Apollo 13 was initially looking like it would be the smoothest flight ever. After the explosion of an oxygen tank, however, the astronauts were close to spending the rest of their lives in rotation around the planet. This well-known incident is used to further discuss the link, or lack thereof, between sport-science research and current field practices. There is a feeling that the academic culture and its publishing requirements have created a bit of an Apollo 13–like orbiting world (eg, journals and conferences) that is mostly disconnected from the reality of elite performance. The author discusses how poor research discredits our profession and provides some examples from the field where the research does not apply. In fact, the reality is that sport scientists often do not have the right answers. Some perspectives to improve translation are finally discussed, including a rethink of the overall publishing process: promotion of relevant submission types (eg, short-paper format, short reports, as provided by IJSPP), improvement of the review process (faster turnaround, reviewers identified to increase accountability, and, in turn, review quality), and media types (eg, free downloads, simplified versions published in coaching journals, book chapters, infographics, dissemination via social media). When it comes to guiding practitioners and athletes, instead of using an evidence-based approach, we should rather promote an “evidence-led” or “informed-practice” approach—one that appreciates context over simple scientific conclusions.
The first sport-science-oriented and comprehensive paper on magnitude-based inferences (MBI) was published 10 y ago in the first issue of this journal. While debate continues, MBI is today well established in sport science and in other fields, particularly clinical medicine, where practical/clinical significance often takes priority over statistical significance. In this commentary, some reasons why both academics and sport scientists should abandon null-hypothesis significance testing and embrace MBI are reviewed. Apparent limitations and future areas of research are also discussed. The following arguments are presented: P values and, in turn, study conclusions are sample-size dependent, irrespective of the size of the effect; significance does not inform on magnitude of effects, yet magnitude is what matters the most; MBI allows authors to be honest with their sample size and better acknowledge trivial effects; the examination of magnitudes per se helps provide better research questions; MBI can be applied to assess changes in individuals; MBI improves data visualization; and MBI is supported by spreadsheets freely available on the Internet. Finally, recommendations to define the smallest important effect and improve the presentation of standardized effects are presented.
Claude Karcher and Martin Buchheit
To (1) assess the usefulness of countermovement jump (CMJ) testing to predict handball-specific jumping ability and (2) examine the acute effect of transiently modified jumping ability (ie, flight time) on shooting efficiency in wing players.
Eleven young highly trained wing players performed 3 CMJs and 10 typical wing jump shots with 3 different modalities: without any constraint (CONTROL), while stepping on a 14-cm step (STEP), and wearing a weighted vest (VEST, 5% of body mass). Flight time and the associated scoring efficiency during the jump shots were recorded.
There was no clear correlation between jump shot and CMJ flight time, irrespective of the condition (r = .04–.18). During jump shots, flight time was most likely longer (effect size [ES] = 1.42–1.97) with VEST (635.4 ± 31 ms) and STEP (615.3 ± 32.9 ms) than CONTROL (566 ± 30.5 ms) and very likely longer with VEST than with STEP (ES = 0.6). The correlation between scoring efficiency and jump-shot flight time was not substantial either in each modality or for all shots pooled. The difference in scoring efficiency between the 3 jumps with the longest vs shortest flight times was either small (VEST, 48% vs 42%) or nonsubstantial (2 other conditions).
The use of CMJ as a predictor of handball-specific jumping ability is questioned given the dissociation between CMJ and jump-shot flying time. These results also show that transiently affected flight time may not affect scoring efficiency, which questions the importance of jumping ability for success in wing players.
Martin Buchheit and Alireza Rabbani
The aim of the current study was to examine the relationship between performance of the Yo-Yo Intermittent Recovery Test Level 1 (Yo-YoIR1) and the 30–15 Intermittent Fitness Test (30-15IFT) and to compare the sensitivity of both tests to training. Fourteen young soccer players performed both tests before and after an 8-wk training intervention, which included 6 sessions/wk: 2 resistance training sessions, 2 high-intensity interval training sessions after technical training (4 sets of 3:30 min of generic running and small-sided games [4v4] during the first and second 4-wk periods, respectively [90–95% maximal HR], interspersed with 3 min at 60–70% maximal HR), and 2 tactical-only training sessions. There was a large correlation between 30-15IFT and Yo-YoIR1 (r = .75, 90% confidence limits [CL] 0.57;0.86). While within-test percentage changes suggested a greater sensitivity to training for the Yo-YoIR1 (+35%, 90%CL 24;45) than for the 30-15IFT (+7%; 4;10), these changes were similarly rated as almost certain (with chances for greater/similar/lower values after training of 100/0/0 for both tests) and moderate, ie, standardized difference, ES = +1.2 90%CL (0.9;1.5) for Yo-YoIR1 and ES = +1.1 (0.7;1.5) for 30-15IFT. The difference in the change between the 2 tests was clearly trivial (0/100/0, ES = –0.1, 90%CL –0.1;–0.1). Both tests might evaluate slightly different physical capacities, but their sensitivity to training is almost certainly similar. These results also highlight the importance of using standardized differences instead of percentage changes in performance to assess the actual training effect of an intervention.
Martin Buchheit, Yannick Cholley, and Philippe Lambert
To examine in elite soccer players after traveling across 6 time zones some psychometric and physiological responses to a competitive camp in the heat.
Data from 12 elite professional players (24.6 ± 5.3 y) were analyzed. They participated in an 8-d preseason summer training camp in Asia (heat index 34.9°C ± 2.4°C). Players’ activity was collected during all training sessions and the friendly game using 15-Hz GPS. Perceived training/playing load was estimated using session rating of perceived exertion (RPE) and training/match duration. Psychometric measures of wellness were collected on awakening before, during, and after the camp using simple questionnaires. Heart-rate (HR) response to a submaximal 4-min run (12 km/h) and the ratio between velocity and force-load (accelerometer-derived measure, a marker of neuromuscular efficiency) response to four ~60-m runs (22–24 km/h) were collected before, at the end of, and after the camp.
After a large increase, the RPE:m/min ratio decreased substantially throughout the camp. There were possible small increases in perceived fatigue and small decreases in subjective sleep quality on the 6th day. There were also likely moderate (~3%) decreases in HR response to the submaximal run, both at the end of and after the camp, which were contemporary to possible small (~8%) and most likely moderate (~19%) improvements in neuromuscular efficiency, respectively.
Despite transient increases in fatigue and reduced subjective sleep quality by the end of the camp, these elite players showed clear signs of heat acclimatization that were associated with improved cardiovascular fitness and neuromuscular running efficiency.
Martin Buchheit and Ben Michael Simpson
With the ongoing development of microtechnology, player tracking has become one of the most important components of load monitoring in team sports. The 3 main objectives of player tracking are better understanding of practice (provide an objective, a posteriori evaluation of external load and locomotor demands of any given session or match), optimization of training-load patterns at the team level, and decision making on individual players’ training programs to improve performance and prevent injuries (eg, top-up training vs unloading sequences, return to play progression). This paper discusses the basics of a simple tracking approach and the need to integrate multiple systems. The limitations of some of the most used variables in the field (including metabolic-power measures) are debated, and innovative and potentially new powerful variables are presented. The foundations of a successful player-monitoring system are probably laid on the pitch first, in the way practitioners collect their own tracking data, given the limitations of each variable, and how they report and use all this information, rather than in the technology and the variables per se. Overall, the decision to use any tracking technology or new variable should always be considered with a cost/benefit approach (ie, cost, ease of use, portability, manpower/ability to affect the training program).