Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance

Abstract

This study investigated the influence of the regression model and initial intensity during an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and performance in elite-standard runners. Twenty-three well-trained runners completed a discontinuous incremental running test on a treadmill. Speed started at 9 km · h^?1 and increased by 1.5 km · h^?1 every 4 min until exhaustion, with a minute of recovery for blood collection. Lactate–speed data were fitted by exponential and polynomial models. The lactate threshold was determined for both models, using all the co-ordinates, excluding the first and excluding the first and second points. The exponential lactate threshold was greater than the polynomial equivalent in any co-ordinate condition (P < 0.001). For both models, the lactate threshold was lower when all co-ordinates were used than when the first and the first and second points were excluded (P < 0.001). 10-km race pace was correlated with both the exponential and polynomial lactate thresholds for all the co-ordinate conditions (r ≥ 0.75, P < 0.001 and r ≥ 0.56, P < 0.05, respectively). The results suggest that the exponential lactate threshold should be used instead of the polynomial equivalent since it is more strongly associated with performance and is independent of the initial intensity of the test.     

Estimation of the maximal lactate steady state in postmenopausal women

This study aimed to estimate the maximal lactate steady-state velocity (_vMLSS) from non-invasive bloodless variables and/or blood lactate-related thresholds (BL_RTs) measured during an Incremental submaximal Shuttle Test (IST), and to determine whether the addition of a Constant Velocity Test (CVT) could improve the estimation. Seventy-five postmenopausal women conducted an IST to determine several BL_RTs and bloodless variables, and two to seven CVTs to determine _vMLSS. Determined BL_RTs were conventionally used lactate threshold (LT) measured either visually (_vLT_+0.1mM) or mathematically (_vLE_min), and 0.5, 1 and 1.5 mmol·L^?1 above LT, along with fixed BL_RTs. The best single predictor of _vMLSS (7.1 ± 1.0 km·h^?1) was _vLE_min+1.5mM (R² = 0.80, P < 0.001; SEE = 0.46 km·h^?1). The combination of BL_RTs and bloodless variables improved the estimation of _vMLSS (R² = 0.85, P < 0.001; SEE = 0.38 km·h^?1). The addition of a CVT still improved the prediction of _vMLSS up to 89.2%, with lower SEE (0.32 km·h^?1). This study suggests that _vLE_min-related thresholds obtained from a single submaximal IST are accurate estimates of _vMLSS in postmenopausal women, and thus the time-consuming procedure of _vMLSS testing could be avoided. Performing an additional CVT is encouraged because it improves the prediction of _vMLSS.     

Lactate Equivalent for Maximal Lactate Steady State Determination in Soccer

ABSTRACT

Purpose: The association between an overlooked classical Lactate Threshold (LT), named “Minimum Lactate Equivalent” (LE_min), with Maximal Lactate Steady State (MLSS) has been recently described with good MLSS prediction results in endurance-trained runners. This study aimed to determine the applicability of LE_min to predict MLSS in lower aerobic-conditioned individuals compared to well-established blood lactate-related thresholds (BLTs). Method: Fifteen soccer players [velocity at MLSS (MLSS_V) 13.2 ± 1.0 km·h^?1; coefficient of variation (CV) 7.6%] conducted a submaximal discontinuous incremental running test to determine BLTs and 3–6 constant velocity running tests to determine MLSS_V. Results: LE_min did not differ from conventional LTs (p > .05) and was 24% lower than MLSS (p < .001; ES: 3.26). Among LTs, LE_min best predicted MLSS_V (r = 0.83; p < .001; SEE = 0.59 km·h^?1). There was no statistical difference between MLSS and estimated MLSS using LE_min prediction formula (p = .99; ES: 0.001). Mean bias and limits of agreement were 0.00 ± 0.58 km·h^?1 and ±1.13 km·h^?1, respectively. LE_min best predicted MLSS_V (r = 0.92; p < .001; SEE = 0.54 km·h^?1) in the pooled data of soccer players and endurance-trained runners of the previous study (n = 28; MLSS_V range 11.2–16.5 km·h^?1; CV 9.8%). Conclusion: Results support LE_min to be one of the best single predictors of MLSS. This study is the sole study providing specific operational regression equations to estimate the impractical gold standard MLSS_V in soccer players by means of a BLT measured during a submaximal single-session test.     

