The Cumulative Impacts of Fatigue during Overload Training Can Be Tracked Using Field-Based Monitoring of Running Stride Interval Correlations.

Integrating running gait coordination assessment into athlete monitoring systems could provide unique insight into training tolerance and fatigue-related gait alterations. This study investigated the impact of an overload training intervention and recovery on running gait coordination assessed by field-based self-testing. Fifteen trained distance runners were recruited to perform 1-week of light training (baseline), 2 weeks of heavy training (high intensity, duration, and frequency) designed to overload participants, and a 10-day light taper to allow recovery and adaptation. Field-based running assessments using ankle accelerometry and online short recovery and stress scale (SRSS) surveys were completed daily. Running performance was assessed after each training phase using a maximal effort multi-stage running test-to-exhaustion (RTE). Gait coordination was assessed using detrended fluctuation analysis (DFA) of a stride interval time series. Two participants withdrew during baseline training due to changed personal circumstances. Four participants withdrew during heavy training due to injury. The remaining nine participants completed heavy training and were included in the final analysis. Heavy training reduced DFA values (standardised mean difference (SMD) = -1.44 ± 0.90; p = 0.004), recovery (SMD = -1.83 ± 0.82; p less than 0.001), performance (SMD = -0.36 ± 0.32; p = 0.03), and increased stress (SMD = 1.78 ± 0.94; p = 0.001) compared to baseline. DFA values (p = 0.73), recovery (p = 0.77), and stress (p = 0.73) returned to baseline levels after tapering while performance trended towards improvement from baseline (SMD = 0.28 ± 0.37; p = 0.13). Reduced DFA values were associated with reduced performance (r2 = 0.55) and recovery (r2 = 0.55) and increased stress (r2 = 0.62). Field-based testing of running gait coordination is a promising method of monitoring training tolerance in running athletes during overload training.

The application of the Lyapunov Exponent to analyse human performance: A systematic review.

Variability is a normal component of human movement, allowing one to adapt to environmental perturbations. It can be analysed from linear or non-linear perspectives. The Lyapunov Exponent (LyE) is a commonly used non-linear technique, which quantifies local dynamic stability. It has been applied primarily to walking gait and appears to be limited application in other movements. Therefore, this systematic review aims to summarise research methodologies applying the LyE to movements, excluding walking gait. Four databases were searched using keywords related to movement variability, dynamic stability, LyE and divergence exponent. Articles written in English, using the LyE to analyse movements, excluding walking gait were included for analysis. 31 papers were included for data extraction. Quality appraisal was conducted and information related to the movement, data capture method, data type, apparatus, sampling rate, body segment/joint, number of strides/steps, state space reconstruction, algorithm, filtering, surrogation and time normalisation were extracted. LyE values were reported in supplementary materials (Appendix 2). Running was the most prevalent non-walking gait movement assessed. Methodologies to calculate the LyE differed in various aspects resulting in different LyE values being generated. Additionally, test-retest reliability, was only conducted in one study, which should be addressed in future.

Analysis of Movement Variability in Cycling: An Exploratory Study.

The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional aim was to determine if changes in the LyE existed across a trial. Twelve novice cyclists completed four sessions of cycling; one was a familiarisation session to determine a bike fit and become better accustomed to the time trial position and pacing of a 4000 m effort. IMUs were attached to the head, thorax, pelvis and left and right shanks to analyse segment accelerations, respectively, and reflective markers were attached to the participant to analyse neck, thorax, pelvis, hip, knee and ankle segment/joint angular kinematics, respectively. Both the IMU and VICON Nexus test-retest repeatability ranged from poor to excellent at the different sites. In each session, the head and thorax IMU acceleration LyE increased across the bout, whilst pelvic and shank acceleration remained consistent. Differences across sessions were evident in VICON Nexus segment/joint angular kinematics, but no consistent trend existed. The improved reliability and the ability to identify a consistent trend in performance, combined with their improved portability and reduced cost, advocate for the use of IMUs in analysing movement variability in cycling. However, additional research is required to determine the applicability of analysing movement variability during cycling.

Individually guided training prescription by heart rate variability and self-reported measure of stress tolerance in recreational runners: Effects on endurance performance.

