Download PDF
CC BY-NC-ND 4.0 · Sports Med Int Open 2017; 1(06): E195-E199
DOI: 10.1055/s-0043-118650
Training & Testing
Eigentümer und Copyright ©Georg Thieme Verlag KG 2017

The within-participant Correlation between s-RPE and Heart Rate in Youth Sport

Sean Scantlebury
1   Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, UK
2   Queen Ethelburgas Collegiate, York, UK
,
Kevin Till
1   Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, UK
,
Greg Atkinson
3   Health and Social Care Institute, Teeside University, Middlesbrough, UK
,
Tom Sawczuk
1   Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, UK
2   Queen Ethelburgas Collegiate, York, UK
,
Ben Jones
1   Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, UK
2   Queen Ethelburgas Collegiate, York, UK
4   The Rugby Football League, Leeds, UK
› Author Affiliations
Further Information

Publication History

received 21 July 2017
revised 06 August 2017

accepted 08 August 2017

Publication Date:
29 September 2017 (online)

   Permissions and Reprints

Abstract

The monitoring of training load is important to ensure athletes are adapting optimally to a training stimulus. Before quantification of training load can take place, coaches must be confident that the tools available are accurate. We aimed to quantify the within-participant correlation between the session rating of perceived exertion (s-RPE) and summated heart rate zone (sHRz) methods of monitoring internal training load. Training load (s-RPE and heart rate) data were collected for rugby, soccer and field hockey field-based training sessions over a 14-week in-season period. A total of 397 sessions were monitored (rugby n=170, soccer n=114 and field hockey n=113). Within-subject correlations between s-RPE and sHRz were quantified for each sport using a general linear model. Large correlations between s-RPE and the sHRz method were found for rugby (r=0.68; 95% CI 0.59–0.75) and field hockey (r=0.60; 95% CI 0.47–0.71) with a very large correlation found for soccer (r=0.72; 95% CI 0.62–0.80). No significant differences were found between the correlations for each sport. The very large and large correlations found between s-RPE and the sHRz methods support the use of s-RPE in quantifying internal training load in youth sport.