Optimization of Maximal Rate of Heart Rate Increase Assessment in Runners

Purpose: Correlations between fatigue-induced changes in exercise performance and maximal rate of heart rate (HR) increase (rHRI) may be affected by exercise intensity during assessment. This study evaluated the sensitivity of rHRI for tracking performance when assessed at varying exercise intensities. Method: Performance (time to complete a 5-km treadmill time-trial [5TTT]) and rHRI were assessed in 15 male runners following 1 week of light training, 2 weeks of heavy training (HT), and a 10-day taper (T). Maximal rate of HR increase (measured in bpm·s^?1) was the first derivative maximum of a sigmoidal curve fit to HR data recorded during 5 min of running at 8 km·h^?1 (rHRI_8km·h^?1), and during subsequent transition to 13 km·h^?1 (rHRI_{8–13km·h^?1}) for a further 5 min. Results: Time to complete a 5-km treadmill time-trial was likely slower following HT (effect size ± 90% confidence interval = 0.16 ± 0.06), and almost certainly faster following T (–0.34 ± 0.08). Maximal rate of HR increase during 5 min of running at 8 km·h^?1 and rHRI_{8–13km·h^?1} were unchanged following HT and likely increased following T (0.77 ± 0.45 and 0.66 ± 0.62, respectively). A moderate within-individual correlation was found between 5TTT and rHRI_8km·h^?1 (r value ± 90% confidence interval = –.35 ± .32). However, in a subgroup of athletes (n = 7) who were almost certainly slower to complete the 5TTT (4.22 ± 0.88), larger correlations were found between the 5TTT and rHRI_8km·h^?1 (r = –.84 ± .22) and rHRI_{8–13km·h^?1} (r = –.52 ± .41). Steady-state HR during rHRI assessment in this group was very likely greater than in the faster subgroup (≥ 1.34 ± 0.86). Conclusion(s): The 5TTT performance was tracked by both rHRI_8km·h^?1 and rHRI_{8–13km·h^?1}. Correlations between rHRI and performance were stronger in a subgroup of athletes who exhibited a slower 5TTT. Individualized workloads during rHRI assessment may be required to account for varying levels of physical conditioning.     

Sprint profile of professional female soccer players during competitive matches: Female Athletes in Motion (FAiM) study

Abstract

The aim of this study was to determine sprint profiles of professional female soccer players and evaluate how various speed thresholds impact those outcomes. Seventy-one professional players competing in full matches were assessed repeatedly during 12 regular season matches using a Global Positioning System (GPS). Locomotion ≥18 km · h^?1 was defined as sprinting and each event was classified into: Zone 1: 18.0–20.9 km· h^?1; Zone 2: 21.0–22.9 km · h^?1; Zone 3: 23.0–24.9 km · h^?1 and Zone 4: >25 km · h^?1. Outcomes included: duration (s), distance (m), maximum speed (km · h^?1), duration since previous sprint (min) and proportion of total sprint distance. In total 5,019 events were analysed from 139 player-matches. Mean sprint duration, distance, maximum speed and time between sprints were 2.3 ± 1.5 s, 15.1 ± 9.4 m, 21.8 ± 2.3 km· h^?1, and 2.5 ± 2.5 min, respectively. Mean sprint distances were 657 ± 157, 447 ± 185, and 545 ± 217 m for forwards, midfielders and defenders, respectively (P ≤ 0.046). Midfielders had shorter sprint duration (P = 0.023), distance (P ≤ 0.003) and maximum speed (P < 0.001), whereas forwards performed more sprints per match (43 ± 10) than midfielders (31 ± 11) and defenders (36 ± 12) (P ≤ 0.016). Forty-five percent, 29%, 15%, and 11% of sprints occurred in sprint Zones 1, 2, 3 and 4, respectively. This group of professional female soccer players covered 5.3 ± 2.0% of total distance ≥18 km · h^?1 with positional differences and percent decrements distinct from other previously identified elite players. These data should guide the development of high intensity and sprint thresholds for elite-standard female soccer players.     