The aim of this study was to determine the effect of endurance training individually guided by objective (Heart Rate Variability-HRV) or self-report measure of stress (DALDA-questionnaire) in comparison to predefined endurance training prescription for improving endurance performance in recreational runners. After a 2-week preliminary baseline period to establish resting HRV and self-reported measure of stress, thirty-six male recreational runners were randomly assigned to HRV-guided (GHRV; n = 12), DALDA-guided (GD; n = 12) or predefined training (GT; n = 12) prescription groups. Before and after 5-weeks of endurance training, participants performed a track field peak velocity (Vpeak_TF), time limit (Tlim) at 100% of Vpeak_TF and 5 km time-trial (5 km TT) tests. GD lead to higher improvements in Vpeak_TF (8.4 ± 1.8%; ES = 1.41) and 5 km TT (-12.8 ± 4.2%; ES = -1.97), than GHRV (6.6 ± 1.5% and -8.3 ± 2.8%; ES = -1.20; 1.24) and GT (4.9 ± 1.5% and -6.0 ± 3.3%; ES = -0.82; 0.68), respectively, with no differences for Tlim. Self-report measures of stress may be used to individualize endurance training prescription on a daily basis leading to better performance enhancement, which may be used with HRV for a holistic understanding of daily training-induce adaptations.

Correction: Bellenger et al. Wrist-Based Photoplethysmography Assessment of Heart Rate and Heart Rate Variability: Validation of WHOOP. Sensors 2021, 21, 3571.

The authors wish to correct the following errors in the original paper [...].

Evaluating the Typical Day-to-Day Variability of WHOOP-Derived Heart Rate Variability in Olympic Water Polo Athletes.

Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore enhanced application in athletes. However, it is important that the reliability of such technology is acceptable prior to its application in practical settings. Eleven elite male water polo players (age 28.8 ± 5.3 years [mean ± standard deviation]; height 190.3 ± 3.8 cm; body mass 95.0 ± 6.9 kg; international matches 117.9 ± 92.1) collected their HR and HRV daily via a WHOOP strap (WHOOP 3.0, CB Rank, Boston, MA, USA) over 16 weeks ahead of the 2021 Tokyo Olympic Games. The WHOOP strap quantified HR and HRV via wrist-based photoplethysmography during overnight sleep periods. The weekly (i.e., 7-day) coefficient of variation in lnRMSSD (lnRMSSDCV) and HR (HRCV) was calculated as a measure of day-to-day variability in lnRMSSD and HR, and presented as a mean of the entire recording period. The mean weekly lnRMSSDCV and HRCV over the 16-week period was 5.4 ± 0.7% (mean ± 95% confidence intervals) and 7.6 ± 1.3%, respectively. The day-to-day variability in WHOOP-derived lnRMSSD and HR is within or below the range of day-to-day variability in alternative lnRMSSD (~3-13%) and HR (~10-11%) assessment protocols, indicating that the assessment of HR and HRV by WHOOP does not introduce any more variability than that which is naturally present in these variables.

Supramaximal Interval Running Prescription in Australian Rules Football Players: A Comparison Between Maximal Aerobic Speed, Anaerobic Speed Reserve, and the 30-15 Intermittent Fitness Test.

ABSTRACT: Collison, J, Debenedictis, T, Fuller, JT, Gerschwitz, R, Ling, T, Gotch, L, Bishop, B, Sibley, L, Russell, J, Hobbs, A, and Bellenger, CR. Supramaximal interval running prescription in Australian Rules Football players: A comparison between maximal aerobic speed, anaerobic speed reserve and the 30-15 intermittent fitness test. J Strength Cond Res 36(12): 3409-3414, 2022-Accurate prescription of supramaximal interval running during Australian Rules Football (AF) preparatory periods is important to facilitate the specific targeting of physiological and neuromuscular adaptation. This study compared the variability in supramaximal interval running performance prescribed by proportion of maximal aerobic speed (MAS), anaerobic speed reserve (ASR), and 30-15 intermittent fitness test (30-15IFT) terminal speed. Seventeen male junior AF players first completed assessments of MAS, ASR, and 30-15IFT in a randomized order. They subsequently performed supramaximal interval running trials (15 seconds on: 15 seconds off until volitional exhaustion) at 120% MAS, 20% ASR, and 95% 30-15IFT in a randomized order. Variability in time to exhaustion (TTE) for each prescription method was calculated as the mean of the square root of the squared difference between the individual value and the mean value, and it was compared via repeated-measures analysis of variance with statistical significance set at p ≤ 0.05. Time to exhaustion during supramaximal interval running was not different between the prescription methods ( p = 0.58). Time to exhaustion residuals were reduced when prescribed by ASR compared with MAS (standardized mean difference [SMD] = -0.47; 29%); however, confidence intervals about this reduction indicated that there was some uncertainty in this finding (SMD = -1.03 to 0.09; p = 0.09). Trivial differences in TTE residuals were present when prescribed by 30-15IFT compared with MAS (SMD = -0.05 ± 0.59; p = 0.86). Although there was some uncertainty about the reduction in supramaximal interval running performance variability when prescribed by ASR compared with MAS, the 29% reduction exceeds the inherent error in TTE efforts (i.e., ∼9-15%) and may thus be considered practically meaningful. Reducing supramaximal interval running performance variability ensures similar physiological demand across individuals, potentially facilitating similar degrees of physiological adaptation.

