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Purpose: There are important methodological considerations for translating wearable-based gait-monitoring data to field settings. This study investigated different devices' sampling rates, signal lengths, and testing frequencies for athlete monitoring using dynamical systems variables. Methods: Secondary analysis of previous wearables data (N = 10 runners) from a 5-week intensive training intervention investigated impacts of sampling rate (100–2000 Hz) and signal length (100–300 strides) on detection of gait changes caused by intensive training. Primary analysis of data from 13 separate runners during 1 week of field-based testing determined day-to-day stability of outcomes using single-session data and mean data from 2 sessions. Stride-interval long-range correlation coefficient α from detrended fluctuation analysis was the gait outcome variable. Results: Stride-interval α reduced at 100- and 200- versus 300- to 2000-Hz sampling rates (mean difference: −.02 to −.08; P ≤.045) and at 100- compared to 200- to 300-stride signal lengths (mean difference: −.05 to −.07; P <.010). Effects of intensive training were detected at 100, 200, and 400 to 2000 Hz (P ≤.043) but not 300 Hz (P =.069). Within-athlete α variability was lower using 2-session mean versus single-session data (smallest detectable change:.13 and.22, respectively). Conclusions: Detecting altered gait following intensive training was possible using 200 to 300 strides and a 100-Hz sampling rate, although 100 and 200 Hz underestimated α compared to higher rates. Using 2-session mean data lowers smallest detectable change values by nearly half compared to single-session data. Coaches, runners, and researchers can use these findings to integrate wearable-device gait monitoring into practice using dynamic systems variables. [ABSTRACT FROM AUTHOR]

Step‐up variations are frequently used in sports performance to develop coordinated and powerful movements that transfer to running. This study aimed to quantify the kinetic characteristics of the first foot contact of four different step‐up variations. Ten professional rugby league players participated in this study and performed the Barbell One Box Step‐Up with Catch (BB1), Barbell Two Box Step‐Up (BB2), Vest Two Box Run (VEST) and Step‐Up Jump (JUMP) as part of routine in‐season strength training sessions during one season. Peak force, total impulse and maximal rate of force development (RFD) were measured from first foot contact on the step‐up box. Significantly greater peak force and RFD were observed in JUMP than any other variation (standardized mean difference; SMD: 3.9–5.5; p < 0.001). Total impulse was equal between JUMP and BB1, and significantly greater in JUMP than BB2 and VEST (SMD: 1.3–2.3; p < 0.001), and in BB1 than BB2 and VEST (SMD: 1.8–2.8; p < 0.001). Significantly larger peak force and RFD were observed in BB2 and VEST than BB1 (SMD: 0.6–0.7) and in total impulse in BB2 than VEST (SMD: 1.6) (p < 0.05). The results of this study highlight that step‐up exercise variations maximize different kinetic characteristics, which may transfer differently to athlete running performance. Highlights: The Step‐Up Jump variation was shown to produce the largest relative peak force, largest rate of force development (RFD) and equal largest total impulse and therefore may have the greatest transferability to maximal speed running through the maximization of the stance phase.The Barbell Two Box Step‐Up (BB2) and Vest Two Box Run (VEST), produced significantly greater peak relative force and RFD than the Barbell One Box Step‐Up with Catch (BB1) and therefore may have better transferability to acceleration ability.Coaches can use the findings of this study to assist their selection of step‐up variations that are best suited to develop running ability and should consider the testing results and individual requirements of each athlete. [ABSTRACT FROM AUTHOR]

