load defined by the psychophysiological responses, specifically, indicators initiated by the body to cope with the elicited external load. 2 , 3 A perceptual indicator of internal load is commonly assessed using a version of rating of perceived exertion (RPE). 3 – 5 It is often described as a
Jessica L. Bigg, Alexander S.D. Gamble, and Lawrence L. Spriet
Javier Raya-González, Fabio Yuzo Nakamura, Daniel Castillo, Javier Yanci, and Maurizio Fanchini
noncontact injuries, both external load (ie, global positioning system) 15 and internal load (ie, session rating of perceived exertion [sRPE]) 13 variables have been used. However, according to the UEFA Elite Club Injury Study, 16 internal load markers have greater relevance as a risk factor than the
Vicente de Dios-Álvarez, Pello Alkain, Julen Castellano, and Ezequiel Rey
classified into internal load, which represents the biological (psychological and physiological) responses of play to a given external load, and external load, which involves objective measures of the work performed by the athletes during training or competition ( 4 ). In recent years, there has been an
Alice Iannaccone, Andrea Fusco, Antanas Skarbalius, Audinga Kniubaite, Cristina Cortis, and Daniele Conte
include inertial sensors gyroscopes, accelerometers, and magnetometers. 9 Differently, the internal load (IL) represents the psychophysiological response of the athlete to a given training stimulus. 10 , 11 Specifically, IL indicates the functional outcome of a given EL, and it can be used as primary
Ibai Guridi Lopategui, Julen Castellano Paulis, and Ibon Echeazarra Escudero
the days, revealing it as the toughest session of the week. On the other hand, preOM is shown as the day with the lowest internal load. Figure 1 —Wll and RPE of the players in the different types of training sessions: STR, DUR, VEL, preOM, and OM. DUR indicates duration day; OM, official match day
Shaun J. McLaren, Michael Graham, Iain R. Spears, and Matthew Weston
To investigate the sensitivity of differential ratings of perceived exertion (dRPE) as measures of internal load.
Twenty-two male university soccer players performed 2 maximal incremental-exercise protocols (cycle, treadmill) on separate days. Maximal oxygen uptake (V̇O2max), maximal heart rate (HRmax), peak blood lactate concentration (B[La]peak), and the preprotocol-to-postprotocol change in countermovement-jump height (ΔCMJH) were measured for each protocol. Players provided dRPE (CR100) for breathlessness (RPE-B) and leg-muscle exertion (RPE-L) immediately on exercise termination (RPE-B0, RPE-L0) and 30 min postexercise (RPE-B30, RPE-L30). Data were analyzed using magnitude-based inferences.
There were clear between-protocols differences for V̇O2max (cycle 46.5 ± 6.3 vs treadmill 51.0 ± 5.1 mL · kg−1 · min−1, mean difference –9.2%; ±90% confidence limits 3.7%), HRmax (184.7 ± 12.7 vs 196.7 ± 7.8 beats/min, –6.0%; ±1.7%), B[La]peak (9.7 ± 2.1 vs 8.5 ± 2.0 mmol/L, 15%; ±10%), and ΔCMJH (–7.1 ± 4.2 vs 0.6 ± 3.6 cm, –23.2%; ±5.4%). Clear between-protocols differences were recorded for RPE-B0 (78.0 ± 11.7 vs 94.7 ± 9.5 AU, –18.1%; ±4.5%), RPE-L0 (92.6 ± 9.7 vs 81.3 ± 14.1 AU, 15.3%; ±7.6%), RPE-B30 (70 ± 11 vs 82 ± 13 AU, –13.8%; ±7.3%), and RPE-L30 (86 ± 12 vs 65 ± 19 AU, 37%; ±17%). A substantial timing effect was observed for dRPE, with moderate to large reductions in all scores 30 min postexercise compared with scores collected on exercise termination.
dRPE enhance the precision of internal-load measurement and therefore represent a worthwhile addition to training-load-monitoring procedures.