Validation of Plantar Pressure and Reaction Force Measured by Moticon Pressure Sensor Insoles on a Concept2 Rowing Ergometer.

The purpose of this study was to determine the reliability and validity of plantar pressure and reaction force measured using the Moticon and Pedar-x sensor insoles while rowing on a Concept2 ergometer. Nineteen participants performed four 500 m trials of ergometer rowing at 22-24 strokes/min; two trials wearing Moticon insoles and two wearing Pedar-x insoles in a randomised order. Moticon and Pedar-x insoles both showed moderate to strong test-retest reliability (ICC = 0.57-0.92) for mean and peak plantar pressure and reaction force. Paired t-test demonstrated a significant difference (p < 0.001) between Moticon and Pedar-x insoles, effect size showed a large bias (ES > 1.13), and Pearson's correlation (r < 0.37) showed poor agreement for all plantar pressure and reaction force variables. Compared to Pedar-x, the Moticon insoles demonstrated poor validity, however, the Moticon insoles had strong reliability. Due to poor validity, caution should be used when considering Moticon insoles to assess changes in pressure and force reliably over time, across multiple trials or sessions. Moticon's wireless and user-friendly application would be beneficial for assessing and monitoring biomechanical parameters in rowing if validity between measures of interest and Moticon's results can be established.

Wrist-Based Photoplethysmography Assessment of Heart Rate and Heart Rate Variability: Validation of WHOOP.

Heart rate (HR) and HR variability (HRV) infer readiness to perform exercise in athletic populations. Technological advancements have facilitated HR and HRV quantification via photoplethysmography (PPG). This study evaluated the validity of WHOOP's PPG-derived HR and HRV against electrocardiogram-derived (ECG) measures. HR and HRV were assessed via WHOOP and ECG over 15 opportunities. WHOOP-derived pulse-to-pulse (PP) intervals were edited with WHOOP's proprietary filter, in addition to various filter strengths via Kubios HRV software. HR and HRV (Ln RMSSD) were quantified for each filter strength. Agreement was assessed via bias and limits of agreement (LOA), and contextualised using smallest worthwhile change (SWC) and coefficient of variation (CV). Regardless of filter strength, bias (≤0.39 ± 0.38%) and LOA (≤1.56%) in HR were lower than the CV (10-11%) and SWC (5-5.5%) for this parameter. For Ln RMSSD, bias (1.66 ± 1.80%) and LOA (±5.93%) were lowest for a 200 ms filter and WHOOP's proprietary filter, which approached or exceeded the CV (3-13%) and SWC (1.5-6.5%) for this parameter. Acceptable agreement was found between WHOOP- and ECG-derived HR. Bias and LOA in Ln RMSSD approached or exceeded the SWC/CV for this variable and should be interpreted against its own level of bias precision.

A validation study of the WHOOP strap against polysomnography to assess sleep.

The aim of the study was to compare the WHOOP strap - a wearable device that estimates sleep based on measures of movement and heart rate derived from actigraphy and photoplethysmography, respectively. Twelve healthy adults (6 females, 6 males, aged 22.9 ± 3.4 years) participated in a 10-day, laboratory-based protocol. A total of 86 sleeps were independently assessed in 30-s epochs using polysomnography and WHOOP. For WHOOP, bed times were entered by researchers and sleeps were scored by the company based on proprietary algorithms. WHOOP overestimated total sleep time by 8.2 ± 32.9 minutes compared to polysomnography, but this difference was non-significant. WHOOP was compared to polysomnography for 2-stage (i.e., wake, sleep) and 4-stage categorisation (i.e., wake, light sleep [N1 or N2], slow-wave sleep [N3], REM) of sleep periods. For 2-stage categorisation, the agreement, sensitivity to sleep, specificity for wake, and Cohen's kappa were 89%, 95%, 51%, and 0.49, respectively. For 4-stage categorisation, the agreement, sensitivity to light sleep, SWS, REM, and wake, and Cohen's kappa were 64%, 62%, 68%, 70%, 51%, and 0.47, respectively. In situations where polysomnography is impractical (e.g., field settings), WHOOP is a reasonable method for estimating sleep, particularly for 2-stage categorisation, if accurate bedtimes are manually entered.

