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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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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.

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Maurizio Fanchini, Ivan Ferraresi, Roberto Modena, Federico Schena, Aaron J. Coutts and Franco M. Impellizzeri

Purpose:

To examine the construct validity of the session rating perceived exertion (s-RPE) assessed with the Borg CR100 scale to measure training loads in elite soccer and to examine if the CR100 is interchangeable and can provide more-accurate ratings than the CR10 scale.

Methods:

Two studies were conducted. The validity of the CR100 was determined in 19 elite soccer players (age 28 ± 6 y, height 180 ± 7 cm, body mass 77 ± 6 kg) during training sessions through correlations with the Edwards heart-rate method (study 1). The interchangeability with CR10 was assessed in 78 soccer players (age 19.3 ± 4.1 y, height 178 ± 5.9 cm, body mass 71.4 ± 6.1 kg) through the Bland–Altman method and correlations between change scores in different sessions. To examine whether the CR100 is more finely graded than the CR10, the proportions of responses corresponding to the verbal expressions were calculated (study 2).

Results:

Individual correlations between the Edwards method and s-RPE were large to very large (.52–.85). The mean difference between the 2 scales was –0.3 ± 0.33 AU (90% CI –0.41 to –0.29) with 95% limits of agreements (0.31 to –0.96 AU). Correlations between scales and between-changes scores were nearly perfect (.95 and .91–.98). Ratings corresponding to the verbal anchors were 49% in CR10 and 26% in CR100.

Conclusions:

The CR100 is valid for assessing the training load in elite soccer players. It can be used interchangeably with the CR10 and may provide more-precise measures of exercise intensity.

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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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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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Paolo Menaspà, Franco M. Impellizzeri, Eric C. Haakonssen, David T. Martin and Chris R. Abbiss

Purpose:

To determine the consistency of commercially available devices used for measuring elevation gain in outdoor activities and sports.

Methods:

Two separate observational validation studies were conducted. Garmin (Forerunner 310XT, Edge 500, Edge 750, and Edge 800; with and without elevation correction) and SRM (Power Control 7) devices were used to measure total elevation gain (TEG) over a 15.7-km mountain climb performed on 6 separate occasions (6 devices; study 1) and during a 138-km cycling event (164 devices; study 2).

Results:

TEG was significantly different between the Garmin and SRM devices (P < .05). The between-devices variability in TEG was lower when measured with the SRM than with the Garmin devices (study 1: 0.2% and 1.5%, respectively). The use of the Garmin elevation-correction option resulted in a 5–10% increase in the TEG.

Conclusions:

While measurements of TEG were relatively consistent within each brand, the measurements differed between the SRM and Garmin devices by as much as 3%. Caution should be taken when comparing elevation-gain data recorded with different settings or with devices of different brands.