Key word

training load - periodisation - soccer - rugby - hockey
 

  • References

  • 1 Achten J, Jeukendrup AE. Heart rate monitoring: applications and limitations. Sport Med 2003; 33: 517-538
    CrossrefPubMedGoogle Scholar
  • 2 Alexiou H, Coutts AJ. A comparison of methods used for quantifying internal training load in women soccer players. Int J Sports Physiol Perform 2008; 3: 320-330
    CrossrefPubMedGoogle Scholar
  • 3 Atkinson G, Batterham AM, Jones H, Taylor CE, Willie CK, Tzeng YC. Appropriate within-subject statistical models for the analysis of baroreflex sensitivity. Clin Physiol Funct Imaging 2011; 31: 80-82
    CrossrefPubMedGoogle Scholar
  • 4 Billows D, Reilly T, George K. Physiological demands of match play and training in elite adolescent footballers. In: Reilly T, Cabri J, Araújo D. eds. Science and Football V.. London and New York: Routledge; 2005: 469-477
    Google Scholar
  • 5 Bland JM, Altman DG. Calculating correlation coefficients with repeated observations: Part 1–Correlation within subjects. BMJ 1995; 310: 446
    CrossrefPubMedGoogle Scholar
  • 6 Borresen J, Lambert M. Quantifying training load: A comparison of subjective and objective methods. Int J Sports Physiol Perform 2008; 3: 16-30
    CrossrefPubMedGoogle Scholar
  • 7 Buchheit M. The 30-15 Intermittent Fitness Test: A new intermittent running field test for intermittent sport players-Part 1. Approch du Handball 2005; 87: 27-34
    PubMedGoogle Scholar
  • 8 Casamichana D, Castellano J, Calleja-Gonzalez J, San Roman J, Castagna C. Relationship between indicators of training load in soccer players. J Strength Cond Res 2013; 27: 369-374
    CrossrefPubMedGoogle Scholar
  • 9 Cohen J, Cohen P, West SG, Aiken Leona S. Applied multple regression/correlation analysis for the behavioural sciences. Routledge; 2013
    Google Scholar
  • 10 Coutts AJ, Rampinini E, Marcora SM, Castagna C, Impellizzeri FM. Physiological correlates of perceived exertion during soccer-specific exercise. J Sci Med Sport 2009; 12: 79-84
    CrossrefPubMedGoogle Scholar
  • 11 Cuff S, Loud K, O’Riordan MA. Overuse injuries in high school athletes. Clin Pediatr (Phila) 2010; 49: 731-736
    CrossrefPubMedGoogle Scholar
  • 12 Day M, Mcguigan M, Brice G, Foster C. Monitoring exercise intensity during resistance training using the session RPE scale. J Strength Cond Res 2004; 18: 353-358
    PubMedGoogle Scholar
  • 13 Difiori JP, Benjamin HJ, Brenner J, Gregory A, Jayanthi N, Landry GL, Luke A. Overuse injuries and burnout in youth sports: a position statement from the American Medical Society for Sports Medicine. Clin J Sport Med 2014; 24: 3-20
    CrossrefPubMedGoogle Scholar
  • 14 Edwards S. The heart rate monitor book. Med Sci Sport Exerc 1994; 26: 647
    PubMedGoogle Scholar
  • 15 Emery Ca, Meeuwisse WH, Hartmann SE. Evaluation of risk factors for injury in adolescent soccer: implementation and validation of an injury surveillance system. Am J Sports Med 2005; 33: 1882-1891
    CrossrefPubMedGoogle Scholar
  • 16 Fanchini M, Ghielmetti R, Coutts AJ, Schena F, Impellizzeri FM. Effect of training-session intensity distribution on session rating of perceived exertion in soccer players. Int J Sports Physiol Perform 2015; 10: 426-430
    CrossrefPubMedGoogle Scholar
  • 17 Foster C. Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sport Exerc 1998; 30: 1164-1168
    CrossrefPubMedGoogle Scholar
  • 18 Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dodge C. A new approach to monitoring exercise training. J Strength Cond Res 2001; 15: 109-115
    PubMedGoogle Scholar
  • 19 Gallo T, Cormack S, Gabbett T, Williams M, Lorenzen C. Characteristics impacting on session rating of perceived exertion training load in Australian footballers. J Sports Sci 2014; 33: 1-9
    PubMedGoogle Scholar
  • 20 Gomes RV, Moreira A, Lodo L, Capitani CD, Aoki MS, Foster C, Jenkins D. Ecological validity of session RPE method for quantifying internal training load in tennis. Int J Sports Sci Coach 2015; 10: 729-737
    CrossrefPubMedGoogle Scholar
  • 21 Groslambert A, Mahon AD. Perceived exertion : influence of age and cognitive development. Sports Med 2006; 36: 911-928
    CrossrefPubMedGoogle Scholar
  • 22 Haddad M, Padulo J, Chamari K. The usefulness of session rating of perceived exertion for monitoring training load despite several influences on perceived exertion. Int J Sports Physiol Perform 2014; 9: 882-883
    CrossrefPubMedGoogle Scholar
  • 23 Halson SL. Monitoring training load to understand fatigue in athletes. Sport Med 2014; 44: 139-147
    CrossrefPubMedGoogle Scholar
  • 24 Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 2009; 41: 3-12
    CrossrefPubMedGoogle Scholar
  • 25 Impellizeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora SM. Use of RPE-based training load in soccer. Med Sci Sport Exerc 2004; 36: 1042-1047
    CrossrefPubMedGoogle Scholar
  • 26 Johnston RD, Gabbett TJ, Seibold AJ, Jenkins DG. Influence of physical contact on neuromuscular fatigue and markers of muscle damage following small-sided games. J Sci Med Sport 2014; 17: 535-540
    CrossrefPubMedGoogle Scholar
  • 27 Kelly DM, Strudwick AJ, Atkinson G, Drust B, Gregson W. The within-participant correlation between perception of effort and heart rate-based estimations of training load in elite soccer players. J Sports Sci 2016; 34: 1-5
    CrossrefPubMedGoogle Scholar
  • 28 Matos NF, Winsley RJ, Williams CA. Prevalence of nonfunctional overreaching/overtraining in young English athletes. Med Sci Sports Exerc 2011; 43: 1287-1294
    CrossrefPubMedGoogle Scholar
  • 29 Phibbs P, Jones B, Roe G, Read D, Darrall-Jones J, Weakley J, Till K. We know they train, but what do they do? Implications for coaches working with adolescent rugby union players. Int J Sport Sci Coach 2016; 12: 175-182
    PubMedGoogle Scholar
  • 30 Read D, Jones B, Phibbs P, Roe G, Darrall-Jones J, Weakley J, Till K. Physical demands of representative match play in adolescent rugby union. J Strength Cond Res 2016; 35: 1290-1296
    PubMedGoogle Scholar
  • 31 Roe G, Till K, Phibbs P, Weakley J, Read D, Jones B. Changes in markers of fatigue following a competitive match in elite academy rugby union players. South African J Sport Med 2016; 28: 3-6
    PubMedGoogle Scholar
  • 32 Seiler S. What is best practice for training intensity and duration distribution in endurance athletes?. Int J Sport Physiol Perform 2010; 5: 276-291
    PubMedGoogle Scholar
  • 33 Seiler S, Jøranson K, Olesen BV, Hetlelid KJ. Adaptations to aerobic interval training: interactive effects of exercise intensity and total work duration. Scand J Med Sci Sport 2013; 23: 74-83
    CrossrefPubMedGoogle Scholar
  • 34 Stewart AM, Hopkins WG. Seasonal training and performance of competitive swimmers. J Sports Sci 2000; 18: 873-884
    CrossrefPubMedGoogle Scholar
  • 35 Sunderland C, Edwards PL. Activity profile and between-match variation in elite male field hockey. J Strength Cond Res 2017; 31: 758-764
    CrossrefPubMedGoogle Scholar
  • 36 Valovich McLeod TC, Decoster LC, Loud KJ, Micheli LJ, Parker JT, Sandrey MA, White C. National Athletic Trainers’ Association position statement: prevention of pediatric overuse injuries. J Athl Train 2011; 46: 206-220
    CrossrefPubMedGoogle Scholar
  • 37 Wallace LK, Slattery KM, Coutts AJ. The ecological validity and application of the session-RPE method for quantifying training loads in swimming. J Strength Cond Res 2009; 23: 33-38
    CrossrefPubMedGoogle Scholar