Contextual Factors Impact Styles of Play in the English Premier League.

The aim of this study was to evaluate the influence of contextual factors on game styles in professional soccer. Interactions between styles and different playing venues, opposition quality, total match goals, and competing styles, were investigated using logistic regression and odds ratios. Game styles were characterised using the moments of play framework where three distinct styles have been identified: Style 1 - moderate strength in defence; Style 2 - dominance in transition, and Style 3 - strength in attacking phases of play. Results revealed that when playing at home against teams identified by Style 1, teams were more likely to play Style 2 (p < 0.05) or Style 3 (p < 0.001). Against top 10 opposition, teams were less likely to play Style 3 compared to either Style 1 (p < 0.001) or Style 2 (p < 0.001). Regardless of venue, teams were more likely to play Style 3 against bottom 10 sides compared to either Style 1 (p < 0.001) or Style 2 (p < 0.001), suggesting a hierarchical order between contextual factors. Competing game styles significantly impacted total match goals scored, whilst match results were also influenced by game style combinations. Overall, this study showed the significant effects of various contextual variables on game styles played by teams in the EPL.

Correction to: The effect of functional overreaching on parameters of autonomic heart rate regulation.

The original version of this article unfortunately contained a mistake. The presentation of Equation was incorrect.

The effect of functional overreaching on parameters of autonomic heart rate regulation.

PURPOSE: Correlations between fatigue-induced changes in performance and maximal rate of HR increase (rHRI) may be affected by differing assessment workloads. This study evaluated the effect of assessing rHRI at different workloads on performance tracking, and compared this with HR variability (HRV) and HR recovery (HRR). METHODS: Performance [5-min cycling time trial (5TT)], rHRI (at multiple workloads), HRV and HRR were assessed in 12 male cyclists following 1 week of light training (LT), 2 weeks of heavy training (HT) and a 10-day taper (T). RESULTS: 5TT very likely decreased after HT (effect size ± 90% confidence interval = -0.75 ± 0.41), and almost certainly increased after T (1.15 ± 0.48). rHRI at 200 W likely increased at HT (0.70 ± 0.60), and then likely decreased at T (-0.50 ± 0.70). rHRI at 120 and 160 W was unchanged. Pre-exercise HR during rHRI assessments at 120 W and 160 W likely decreased after HT (≤-0.39 ± 0.14), and correlations between these changes and rHRI were large to very large (r = -0.67 ± 0.31 and r = -0.78 ± 0.23). When controlling for pre-exercise HR, rHRI at 120 W very likely slowed after HT (-0.72 ± 0.44), and was moderately correlated with 5TT (r = 0.35 ± 0.32). RMSSD likely increased at HT (0.75 ± 0.49) and likely decreased at T (-0.49 ± 0.49). HRR following 5TT likely increased at HT (0.84 ± 0.31) and then likely decreased at T (-0.81 ± 0.35). CONCLUSIONS: When controlling for pre-exercise HR, rHRI assessment at 120 W most sensitively tracked performance. Increased RMSSD following HT indicated heightened parasympathetic modulation in fatigued athletes. HRR was only sensitive to changes in training status when assessed after maximal exercise, which may limit its practical applicability.

Maximal rate of heart rate increase correlates with fatigue/recovery status in female cyclists.

PURPOSE: Being able to identify how an athlete is responding to training would be useful to optimise adaptation and performance. The maximal rate of heart rate increase (rHRI), a marker of heart rate acceleration has been shown to correlate with performance changes in response to changes in training load in male athletes; however, it has not been established if it also correlates with performance changes in female athletes. METHODS: rHRI and cycling performance were assessed in six female cyclists following 7 days of light training (LT), 14 days of heavy training (HT) and a 10 day taper period. rHRI was the first derivative maximum of a sigmoidal curve fit to R-R data recorded during 5 min of cycling at 100 W. Cycling performance was assessed as work done (kJ) during time-trials of 5 (5TT) and 60 (60TT) min duration. RESULTS: 5TT was possibly decreased at HT (ES ± 90% confidence interval = - 0.16 ± 0.25; p = 0.60), while, 5TT and 60TT very likely to almost certainly increased from HT to taper (ES = 0.71 ± 0.24; p = 0.007 and ES = 0.42 ± 0.19; p = 0.02, respectively). Large within-subject correlations were found between rHRI, and 5TT (r = 0.65 ± 0.37; p = 0.02) and 60TT (r = 0.70 ± 0.31; p = 0.008). CONCLUSIONS: rHRI during the transition from rest to light exercise correlates with training induced-changes in exercise performance in females, suggesting that rHRI may be a useful monitoring tool for female athletes.