Prediction of performance by heart rate-derived parameters in recreational runners

We investigated whether heart rate (HR)-derived parameters are accurate performance predictors in endurance recreational runners. One hundred thirty recreational athletes completed an incremental running test (4´running + 1´rest). After each stage, we recorded HR, % of maximum HR (%HRmax), and blood lactate. We also assessed HR after each recovery period, and calculated lactate and HR recovery thresholds and HR deflection point. We tested these parameters for associations with running performance, as measured by peak treadmill speed (PTS) and personal best International Association of Athletics Federations (IAAF) score. The %HRmax at 14.5 km·h^?1 correlated with PTS (r = ?0.92), and IAAF score (rho = ?0.80). The magnitudes of the correlations of lactate-related parameters with PTS (|r| = 0.84 to 0.86) or IAAF score (|rho| = 0.70 to 0.77) in absolute values were slightly lower. The correlations detected between other HR-derived parameters and running performance were weaker (|r or rho| = 0.24 to 0.70). Regression models identified %HRmax at 14.5 km·h^?1 as the strongest predictor of both PTS (β = ?0.72) and IAAF score (β = ?0.72). Consequently, tests based on %HRmax may provide a non-invasive and inexpensive alternate method for predicting the performance of these athletes.     

Assessment of energy expenditure in children using the RT3 accelerometer

Abstract

The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km · h^?1, 0% grade and 6% grade), and one horizontal running speed (8 km · h^?1, 0% grade), on a treadmill. Energy expenditure and oxygen consumption ([Vdot]O₂) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km · h^?1 on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km · h^?1. Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633–0.850, P < 0.01). A child-specific prediction equation (adjusted R ² = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.     

Are gait characteristics and ground reaction forces related to energy cost of running in elite Kenyan runners?

The aim of this study was to determine whether gait cycle characteristics are associated with running economy in elite Kenyan runners. Fifteen elite Kenyan male runners completed two constant-speed running sets on a treadmill (12 km ·h^?1 and 20 km ·h^?1). VO₂ and respiratory exchange ratio values were measured to calculate steady-state oxygen and energy cost of running. Gait cycle characteristics and ground contact forces were measured at each speed. Oxygen cost of running at different velocities was 192.2 ± 14.7 ml· kg^?1· km^?1 at 12 km· h^?1 and 184.8 ± 9.9 ml· kg^?1· km^?1 at 20 km· h^?1, which corresponded to a caloric cost of running of 0.94 ± 0.07 kcal ·kg^?1·km^?1 and 0.93 ± 0.07 kcal· kg^?1· km^?1. We found no significant correlations between oxygen and energy cost of running and biomechanical variables and ground reaction forces at either 12 or 20 km· h^?1. However, ground contact times were ~10.0% shorter (very large effect) than in previously published literature in elite runners at similar speeds, alongside an 8.9% lower oxygen cost (very large effect). These results provide evidence to hypothesise that the short ground contact times may contribute to the exceptional running economy of Kenyan runners.     

Validity and reliability of a novel iPhone app for the measurement of barbell velocity and 1RM on the bench-press exercise

