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Franco M. Impellizzeri

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Franco M. Impellizzeri and Samuele M. Marcora

We propose that physiological and performance tests used in sport science research and professional practice should be developed following a rigorous validation process, as is done in other scientific fields, such as clinimetrics, an area of research that focuses on the quality of clinical measurement and uses methods derived from psychometrics. In this commentary, we briefly review some of the attributes that must be explored when validating a test: the conceptual model, validity, reliability, and responsiveness. Examples from the sport science literature are provided.

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Franco M. Impellizzeri, Samuele M. Marcora, and Aaron J. Coutts

Exercise is a stressor that induces various psychophysiological responses, which mediate cellular adaptations in many organ systems. To maximize this adaptive response, coaches and scientists need to control the stress applied to the athlete at the individual level. To achieve this, precise control and manipulation of the training load are required. In 2003, the authors introduced a theoretical framework to define and conceptualize the measurable constructs of the training process. They described training load as having 2 measurable components: internal and external load. The aim of this commentary is to extend, clarify, and refine both the theoretical framework and the definitions of internal and external training load to avoid misinterpretation of this concept.

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Ian Rollo, Franco M. Impellizzeri, Matteo Zago, and F. Marcello Iaia

The physical-performance profiles of subelite male footballers were monitored during 6 wk of a competitive season. The same squad of players played either 1 (1G, n = 15) or 2 (2G, n = 15) competitive matches per week. On weeks 0, 3, and 6, 48 h postmatch, players completed countermovement jump (CMJ), 10- and 20-m sprints, the Yo-Yo Intermittent Recovery Test (YYIRT), and the Recovery-Stress Questionnaire. Both groups undertook 2 weekly training sessions. The 2G showed after 6 wk lower YYIRT (–11% to 3%, 90% CI –15.8% to –6.8%; P < .001) and CMJ performances (–18.7%, –21.6 to –15.9%; P = .007) and higher 10-m (4.4%, 1.8–6.9%; P = .007) and 20-m sprints values (4.7%, 2.9% to 6.4%; P < .001). No differences were found at 3 wk (.06 < P < .99). No changes over time (.169 < P < .611) and no differences time × group interactions (.370 < P < .550) were found for stress, recovery, and the Stress Recovery Index. In conclusion players’ ability to sprint, jump, and perform repeated intense exercise was impaired when playing 2 competitive matches a week over 6 wk.

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Geoffrey M. Minett, Valentin Fels-Camilleri, Joshua J. Bon, Franco M. Impellizzeri, and David N. Borg

Purpose: This study aimed to examine the effect of peer presence on session rating of perceived exertion (RPE) responses. Method: Fourteen males, with mean (SD) age 22.4 (3.9) years, peak oxygen uptake 48.0 (6.6) mL·kg−1·min−1, and peak power output 330 (44) W, completed an incremental cycling test and 3 identical experimental sessions, in groups of 4 or 5. Experimental sessions involved 24 minutes of cycling, whereby the work rate alternated between 40% and 70% peak power output every 3 minutes. During cycling, heart rate was collected every 3 minutes, and session-RPE was recorded 10 minutes after cycling, in 3 communication contexts: in written form unaccompanied (intrapersonal communication), verbally by the researcher only (interpersonal communication), and in the presence of the training group. Session-RPE was analyzed using ordinal regression and heart rate using a linear mixed-effects model, with models fit in a Bayesian framework. Results: Session-RPE was voted higher when collected in the group’s presence compared with when written (odds ratio = 4.26, 95% credible interval = 1.27–14.73). On average, the posterior probability that session-RPE was higher in the group setting than when written was .53. Session-RPE was not different between the group and verbal, or verbal and written collection contexts. Conclusions: This study suggests that contextual psychosocial inputs influence session-RPE and highlights the importance of session-RPE users controlling the measurement environment when collecting votes.

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Matthew Weston, Warren Gregson, Carlo Castagna, Simon Breivik, Franco M. Impellizzeri, and Ric J. Lovell

Athlete case studies have often focused on the training outcome and not the training process. Consequently, there is a dearth of information detailing longitudinal training protocols, yet it is the combined assessment of both outcome and process that enhances the interpretation of physical test data. We were provided with a unique opportunity to assess the training load, physical match performance, and physiological fitness of an elite soccer referee from the referee’s final season before attaining full-time, professional status (2002) until the season when he refereed the 2010 UEFA Champions League and FIFA World Cup finals. An increased focus on on-field speed and gym-based strength training was observed toward the end of the study period and longitudinal match data showed a tendency for decreased total distances but an increased intensity of movements. Laboratory assessments demonstrated that VO2max remained stable (52.3 vs 50.8 mL-kg–1-min–1), whereas running speed at the lactate threshold (14.0 vs 12.0 km-h-1) and running economy (37.3 vs 43.4 mLkg–1min–1) both improved in 2010 compared with 2002.