Predicting maximal aerobic speed through set distance time-trials.

PURPOSE: Knowledge of aerobic performance capacity allows for the optimisation of training programs in aerobically dominant sports. Maximal aerobic speed (MAS) is a measure of aerobic performance; however, the time and personnel demands of establishing MAS are considerable. This study aimed to determine whether time-trials (TT), which are shorter and less onerous than traditional MAS protocols, may be used to predict MAS. METHODS: 28 Australian Rules football players completed a test of MAS, followed by TTs of six different distances in random order, each separated by at least 48 h. Half of the participants completed TT distances of 1200, 1600 and 2000 m, and the others completed distances of 1400, 1800 and 2200 m. RESULTS: Average speed for the 1200 and 1400 m TTs were greater than MAS (P < 0.01). Average speed for 1600, 1800, 2000 and 2200 m TTs were not different from MAS (P > 0.08). Average speed for all TT distances correlated with MAS (r = 0.69-0.84; P < 0.02), but there was a negative association between the difference in average TT speed and MAS with increasing TT distance (r = -0.79; P < 0.01). Average TT speed over the 2000 m distance exhibited the best agreement with MAS. CONCLUSIONS: MAS may be predicted from the average speed during a TT for any distance between 1200 and 2200 m, with 2000 m being optimal. Performance of a TT may provide a simple alternative to traditional MAS testing.

The Effect of Water Dousing on Heat Strain and Performance During Endurance Running in the Heat.

OBJECTIVES: Assess the effect of water dousing on heat strain and performance during self- and fixed-paced exercise in the heat. DESIGN: Crossover, block-randomized controlled trial. METHODS: Thirteen trained runners completed a 10-km time trial (TT) and 60-minute fixed-pace run (60% velocity of V˙O2max) in a 30.4 °C, 47.4% relative humidity environment using either water dousing (DOUSE) or no dousing (CON). RESULTS: Ten-kilometer TT performance was faster in DOUSE compared to CON (44:11 [40:48, 47:34] vs 44:38 [41:21, 47:56] min:s; P = .033). Change in core temperature (Tc) was not different between groups during the TT (+0.02 [-0.04, 0.07] °C in DOUSE; P = .853) or fixed-pace run (+0.02 [-0.15, 0.18] °C; P = .848). Change in mean skin temperature was lower in DOUSE during the TT (-1.80 [-2.15, -1.46] °C; P < .001) and fixed-pace run (-1.38 [-1.81, -0.96] °C; P < .001). Heart rate was lower for DOUSE during the fixed-pace run (-3.5 [-6.8, -0.2] beats/min; P = .041) but not during the TT (-0.2 [-2.5, 2.1] beats/min; P = .853). Thermal sensation was lower for DOUSE during the TT (-49.3 [-72.1, -26.1] mm; P < .001) and fixed-pace run (-44.7 [-59.7, -29.6] mm; P < .001). Rating of perceived exertion was not different between groups for the TT (-0.2 [-0.7, 0.3]; P = .390) or fixed-pace run (-0.2 [-0.8, 0.4]; P = .480). Sweat rate was lower for DOUSE for the TT (-0.37 [-0.53, -0.22] L/h; P < .001) and fixed-pace run (-0.37 [-0.48, -0.26] L/h; P < .001). CONCLUSION: Water dousing improves 10-km TT performance in the heat but does not affect Tc. The positive change in thermal perception (via lower skin temperature) during the TT likely drives this benefit.

Optimizing Wearable Device and Testing Parameters to Monitor Running-Stride Long-Range Correlations for Fatigue Management in Field Settings.

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.

Contextual factors associated with running demands in elite Australian football: a scoping review.