The purpose of this study was to analyse the validity and reliability of a novel iPhone app (named: PowerLift) for the measurement of mean velocity on the bench-press exercise. Additionally, the accuracy of the estimation of the 1-Repetition maximum (1RM) using the load–velocity relationship was tested. To do this, 10 powerlifters (Mean (SD): age = 26.5 ± 6.5 years; bench press 1RM · kg^?1 = 1.34 ± 0.25) completed an incremental test on the bench-press exercise with 5 different loads (75–100% 1RM), while the mean velocity of the barbell was registered using a linear transducer (LT) and Powerlift. Results showed a very high correlation between the LT and the app (r = 0.94, SEE = 0.028 m · s^?1) for the measurement of mean velocity. Bland–Altman plots (R² = 0.011) and intraclass correlation coefficient (ICC = 0.965) revealed a very high agreement between both devices. A systematic bias by which the app registered slightly higher values than the LT (P < 0.05; mean difference (SD) between instruments = 0.008 ± 0.03 m · s^?1). Finally, actual and estimated 1RM using the app were highly correlated (r = 0.98, mean difference (SD) = 5.5 ± 9.6 kg, P < 0.05). The app was found to be highly valid and reliable in comparison with a LT. These findings could have valuable practical applications for strength and conditioning coaches who wish to measure barbell velocity in the bench-press exercise.     

Intensity of exercise recovery,blood lactate disappearance,and subsequent swimming performance

Abstract

The aim of this study was to examine the effects of active versus passive recovery on blood lactate disappearance and subsequent maximal performance in competitive swimmers. Fourteen male swimmers from the University of Virginia swim team (mean age 20.3 years, s = 4.1; stature 1.85 m, s = 2.2; body mass 81.1 kg, s = 5.6) completed a lactate profiling session during which the speed at the lactate threshold (V_LT), the speed at 50% of the lactate threshold (V_LT.5), and the speed at 150% of the lactate threshold (V_LT1.5) were determined. Participants also completed four randomly assigned experimental sessions that consisted of a 200-yard maximal-effort swim followed by 10 min of recovery (passive, V_LT.5, V_LT, V_LT1.5) and a subsequent 200-yard maximal effort swim. All active recovery sessions resulted in greater lactate disappearance than passive recovery (P < 0.0001 for all comparisons), with the greatest lactate disappearance associated with recovery at V_LT (P = 0.006 and 0.007 vs. V_LT.5 and V_LT1.5 respectively) [blood lactate disappearance was 2.1 mmol · l^?1 (s = 2.0), 6.0 mmol · l^?1 (s = 2.6), 8.5 mmol · l^?1 (s = 1.8), and 6.1 mmol · l^?1 (s = 2.5) for passive, V_LT.5, V_LT, and V_LT1.5 respectively]. Active recovery at V_LT and V_LT1.5 resulted in faster performance on time trial 2 than passive recovery (P = 0.005 and 0.03 respectively); however, only active recovery at V_LT resulted in improved performance on time trial 2 (TT₂) relative to time trial 1 (TT₁) [TT₂?TT₁: passive +1.32 s (s = 0.64), V_LT.5+1.01 s (s = 0.53), V_LT?1.67 s (s = 0.26), V_LT1.5?0.07 s (s = 0.51); P < 0.0001 for V_LT). In conclusion, active recovery at the speed associated with the lactate threshold resulted in the greatest lactate disappearance and in improved subsequent performance in all 14 swimmers. Our results suggest that coaches should consider incorporating recovery at the speed at the lactate threshold during competition and perhaps during hard training sessions.     

The use of individualized speed and intensity thresholds for determining the distance run at high-intensity in professional soccer

Abstract

As with other match analysis systems, ProZone® uses an absolute speed threshold to identify running speeds at “high-intensity”. In this study, we examined the use of an individualized high-intensity speed threshold based on the speed at the second ventilatory threshold (VT_2speed) for assessment of the distance run at high-intensity during matches. Ten professional soccer players completed a maximal treadmill test to determine VT_2speed. Match data were identified by means of the ProZone® match analysis system. The distances run at high-intensity during matches were calculated using the default value (19.8 km · h^?1) and VT_2speed. Differences between VT_2speed and the default were analysed using a non-parametric median sign test. The distances run at high-intensity were compared with a paired t-test. The median VT_2speed was 15 km · h^?1 (range 14–16 km · h^?1), which was less than the default (P < 0.01). Mean distance run at high-intensity based on the default and VT_2speed was 845 m (s = 296) and 2258 m (s = 707), respectively [mean difference 1413 m; P < 0.001 (95% CI: 1037–1789 m)]. The high-intensity running speeds based on the second ventilatory threshold are substantially less than that used as the default within the ProZone® match analysis system, thus the distance run at high-intensity can be substantially underestimated.     