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Clementine Grandou, Lee Wallace, Aaron J. Coutts, Lee Bell, and Franco M. Impellizzeri

Purpose: To provide details on the nature and symptomatic profile of training maladaptation in competitive resistance-based athletes to examine whether there are symptoms that may be used as prognostic indicators of overtraining. Identifying prognostic tools to assess for training maladaptation is essential for avoiding severe overtraining conditions. Methods: A Web-based survey was distributed to a cross-sectional convenience sample of competitive athletes involved in sports with a significant resistance-training component. The 46-item anonymous survey was distributed via industry experts and social media from July to August 2019. Results: The final sample included 605 responses (completion rate: 84%). About 71% of the respondents indicated that they had previously experienced an unexplained decrease in performance. Among those, the majority reported a performance decrement lasting 1 wk to 1 mo (43.8%). General feelings of fatigue were the most frequent self-reported symptom of maladaptation. Acute training maladaptation, lasting <1 mo, was also accompanied by symptoms of musculoskeletal aches and pain. In the majority of cases (92.5%), training maladaptation was accompanied by additional nontraining stressors. A greater proportion of the respondents with more severe maladaptation (>4 mo) were training to muscle failure. Conclusion: The results from this study support the multifactorial nature of training maladaptation. The multidimensional nature of fatigue and individual variability in symptomatic responses precludes definitive prognostic symptoms or differential diagnostic factors of functional/nonfunctional overreaching or the overtraining syndrome in resistance exercise.

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Thomas W.J. Lovell, Anita C. Sirotic, Franco M. Impellizzeri, and Aaron J. Coutts

Purpose:

The purpose of this study was to examine the validity of session rating of perceived exertion (sRPE) for monitoring training intensity in rugby league.

Methods:

Thirty-two professional rugby league players participated in this study. Training-load (TL) data were collected during an entire season and assessed via microtechnology (heart-rate [HR] monitors, global positioning systems [GPS], and accelerometers) and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and various other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during rugby league training.

Results:

There were significant within-individual correlations between sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 62.4% of the adjusted variance in sRPE-TL could be explained by TL measures of distance, impacts, body load, and training impulse (y = 37.21 + 0.93 distance − 0.39 impacts + 0.18 body load + 0.03 training impulse). Furthermore, 35.2% of the adjusted variance in sRPE could be explained by exercise-intensity measures of percentage of peak HR (%HRpeak), impacts/min, m/min, and body load/min (y = −0.01 + 0.37%HRpeak + 0.10 impacts/min + 0.17 m/min + 0.09 body load/min).

Conclusion:

A combination of internal and external TL factors predicts sRPE in rugby league training better than any individual measures alone. These findings provide new evidence to support the use of sRPE as a global measure of exercise intensity in rugby league training.

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Maurizio Fanchini, Roberto Ghielmetti, Aaron J. Coutts, Federico Schena, and Franco M. Impellizzeri

Purpose:

To examine the effect of different exercise-intensity distributions within a training session on the session rating of perceived exertion (RPE) and to examine the timing of measure on the rating.

Methods:

Nineteen junior players (age 16 ± 1 y, height 173 ± 5 cm, body mass 64 ± 6 kg) from a Swiss soccer team were involved in the study. Percentage of heart rate maximum (%HR) and RPE (Borg CR100®) were collected in 4 standardized training sessions (conditions). The Total Quality of Recovery scale (TQR) and a visual analogue scale (VAS) for pain of the lower limbs were used to control for the effect of pretraining fatigue. Every session consisted of three 20-min blocks of different intensities (ie, low-moderate-high) performed in a random order. RPE was collected after every block (RPE5), immediately after the session (RPE-end), and 30 min after the session (RPE30).

Results:

RPE5s of each block were different depending on the distribution sequence (P < .0001). RPE-end, TQR, and VAS values were not different between conditions (P = .57, P = .55, and P = .96, respectively). The %HR was significantly different between conditions (P = .008), with condition 3 higher than condition 2 (74.1 vs 70.2%, P = .02). Edwards training loads were not significantly different between conditions (P = .09). RPE30 was not different from RPE-end (P > .05).

Conclusions:

The current results show that coaches can design training sessions without concern about the influence of the within-session distribution of exercise intensity on session-RPE and that RPE can be collected at the end of the session or 30 min later.