Renato Barroso, Diego F. Salgueiro, Everton C. do Carmo, and Fábio Y. Nakamura
To assess swimmers’ session rating of perceived exertion (sRPE) after standardized sets of interval swimming training performed at the same relative intensity but with different total volume and repetition distance.
Thirteen moderately trained swimmers (21.1 ± 1.1 y, 178 ± 6 cm, 74.1 ± 8.3 kg, 100-m freestyle 60.2 ± 2.9 s) performed 4 standardized sets (10 × 100-m, 20 × 100-m, 10 × 200-m, and 5 × 400-m) at the same relative intensity (ie, critical speed), and 1 coach (age 31 y, 7 y coaching experience) rated their efforts. Swimmers’ sRPE was assessed 30 min after the training session. Coach sRPE was collected before each training session. Internal load was calculated by multiplying sRPE by session duration.
When bouts with the same repetition distance and different volumes (10 × 100-m vs 20 × 100-m) are compared, sRPE and internal load are higher in 20 × 100-m bouts. When maintaining constant volume, sRPE and internal load (20 × 100-m, 10 × 200-m, and 5 × 400-m) are higher only in 5 × 400-m bouts. The coach’s and swimmers’ sRPE differed in 10 × 200-m and 5 × 400-m.
These results indicate that sRPE in swimming is affected not only by intensity but also by volume and repetition distance. In addition, swimmers’ and the coach’s sRPE were different when longer repetition distances were used during training sessions. Therefore, care should be taken when prescribing swimming sessions with longer volume and/or longer repetition distances.
Nacho Torreño, Diego Munguía-Izquierdo, Aaron Coutts, Eduardo Sáez de Villarreal, Jose Asian-Clemente, and Luis Suarez-Arrones
To analyze the match running profile, distance traveled over successive 15 min of match play, heart rates (HRs), and index of performance efficiency (effindex) of professional soccer players with a global positioning system (GPS) and HR in official competition.
Twenty-six professional players were investigated during full matches in competitive club-level matches (N = 223). Time–motion data and HR were collected using GPS and HR technology.
The relative total distance was 113 ± 11 m/min, with substantial differences between halves. For all playing positions, a substantial decrease in total distance and distance covered at >13.0 km/h was observed in the second half in comparison with the first. The decrease during the second half in distance covered at >13.0 km/h was substantially higher than in total distance. The average HR recorded was 86.0% maximal HR, and the relationship between external and internal load (effindex) was 1.3, with substantial differences between halves in all playing positions, except strikers for effindex. Wide midfielders reflected substantially the lowest mean HR and highest effindex, whereas center backs showed substantially the lowest effindex of all playing positions.
The current study confirmed the decrement in a player’s performance toward the end of a match in all playing positions. Wide midfielders displayed the highest and fittest levels of physical and physiological demands, respectively, whereas center backs had the lowest and least-fit levels of physical and physiological demands, respectively. The position-specific relationship between external and internal load confirms that players with more overall running performance during the full match were the best in effindex.
Marco Cardinale and Matthew C. Varley
The need to quantify aspects of training to improve training prescription has been the holy grail of sport scientists and coaches for many years. Recently, there has been an increase in scientific interest, possibly due to technological advancements and better equipment to quantify training activities. Over the last few years there has been an increase in the number of studies assessing training load in various athletic cohorts with a bias toward subjective reports and/or quantifications of external load. There is an evident lack of extensive longitudinal studies employing objective internal-load measurements, possibly due to the cost-effectiveness and invasiveness of measures necessary to quantify objective internal loads. Advances in technology might help in developing better wearable tools able to ease the difficulties and costs associated with conducting longitudinal observational studies in athletic cohorts and possibly provide better information on the biological implications of specific external-load patterns. Considering the recent technological developments for monitoring training load and the extensive use of various tools for research and applied work, the aim of this work was to review applications, challenges, and opportunities of various wearable technologies.
Håvard Wiig, Thor Einar Andersen, Live S. Luteberget, and Matt Spencer
. Training load is typically classified into external load, defined as the work completed by an athlete measured independently of his or her internal characteristics, or into internal load, defined as the relative physiological stress imposed on the athlete. 4 Hence, the internal load is determined by an