Reliability and validity of two tests of soccer skill

Abstract

Twenty-four players from the 1st/2nd (elite) and 24 players from the 3rd/4th (non-elite) university football teams were recruited to evaluate the Loughborough Soccer Passing Test (LSPT) and Loughborough Soccer Shooting Test (LSST) as tools to assess soccer skill. The LSPT requires players to complete 16 passes as quickly as possible. The LSST requires players to pass, control, and shoot the ball to targets on a full-sized goal. Participants completed two main trials each separated by at least one day. During both trials, the participants were given practice efforts before recording the mean of the next two (LSPT) or 10 (LSST) attempts as the performance score. For the LSPT, the mean time taken, added penalty time, and overall performance time were less in the elite players (elite: 43.6 s, s = 3.8; non-elite: 52.5 s, s = 7.4; P = 0.0001). For the LSST, there was no difference in the mean points scored per shot between groups (elite: 1.34, s = 0.46; non-elite: 1.28, s = 0.53). However, the elite players had higher mean shot speed (elite: 80 km · h^?1, s = 4.5; non-elite: 74 km · h^?1, s = 4.2; P < 0.0001) and performed each shot sequence faster (elite: 7.87 s, s = 0.29; non-elite: 8.07 s, s = 0.35; P = 0.037) than the non-elite players. Performance on both tests was more repeatable in elite players. In conclusion, the LSPT and LSST are valid and reliable protocols to assess differences in soccer skill performance.     

Effects of strength,explosive and plyometric training on energy cost of running in ultra-endurance athletes

The aim of the present study was to evaluate the effects of a 12-week home-based strength, explosive and plyometric (SEP) training on the cost of running (Cr) in well-trained ultra-marathoners and to assess the main mechanical parameters affecting changes in Cr. Twenty-five male runners (38.2?±?7.1 years; body mass index: 23.0?±?1.1?kg·m^?2; V˙O₂max: 55.4?±?4.0 mlO₂·kg^?1·min^?1) were divided into an exercise (EG?=?13) and control group (CG?=?12). Before and after a 12-week SEP training, Cr, spring-mass model parameters at four speeds (8, 10, 12, 14?km·h^?1) were calculated and maximal muscle power (MMP) of the lower limbs was measured. In EG, Cr decreased significantly (p?<?.05) at all tested running speeds (?6.4?±?6.5% at 8?km·h^?1; ?3.5?±?5.3% at 10?km·h^?1; ?4.0?±?5.5% at 12?km·h^?1; ?3.2?±?4.5% at 14?km·h^?1), contact time (t_c) increased at 8, 10 and 12?km·h^?1 by mean +4.4?±?0.1% and t_a decreased by ?25.6?±?0.1% at 8?km·h^?1 (p?<?.05). Further, inverse relationships between changes in Cr and MMP at 10 (p?=?.013; r?=??0.67) and 12?km·h^?1 (p?<?.001; r?=??0.86) were shown. Conversely, no differences were detected in the CG in any of the studied parameters. Thus, 12-week SEP training programme lower the Cr in well-trained ultra-marathoners at submaximal speeds. Increased t_c and an inverse relationship between changes in Cr and changes in MMP could be in part explain the decreased Cr. Thus, adding at least three sessions per week of SEP exercises in the normal endurance-training programme may decrease the Cr.     

