Throughout the sport-science and sports-medicine literature, the term “elite” subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.
Alannah K.A. McKay, Trent Stellingwerff, Ella S. Smith, David T. Martin, Iñigo Mujika, Vicky L. Goosey-Tolfrey, Jeremy Sheppard, and Louise M. Burke
Grant C. Brechney, Jack Cannon, and Stephen P. Goodman
Weight cutting in combat sports is a prevalent practice whereby athletes voluntarily dehydrate themselves via various methods to induce rapid weight loss (RWL) to qualify for a lower weight category than that of their usual training body weight. The intention behind this practice is to regain the lost body mass and compete at a heavier mass than permitted by the designated weight category. The purpose of this study was to quantitatively synthesize the available evidence examining the effects of weight cutting on exercise performance in combat-sport athletes. Following a systematic search of the literature, meta-analyses were performed to compare maximal strength, maximal power, anaerobic capacity, and/or repeated high-intensity-effort performance before rapid weight loss (pre-RWL), immediately following RWL (post-RWL), and 3 to 36 hours after RWL following recovery and rapid weight gain (post-RWG). Overall, exercise performance was unchanged between pre-RWL and post-RWG (g = 0.22; 95% CI, −0.18 to 0.62). Between pre-RWL and post-RWL analyses revealed small reductions in maximal strength and repeated high-intensity-effort performance (g = −0.29; 95% CI, −0.54 to −0.03 and g = −0.37; 95% CI, −0.59 to −0.16, respectively; both P ≤ .03). Qualitative analysis indicates that maximal strength and power remained comparable between post-RWL and post-RWG. These data suggest that weight cutting in combat-sport athletes does not alter short-duration, repeated high-intensity-effort performance; however, there is evidence to suggest that select exercise performance outcomes may decline as a product of RWL. It remains unclear whether these are restored by RWG.
Lindsay B. Baker, Michelle A. King, David M. Keyes, Shyretha D. Brown, Megan D. Engel, Melissa S. Seib, Alexander J. Aranyosi, and Roozbeh Ghaffari
The purpose of this study was to compare a wearable microfluidic device and standard absorbent patch in measuring local sweating rate (LSR) and sweat chloride concentration ([Cl−]) in elite basketball players. Participants were 53 male basketball players (25 ± 3 years, 92.2 ± 10.4 kg) in the National Basketball Association’s development league. Players were tested during a moderate-intensity, coach-led practice (98 ± 30 min, 21.0 ± 1.2 °C). From the right ventral forearm, sweat was collected using an absorbent patch (3M Tegaderm™ + Pad). Subsequently, LSR and local sweat [Cl−] were determined via gravimetry and ion chromatography. From the left ventral forearm, LSR and local sweat [Cl−] were measured using a wearable microfluidic device and associated smartphone application-based algorithms. Whole-body sweating rate (WBSR) was determined from pre- to postexercise change in body mass corrected for fluid/food intake (ad libitum), urine loss, and estimated respiratory water and metabolic mass loss. The WBSR values predicted by the algorithms in the smartphone application were also recorded. There were no differences between the absorbent patch and microfluidic patch for LSR (1.25 ± 0.91 mg·cm−2·min−1 vs. 1.14 ±0.78 mg·cm−2·min−1, p = .34) or local sweat [Cl−] (30.6 ± 17.3 mmol/L vs. 29.6 ± 19.4 mmol/L, p = .55). There was no difference between measured and predicted WBSR (0.97 ± 0.41 L/hr vs. 0.89 ± 0.35 L/hr, p = .22; 95% limits of agreement = 0.61 L/hr). The wearable microfluidic device provides similar LSR, local sweat [Cl−], and WBSR results compared with standard field-based methods in elite male basketball players during moderate-intensity practices.
Arturo Casado, Fernando González-Mohíno, José María González-Ravé, and Carl Foster
Purpose: This review aimed to determine (1) performance and training characteristics such as training intensity distribution (TID), volume, periodization, and methods in highly trained/elite distance runners and (2) differences in training volume and TID between event distances in highly trained/elite distance runners. Methods: A systematic review of the literature was carried out using the PubMed/MEDLINE, Scopus, and Web of Science databases. Results: Ten articles met the inclusion criteria. Highly trained/elite distance runners typically follow a pyramidal TID approach, characterized by a decreasing training volume from zone 1 (at or below speed at first ventilatory/lactate threshold [LT]) to zone 2 (between speeds associated with either both ventilatory thresholds or 2 and 4 mmol·L−1 LTs [vLT1 and vLT2, respectively]) and zone 3 (speed above vVT2/vLT2). Continuous-tempo runs or interval training sessions at vLT2 in zone 2 (ie, medium and long aerobic intervals) and those in zone 3 (ie, anaerobic or short-interval training) were both used at least once per week each in elite runners, and they were used to increase the number of either vLT2 or z3 sessions to adopt either a pyramidal or a polarized approach, respectively. More pyramidal- and polarized-oriented approaches were used by marathoners and 1500-m runners, respectively. Conclusions: Highly trained and elite middle- and long-distance runners are encouraged to adopt a traditional periodization pattern with a hard day–easy day basis, consisting in a shift from a pyramidal TID used during the preparatory and precompetitive periods toward a polarized TID during the competitive period.
Kobe Vermeire, Michael Ghijs, Jan G. Bourgois, and Jan Boone
Purpose: The purpose of this commentary is to outline some of the pitfalls when using the fitness–fatigue model to unravel the interaction between training load and performance. By doing so, we encourage sport scientists and coaches to interpret the parameters from the model with some extra caution. Conclusions: Caution is needed when interpreting the fitness–fatigue model since the parameter values are influenced by the starting parameter values, the modeling technique, and the input of the model. Also, the use of general constants should be avoided since they do not account for interindividual differences and differences between training-load methods. Therefore, we advise sport scientists and coaches to use the model as a way to work more data-informed rather than working data-driven.
Jonathon Weakley, Shona L. Halson, and Iñigo Mujika
Context: To understand overtraining syndrome (OTS), it is important to detail the physiological and psychological changes that occur in athletes. Objectives: To systematically establish and detail the physiological and psychological changes that occur as a result of OTS in athletes. Methods: Databases were searched for studies that were (1) original investigations; (2) English, full-text articles; (3) published in peer-reviewed journals; (4) investigations into adult humans and provided (5) objective evidence that detailed changes in performance from prior to the onset of OTS diagnosis and that performance was suppressed for more than 4 weeks and (6) objective evidence of psychological symptoms. Results: Zero studies provided objective evidence of detailed changes in performance from prior to the onset of OTS diagnosis and demonstrated suppressed performance for more than 4 weeks accompanied by changes in psychological symptoms. Conclusions: All studies failed to provide evidence of changes in performance and mood from “healthy” to an overtrained state with evidence of prolonged suppression of performance. While OTS may be observed in the field, little data is available describing how physiological and psychological symptoms manifest. This stems from vague terminology, difficulties in monitoring for prolonged periods of time, and the need for prospective testing. Real-world settings may facilitate the collection of such data, but the ideal testing battery that can easily be conducted on a regular basis does not yet exist. Consequently, it must be concluded that an evidence base of sufficient scientific quality for understanding OTS in athletes is lacking.