This study aimed to validate a 7-sensor inertial measurement unit system against optical motion capture to estimate bilateral lower-limb kinematics. Hip, knee, and ankle sagittal plane peak angles and range of motion (ROM) were compared during bodyweight squats and countermovement jumps in 18 participants. In the bodyweight squats, left peak hip flexion (intraclass correlation coefficient [ICC] =.51), knee extension (ICC =.68) and ankle plantar flexion (ICC =.55), and hip (ICC =.63) and knee (ICC =.52) ROM had moderate agreement, and right knee ROM had good agreement (ICC =.77). Relatively higher agreement was observed in the countermovement jumps compared to the bodyweight squats, moderate to good agreement in right peak knee flexion (ICC =.73), and right (ICC =.75) and left (ICC =.83) knee ROM. Moderate agreement was observed for right ankle plantar flexion (ICC =.63) and ROM (ICC =.51). Moderate agreement (ICC >.50) was observed in all variables in the left limb except hip extension, knee flexion, and dorsiflexion. In general, there was poor agreement for peak flexion angles, and at least moderate agreement for joint ROM. Future work will aim to optimize methodologies to increase usability and confidence in data interpretation by minimizing variance in system-based differences and may also benefit from expanding planes of movement. [ABSTRACT FROM AUTHOR]

Purpose: Stride-to-stride fluctuations in running-stride interval display long-range correlations that break down in the presence of fatigue accumulated during an exhaustive run. The purpose of the study was to investigate whether long-range correlations in running-stride interval were reduced by fatigue accumulated during prolonged exposure to a high training load (functional overreaching) and were associated with decrements in performance caused by functional overreaching. Methods: Ten trained male runners completed 7 d of light training (LT7), 14 d of heavy training (HT14) designed to induce a state of functional overreaching, and 10 d of light training (LT10) in a fixed order. Running-stride intervals and 5-km time-trial (5TT) performance were assessed after each training phase. The strength of long-range correlations in running-stride interval was assessed at 3 speeds (8, 10.5, and 13 km/h) using detrended fluctuation analysis. Results: Relative to performance post-LT7, time to complete the 5TT was increased after HT14 (+18 s; P < .05) and decreased after LT10 (-20 s; P = .03), but stride-interval long-range correlations remained unchanged at HT14 and LT10 (P > .50). Changes in stride-interval long-range correlations measured at a 10.5-km/h running speed were negatively associated with changes in 5TT performance (r -.46; P = .03). Conclusions: Runners who were most affected by the prolonged exposure to high training load (as evidenced by greater reductions in 5TT performance) experienced the greatest reductions in stride-interval long-range correlations. Measurement of stride-interval long-range correlations may be useful for monitoring the effect of high training loads on athlete performance. [ABSTRACT FROM AUTHOR]

Wade, JA, Fuller, JT, Devlin, PJ, and Doyle, TLA. Senior and junior rugby league players improve lower-body strength and power differently during a rugby league season. J Strength Cond Res 36(5): 1367–1372, 2022—This investigation evaluated lower-body strength and power changes across a rugby league season in elite junior and senior athletes. Twenty-five senior and 20 junior rugby league players performed an isometric midthigh pull and countermovement jump at 3 time points in a National Rugby League training season (mid-preseason, end-preseason, and in-season). Linear fixed-effects models were used to compare isometric midthigh pull force and countermovement jump power between player experience groups (senior vs. junior) across the season phases (mid-preseason vs. end-preseason vs. and in-season). Cohen's effect sizes (ES) with 95% confidence intervals were calculated for pairwise comparisons. For senior players, absolute and relative strength (ES = 0.38, p < 0.007) and power (ES = 0.64, p < 0.008) increases were observed at end-preseason compared with mid-preseason, but there were no changes in-season (ES = 0.02, p > 0.571). For junior players, strength did not change (ES < 0.01, p > 0.738) and absolute power decreased (ES = 0.29, p < 0.014) at end-preseason compared with mid-preseason; large increases were evident for absolute and relative strength (ES = 1.43, p < 0.001) and power (ES = 0.62, p < 0.001) in-season. This research demonstrates senior and junior rugby league players exhibit unique patterns of improvements in lower-body strength and power across different phases of the season. This highlights the importance for training programs to differ between junior and senior athletes and target different physical qualities for both groups at different times of the season, thus providing guidance for strength and conditioning coaches. [ABSTRACT FROM AUTHOR]