The physiological cost of velocity coupling during tennis groundstrokes

Abstract

Velocity coupling denotes a perceptual motor behaviour known to occur during coincidence timing tasks. Individuals have been shown to increase their effector limb speed with increases in stimulus speed during interceptive tasks. However, little is known about the physiological effects of velocity coupling. The aim of this study was to determine the physiological cost of velocity coupling during tennis groundstrokes. Eight male and eight female competitive tennis players volunteered to perform three 4-min bouts of continuous groundstrokes against balls projected from a tennis ball machine at speeds of 18, 22, and 27 m · s^?1 (65, 79, and 97 km · h^?1) and a frequency of 14 balls per minute, the order of which was counterbalanced. Breath-by-breath pulmonary gas exchange, heart rate, locomotion time, and limb acceleration were measured throughout each of the 4-min bouts. Capillary blood samples (for blood lactate analysis), rating of perceived exertion, and difficulty rating were taken at the end of each bout. Increasing ball speed did not influence the locomotion time between groundstrokes but did result in a bilateral increase in both the mean upper- and lower-limb acceleration (all P < 0.05). Velocity coupling behaviour increased oxygen uptake, blood lactate concentration, heart rate, rating of perceived exertion, and perceived task difficulty (all P < 0.05). It would appear, therefore, that velocity coupling influenced tennis groundstroke behaviour and indirectly modified the concurrent cardiopulmonary and metabolic responses.     

Phases of match-play in professional Australian Football: Distribution of physical and technical performance

ABSTRACT

The current study aimed to describe the distribution of physical and technical performance during the different phases of play in professional Australian Football. The phases of play (offence, defence, contested play, umpire stoppages, set shots and goal resets) were manually coded from video footage for a single team competing in 18 matches in the Australian Football League. Measures of physical performance including total distance (m), average speed (m · min^?1), low-speed running (LSR, <14.4 km h^?1), high-speed running (HSR, >14.4 km h^?1), accelerations (2.78 m · s^?2) and decelerations (?2.78 m · s^?2) were derived from each phase of play via global positioning system (GPS) devices. Technical skill data including tackles, handballs and kicks were obtained from a commercial statistics provider and derived from each phase of play. Linear mixed-effects models and effect sizes were used to assess and reflect the differences in physical and technical performance between the six phases of play. Activity and recovery cycles, defined as periods where the ball was in or out of play were also described using mean and 95% confidence intervals. The analysis showed that several similarities existed between offence and defence for physical performance metrics. Contested play involved the highest total distance, LSR, accelerations, decelerations and tackles compared to all other phases. Offence and defence involved the highest average speed and HSR running distances. Handballs and kicks were highest during offence, while tackles were highest during contested play, followed by defence. Activity and recovery cycles involved mean durations of ~110 and ~39 s and average speeds of ~160 and ~84 m · min^?1, respectively. The integration of video, GPS and technical skill data can be used to investigate specific phases of Australian Football match-play and subsequently guide match analysis and training design.     

Influence of regression model and incremental test protocol on the relationship between lactate threshold using the maximal-deviation method and performance in female runners

This study examined the influence of the regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and the endurance performance. Sixteen non-competitive, recreational female runners performed a discontinuous incremental treadmill test. The initial speed was set at 7 km · h?1, and increased every 3 min by 1 km · h?1 with a 30-s rest between the stages used for earlobe capillary blood sample collection. Lactate-speed data were fitted by an exponential-plus-constant and a third-order polynomial equation. The lactate threshold was determined for both regression equations, using all the coordinates, excluding the first and excluding the first and second initial points. Mean speed of a 10-km road race was the performance index (3.04 ± 0.22 m · s?1). The exponentially-derived lactate threshold had a higher correlation (0.98 ≤ r ≤ 0.99) and smaller standard error of estimate (SEE) (0.04 ≤ SEE ≤ 0.05 m · s?1) with performance than the polynomially-derived equivalent (0.83 ≤ r ≤ 0.89; 0.10 ≤ SEE ≤ 0.13 m · s?1). The exponential lactate threshold was greater than the polynomial equivalent (P < 0.05). The results suggest that the exponential lactate threshold is a valid performance index that is independent of the initial intensity of the incremental test and better than the polynomial equivalent.     

