournament basketball competition. Int J Sports Physiol Perform 2013; 8: 623–629.

25.

Borg

Kaijser

A comparison between three rating scales for perceived exertion and two different work tests. Scand J Med Sci Sports 2006; 16: 57–69.

26.

McLaren

Smith

Spears

, et al. A detailed quantification of differential ratings of perceived exertion during team-sport training. J Sci Med Sport 2017; 20: 290–295.

27.

McHugh

ML.

Interrater reliability: The kappa statistic. Biochem Med (Zagreb) 2012; 22: 276–282.

28.

R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2018.

29.

Green

MacLeod

simr: an R package for power analysis of generalised linear mixed models by simulation. Methods Ecol Evol 2016; 7: 493–498.

30.

Bates

Mächler

Bolker

, et al. Fitting linear mixed-effects models using lme4. J Stat Softw 2015; 67: 1–48.

31.

Northey

Pumpa

Quinlan

, et al. Cognition in breast cancer survivors: a pilot study of interval and continuous exercise. J Sci Med Sport 2019; 22: 580–585.

32.

Hopkins

WG.

Linear models and effect magnitudes for research, clinical and practical applications. Sportscience 2010; 14: 49–57.

33.

McInnes

Carlson

Jones

, et al. The physiological load imposed on basketball players during competition. J Sports Sci 1995; 13: 387–397.

34.

Buchheit

Laursen

PB.

High-intensity interval training, solutions to the programming puzzle: part 1. Sports Med 2013; 43: 313–338.

35.

Buchheit

Laursen

PB.

High-intensity interval training, solutions to the programming puzzle: part 2. Sports Med 2013; 43: 927–954.

36.

Delextrat

Gruet

Bieuzen

Effects of small-sided games and high-intensity interval training on aerobic and repeated sprint performance and peripheral muscle oxygenation changes in elite junior basketball players. J Str Cond Res 2018; 32: 1882–1891.

37.

Barnett

Using recovery modalities between training sessions in elite athletes. Sports Med 2006; 36: 781–796.

38.

Leeder

Gissane

van Someren

, et al. Cold water immersion and recovery from strenuous exercise: a meta-analysis. Br J Sports Med 2012; 46: 233–240.

39.

Wiewelhove

Döweling

Schneider

, et al. A meta-analysis of the effects of foam rolling on performance and recovery. Front Physiol 2019; 10: 376.

40.

Ben Abdelkrim

Castagna

Jabri

, et al. Activity profile and physiological requirements of junior elite basketball players in relation to aerobic-anaerobic fitness. J Str Cond Res 2010; 24: 2330–2342.