Search Results

Purpose: To assess the value of monitoring changes in fitness in professional soccer players, using changes in heart rate at submaximal intensity (HR_12km/h) over the velocity at a lactate concentration of 4 mmol/L (v_4mmol/L). The authors reexamined (1) a range of threshold magnitudes, which may improve detecting substantial individual changes and (2) the agreement between changes in these 2 variables. Methods: On at least 2 occasions during different moments of the season, 97 professional soccer players from Germany (first, second, and fourth division) completed an incremental test to determine HR_12km/h and v_4mmol/L. Optimal thresholds for changes in HR_12km/h and v_4mmol/L were assessed, using various methods (eg, smallest worthwhile change + typical error [TE], successive reiterations approach). Agreement between both variable changes was examined for the whole sample (225 comparisons), 4 different subgroups (depending on the moment of the season), and in an individual over 6 years (n = 23 tests). Results: Changes of 4.5% and 6.0% for HR_12km/h and v_4mmol/L, respectively, were rated as optimal to indicate substantial changes in fitness. Depending on the (sub)groups analyzed, these thresholds yielded 0% to 2% full mismatches, 22% to 38% partial agreements, and 60% to 78% full agreements in terms of fitness change interpretation between both variables. Conclusions: When lactate sampling during incremental tests is not possible, practitioners willing to monitor adult professional soccer players’ (Germany; first, second, and fourth division) training status can confidently implement short, 3-minute submaximal runs, with 4.5% changes in HR_12km/h being indicative of true substantial fitness changes, with 60% to 78% accuracy. Future studies should investigate the potential role of confounding factors of HR_12km/h to improve changes in fitness prediction.

Purpose: To investigate if error-correction-processing (ECP) algorithms in timing lights are able to eliminate or reduce measurement errors (MEs) and false signals due to swinging arms or legs. Methods: First, a dummy was used to check if ECP generally works. Second, 15 male sport students performed sprints over 5 and 10 m. Timing lights with ECP and a high-speed camera as a gold standard were used to simultaneously capture the athletes when passing the timing lights at start, 5 m, and 10 m. MEs of the timing lights were calculated for hip and upper body. Results: The dummy condition revealed that ECP is able to eliminate MEs. In real sprint conditions, MEs were highest for timing light at start and when using the hip as a reference. Overall, out of 120 trials, only 4 false signals were not detected by ECP. They all occurred at the start timing light, with highest MEs being 0.263 s (hip) and 0.134 s (upper body). Regarding 5 and 10 m, all false signals were eliminated. Conclusions: As proven through video analyses, ECP eliminated almost all false signals. The largest MEs at the start timing light were associated with a distinct forward leaning of the athletes. Therefore, clear instructions concerning starting posture should be given to further improve measurement accuracy of the start timing light. This approach could also enhance comparisons between athletes. Nevertheless, based on the results, timing lights employing ECP can be recommended for measuring short sprints.

Purpose: Replicating the studies of Gibson et al and Brownstein et al to assess performance, and physiological, and perceived variables during a repeated sprint protocol (RSP) with standardized versus self-selected recovery in youth soccer players. Methods: Nineteen male soccer players (age 13.1 [1.3] y) completed 2 separate RSPs. RSP₁: 10 × 30-m sprints with 30-second recovery and RSP₂: 10 × 30-m sprints interspersed with self-selected recovery periods. Mean time of both 10 × 30-m RSPs and self-selected recovery periods of RSP₂ were assessed. Heart rate, blood lactate concentration, and rates of perceived exertion were measured following RSPs. Results: RSP₂ revealed longer recovery periods (RSP₁: 30.0 [0.0] s; RSP₂: 39.0 [7.7] s; P < .001; effect size d = 1.648) with shorter repeated sprint time (mean 30-m sprint time: RSP₁: 4.965 [0.256] s; RSP₂: 4.865 [0.227] s; P = .014; d = 0.414). Blood lactate concentration (P = .002–.005; d = 0.730–0.958), heart rate (P < .001; d = 1.353), and rates of perceived exertion (RSP₁: 14.9 [1.9]; RSP₂: 12.9 [2.1]; P = .016; d = 1.046) were higher following RSP₁. Conclusion: In contrast to the original studies, the present replication study demonstrated that self-selected recovery periods during a RSP leads to better repeated sprint performance compared with standardized recovery periods in youth soccer players. The better repeated sprint performance with individual recovery durations in RSP₂ was achieved with less physiological and perceived effort.

Purpose: To raise attention to the quality of published validation protocols while comparing (in)consistencies and providing an overview on wearables, and whether they show promise or not. Methods: Searches from five electronic databases were included concerning the following eligibility criteria: (a) laboratory conditions with humans (<18 years), (b) device outcome must belong to one dimension of the 24-hr physical behavior construct (i.e., intensity, posture/activity type outcomes, biological state), (c) must include a criterion measure, and (d) published in a peer-reviewed English language journal between 1980 and 2021. Results: Out of 13,285 unique search results, 123 articles were included. In 86 studies, children <13 years were recruited, whereas in 26 studies adolescents (13–18 years) were recruited. Most studies (73.2%) validated an intensity outcome such as energy expenditure; only 20.3% and 13.8% of studies validated biological state or posture/activity type outcomes, respectively. We identified 14 wearables that had been used to validate outcomes from two or three different dimensions. Most (n = 72) of the identified 88 wearables were only validated once. Risk of bias assessment resulted in 7.3% of studies being classified as “low risk,” 28.5% as “some concerns,” and 71.5% as “high risk.” Conclusion: Overall, laboratory validation studies of wearables are characterized by low methodological quality, large variability in design, and a focus on intensity. No identified wearable provides valid results across all three dimensions of the 24-hr physical behavior construct. Future research should more strongly aim at biological state and posture/activity type outcomes, and strive for standardized protocols embedded in a validation framework.