Kinematic and kinetic analysis of the goalkeeper’s diving save in football

Kinetics and full body kinematics were measured in ten elite goalkeepers diving to save high and low balls at both sides of the goal, aiming to investigate their starting position, linear and angular momentum, and legs' contribution to end-performance. Our results showed that goalkeepers adopted a starting position with a stance width of 33 ± 1% of leg length, knee flexion angle of 62 ± 18° and hip flexion angle of 63 ± 18°. The contralateral leg contributed more than the ipsilateral leg to COM velocity (p < 0.01), both for the horizontal (2.7 ± 0.1 m·s^?1 versus 1.2 ± 0.1 m·s^?1) and for the vertical component (3.1 ± 0.3 m·s^?1 versus 0.4 ± 0.2 m·s^?1). Peak horizontal and peak angular momenta were significantly larger (p < 0.01) for low dives than for high dives with a mean difference of 55 kg·m·s^?1 and 9 kg·m²·s^?1, respectively. In addition, peak vertical momentum was significantly larger (p < 0.01) for high dives with a mean difference between dive heights of 113 kg·m·s^?1. Coaches need to highlight horizontal lateral skills and exercises (e.g. sideward push-off, sideward jumps), with emphasis on pushing-off with the contralateral leg, when training and assessing goalkeeper’s physical performance.     

Parallel assessment of nutrition and activity in athletes: Validation against doubly labelled water, 24-h urea excretion,and indirect calorimetry

Abstract

The assessment of nutrition and activity in athletes requires accurate and precise methods. The aim of this study was to validate a protocol for parallel assessment of diet and exercise against doubly labelled water, 24-h urea excretion, and respiratory gas exchange. The participants were 14 male triathletes under normal training conditions. Energy intake and doubly labelled water were weakly associated with each other (r = 0.69, standard error of estimate [SEE] = 304 kcal · day^?1). Protein intake was strongly correlated with 24-h urea (r = 0.89) but showed considerable individual variation (SEE = 0.34 g · kg^?1 · day^?1). Total energy expenditure based on recorded activities was highly correlated with doubly labelled water (r = 0.95, SEE = 195 kcal · day^?1) but was proportionally biased. During running and cycling, estimated exercise energy expenditure was highly correlated with gas exchange (running: r = 0.89, SEE = 1.6 kcal · min^?1; cycling: r = 0.95, SEE = 1.4 kcal · min^?1). High exercise energy expenditure was slightly underestimated during running. For nutrition data, variations appear too large for precise measurements in individual athletes, which is a common problem of dietary assessment methods. Despite the high correlations of total energy expenditure and exercise energy expenditure with reference methods, a correction for systematic errors is necessary for the valid estimation of energetic requirements in individual athletes.     

Effect of different inter-repetition rest intervals across four load intensities on velocity loss and blood lactate concentration during full squat exercise

ABSTRACT

This study aimed to analyze the acute effect of inter-repetition rest (IRR) intervals on mechanical and metabolic response during four resistance exercise protocols (REPs). Thirty resistance-trained men were randomly assigned to: continuous repetitions (CR), 10 s (IRR10) or 20 s (IRR20) inter-repetition rest. The REPs consisted of 3 sets of 6, 5, 4 and 3 repetitions against 60, 70, 75 and 80% 1RM, respectively, in the full squat exercise. Muscle fatigue was assessed using: percentage of velocity loss over three sets, percentage of velocity loss against the ~1 m·s^?1 load (V1 m·s^?1), and loss of countermovement jump (CMJ) height pre-post exercise. Blood lactate was measured before and after exercise. The percentage of velocity loss over three sets and lactate concentration were significantly lower (P < 0.05) for IRR groups compared to CR in all REPs. The CR group showed a significantly higher (P < 0.05) velocity loss against V1 m·s^?1 load and loss of CMJ height pre-post exercise than IRR groups in REP against 60% 1RM. In conclusion, both IRR groups produced a significant lower degree of fatigue compared to CR group. However, no significant differences were found in any measured variables between IRR configurations.