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
Tai T. Tran, Lina Lundgren, Josh Secomb, Oliver R.L. Farley, G. Gregory Haff, Robert U. Newton, Sophia Nimphius, and Jeremy M. Sheppard
The purpose of this study was to develop and evaluate a drop-and-stick (DS) test method and to assess dynamic postural control in senior elite (SE), junior elite (JE), and junior development (JD) surfers. Nine SE, 22 JE, and 17 JD competitive surfers participated in a single testing session. The athletes completed 5 drop-and-stick trials barefoot from a predetermined box height (0.5 m). The lowest and highest time-to-stabilization (TTS) trials were discarded, and the average of the remaining trials was used for analysis. The SE group demonstrated excellent single-measures repeatability (ICC = .90) for TTS, whereas the JE and JD demonstrated good single-measures repeatability (ICC .82 and .88, respectively). In regard to relative peak landing force (rPLF), SE demonstrated poor single-measures reliability compared with JE and JD groups. Furthermore, TTS for the SE (0.69 ± 0.13 s) group was significantly (P = .04) lower than the JD (0.85 ± 0.25 s). There were no significant (P = .41) differences in the TTS between SE (0.69 ± 0.13 s) and JE (0.75 ± 0.16 s) groups or between the JE and JD groups (P = .09). rPLF for the SE (2.7 ± 0.4 body mass; BM) group was significantly lower than the JE (3.8 ± 1.3 BM) and JD (4.0 ± 1.1 BM), with no significant (P = .63) difference between the JE and JD groups. A possible benchmark approach for practitioners would be to use TTS and rPLF as a qualitative measure of dynamic postural control using a reference scale to discriminate among groups.
Tai T. Tran, Lina Lundgren, Josh Secomb, Oliver R.L. Farley, G. Gregory Haff, Laurent B. Seitz, Robert U. Newton, Sophia Nimphius, and Jeremy M. Sheppard
To determine whether a previously validated performance-testing protocol for competitive surfers is able to differentiate between Australian elite junior surfers selected (S) to the national team and those not selected (NS).
Thirty-two elite male competitive junior surfers were divided into 2 groups (S = 16, NS = 16). Their age, height, body mass, sum of 7 skinfolds, and lean-body-mass ratio (mean ± SD) were 16.17 ± 1.26 y, 173.40 ± 5.30 cm, 62.35 ± 7.40 kg, 41.74 ± 10.82 mm, 1.54 ± 0.35 for the S athletes and 16.13 ± 1.02 y, 170.56 ± 6.6 cm, 61.46 ± 10.10 kg, 49.25 ± 13.04 mm, 1.31 ± 0.30 for the NS athletes. Power (countermovement jump [CMJ]), strength (isometric midthigh pull), 15-m sprint paddling, and 400-m endurance paddling were measured.
There were significant (P ≤ .05) differences between the S and NS athletes for relative vertical-jump peak force (P = .01, d = 0.9); CMJ height (P = .01, d = 0.9); time to 5-, 10-, and 15-m sprint paddle; sprint paddle peak velocity (P = .03, d = 0.8; PV); time to 400 m (P = .04, d = 0.7); and endurance paddling velocity (P = .05, d = 0.7).
All performance variables, particularly CMJ height; time to 5-, 10-, and 15-m sprint paddle; sprint paddle PV; time to 400 m; and endurance paddling velocity, can effectively discriminate between S and NS competitive surfers, and this may be important for athlete profiling and training-program design.
Lina E. Lundgren, Tai T. Tran, Sophia Nimphius, Ellen Raymond, Josh L. Secomb, Oliver R.L. Farley, Robert U. Newton, Julie R. Steele, and Jeremy M. Sheppard
To develop and evaluate a multifactorial model based on landing performance to estimate injury risk for surfing athletes.
Five measures were collected from 78 competitive surfing athletes and used to create a model to serve as a screening tool for landing tasks and potential injury risk. In the second part of the study, the model was evaluated using junior surfing athletes (n = 32) with a longitudinal follow-up of their injuries over 26 wk. Two models were compared based on the collected data, and magnitude-based inferences were applied to determine the likelihood of differences between injured and noninjured groups.
The study resulted in a model based on 5 measures—ankle-dorsiflexion range of motion, isometric midthigh-pull lower-body strength, time to stabilization during a drop-and-stick (DS) landing, relative peak force during a DS landing, and frontal-plane DS-landing video analysis—for male and female professional surfers and male and female junior surfers. Evaluation of the model showed that a scaled probability score was more likely to detect injuries in junior surfing athletes and reported a correlation of r = .66, P = .001, with a model of equal variable importance. The injured (n = 7) surfers had a lower probability score (0.18 ± 0.16) than the noninjured group (n = 25, 0.36 ± 0.15), with 98% likelihood, Cohen d = 1.04.
The proposed model seems sensitive and easy to implement and interpret. Further research is recommended to show full validity for potential adaptations for other sports.