OBJECTIVES: To identify and summarise the contextual factors associated with running demands in elite male Australian football (AF) gameplay that have been reported in the literature. DESIGN: Scoping review. METHODS: A contextual factor in sporting gameplay is a variable associated with the interpretation of results, yet is not the primary objective of gameplay. Systematic literature searches were performed in four databases to identify what contextual factors associated with running demands in elite male AF have been reported: Scopus, SPORTDiscus, Ovid Medline and CINAHL, for terms constructed around Australian football AND running demands AND contextual factors. The present scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and narrative synthesis was conducted. RESULTS AND CONCLUSION: A total of 36 unique articles were identified by the systematic literature search, which included 20 unique contextual factors. The most studied contextual factors were position (n = 13), time in game (n = 9), phases of play (n = 8), rotations (n = 7) and player rank (n = 6). Multiple contextual factors, such as playing position, aerobic fitness, rotations, time within a game, stoppages, and season phase appear to correlate with running demands in elite male AF. Many identified contextual factors have very limited published evidence and thus additional studies would help draw stronger conclusions.

Effects of Cold-Water Immersion Compared with Other Recovery Modalities on Athletic Performance Following Acute Strenuous Exercise in Physically Active Participants: A Systematic Review, Meta-Analysis, and Meta-Regression.

BACKGROUND: Studies investigating the effects of common recovery modalities following acute strenuous exercise have reported mixed results. OBJECTIVES: This systematic review with meta-analysis and meta-regression compared the effects of cold-water immersion (CWI) against other common recovery modalities on recovery of athletic performance, perceptual outcomes, and creatine kinase (CK) following acute strenuous exercise in physically active populations. STUDY DESIGN: Systematic review, meta-analysis, and meta-regression. METHODS: The MEDLINE, SPORTDiscus, Scopus, Web of Science, Cochrane Library, EmCare, and Embase databases were searched up until September 2022. Studies were included if they were peer reviewed, published in English, included participants who were involved in sport or deemed physically active, compared CWI with other recovery modalities following an acute bout of strenuous exercise, and included measures of performance, perceptual measures of recovery, or CK. RESULTS: Twenty-eight studies were meta-analysed. CWI was superior to other recovery methods for recovering from muscle soreness, and similar to other methods for recovery of muscular power and flexibility. CWI was more effective than active recovery, contrast water therapy and warm-water immersion for most recovery outcomes. Air cryotherapy was significantly more effective than CWI for the promotion of recovery of muscular strength and the immediate recovery of muscular power (1-h post-exercise). Meta-regression revealed that water temperature and exposure duration were rarely exposure moderators. CONCLUSION: CWI is effective for promoting recovery from acute strenuous exercise in physically active populations compared with other common recovery methods. PROTOCOL REGISTRATION: Open Science Framework: https://doi.org/10.17605/OSF.IO/NGP7C.

Heart-Rate Acceleration Is Linearly Related to Anaerobic Exercise Performance.

PURPOSE: To prescribe training loads to improve performance, one must know how an athlete is responding to loading. The maximal rate of heart-rate increase (rHRI) during the transition from rest to exercise is linearly related to changes in endurance exercise performance and can be used to infer how athletes are responding to changes in training load. Relationships between rHRI and anaerobic exercise performance have not been evaluated. The objective of this study was to evaluate relationships between rHRI and anaerobic exercise performance. METHODS: Eighteen recreational strength and power athletes (13 male and 5 female) were tested on a cycle ergometer for rHRI, 6-second peak power output, anaerobic capacity (30-s average power), and blood lactate concentration prior to (PRE), and 1 (POST1) and 3 (POST3) hours after fatiguing high-intensity interval cycling. RESULTS: Compared with PRE, rHRI was slower at POST1 (effect size [ES] = -0.38, P = .045) but not POST3 (ES = -0.36, P = .11). PPO was not changed at POST1 (ES = -0.12, P = .19) but reduced at POST3 (ES = -0.52, P = .01). Anaerobic capacity was reduced at POST1 (ES = -1.24, P < .001) and POST3 (ES = -0.83, P < .001), and blood lactate concentration was increased at POST1 (ES = 1.73, P < .001) but not at POST3 (ES = 0.75, P = .11). rHRI was positively related to PPO (B = 0.19, P = .03) and anaerobic capacity (B = 0.14, P = .005) and inversely related to blood lactate concentration (B = -0.22, P = .04). CONCLUSIONS: rHRI is linearly related to acute changes in anaerobic exercise performance and may indicate how athletes are responding to training to guide the application of training loads.