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Initial Maximum Push-Rim Propulsion and Sprint Performance in Elite Men’s Wheelchair Basketball

Aitor Iturricastillo, Jordi Sanchez-Grau, Gerard Carmona, Adrián García-Fresneda, and Javier Yanci

Objectives: This study sought to report the reliability (intrasession) values of initial maximum push-rim propulsion (IMPRP) and sprint performance in elite wheelchair basketball (WB) players and to assess the involvement of strength in sprint capacity. Methods: Fifteen Spanish international WB male players participated in this study. The maximum single wheelchair push from a stationary position (IMPRP) and the sprint performance (ie, 3, 5, and 12 m) of WB players were measured in this study. Results: IMPRP mechanical outputs V, V max, P, Rel. P, F, and Rel. F variables presented high reliability values (intraclass correlation coefficient [ICC] ≥ .92; coefficient of variation [CV] ≤ 8.04 ± 7.37; standard error of measurement [SEM] ≤ 29.92), but the maximum strength variables Pmax, Rel. Pmax, F max, and Rel. F max (ICC ≥ .63; CV ≤ 13.19 ± 16.63; SEM ≤ 203.76) showed lower ICC values and by contrast higher CV and SEM values. The most substantial correlations were identified between maximum IMPRP values (ie, V, V max, P, Rel. P, F, and Rel. F) and sprint performance in 3 m (r ±  confidence limits ≥ −0.74 ± 0.22, very large; R 2 ≥ .55), 5 m (r ±  confidence limits ≥ −0.72 ± 0.24, very large; R 2 ≥ .51), and 12 m (r ±  confidence limits ≥ −0.67 ± 0.27, large; R 2 ≥ .44). Conclusions: The IMPRP test and sprint tests (3, 5, and 12 m) are practical and reliable for measuring strength and speed in WB players. In addition, there were large to very large associations among strength variables (ie, P, Rel. P, F, and Rel. F) and all sprint variables. This could indicate a need to implement specific strength exercises in WB players to improve sprint capacity.

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

Joel T. Fuller, Dominic Thewlis, Jodie A. Wills, Jonathan D. Buckley, John B. Arnold, Eoin Doyle, Tim L.A. Doyle, and Clint R. Bellenger

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.

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The Effects of Neuromuscular Training on Sand Versus Hard Surfaces on Physical Fitness in Young Male Tennis Players

Jaime Fernandez-Fernandez, Fábio Yuzo Nakamura, Daniel Boullosa, Francisco Javier Santos-Rosa, Alba Herrero-Molleda, Urs Granacher, and David Sanz-Rivas

Purpose: To examine the effects of a neuromuscular training program combining plyometric exercises with acceleration, deceleration, and change-of-direction drills conducted on sand or hard surfaces on the fitness qualities of young male tennis players. Methods: Thirty-one young male players were allocated to a training group performing 12 training sessions on sand or hard surfaces, during a 6-week period. Tests included linear sprint (10-m acceleration with 5-m split times), change of direction (modified 5-0-5 test), vertical jumps (countermovement jump and the 10/5 repeated-jump test), isometric hip abduction and adduction strength, and dynamic balance (Y-balance test). Perceived training loads and muscle soreness were assessed during the intervention. Results: Both training strategies were similarly effective in improving the analyzed fitness components. Group × time interaction effects were noticed, with countermovement jump (P = .032), repeated-jump test (P = .029), and reactive strength index (P = .008) favoring hard surfaces and 5-m sprint (P = .009), dynamic balance (P < .05), adduction strength (P < .05), and abduction strength (P < .001) indices favoring sand. Furthermore, the sand group promoted greater perceived training loads and muscle soreness (P < .05) than the hard group across the intervention period. Conclusion: Neuromuscular training strategies characterized by a relatively low volume (∼35 min), conducted on sand or hard surfaces, promoted similar improvements in the fitness qualities of young tennis players, with selected surface-interaction effects. Training on sand can cause transiently higher training loads and persistently higher muscle soreness, suggesting the need for an adequate familiarization period.

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Effect of Personalized Sodium Replacement on Fluid and Sodium Balance and Thermophysiological Strain During and After Ultraendurance Running in the Heat

Alan J. McCubbin and Ricardo J.S. da Costa

Purpose: To investigate the effect of personalized sweat sodium replacement on drinking behavior, sodium and water balance, and thermophysiological responses during and after ultraendurance running in hot conditions. Methods: Nine participants (7 male, 2 female) completed two 5-hour treadmill runs (60% maximum oxygen uptake, 30°C ambient temperature), in a double-blind randomized crossover design, consuming sodium chloride (SODIUM) capsules to replace 100% of previously assessed losses or placebo (PLACEBO). Fluid was consumed ad libitum. Results: No effect of SODIUM was observed for ad libitum fluid intake or net fluid balance (P > .05). Plasma sodium concentration increased in both trials, but to a greater extent in SODIUM at 2.5 hours (mean [SD]: 4 [4] mmol·L−1 vs 1 [5] mmol·L−1; P < .05) and postexercise (4 [3] mmol·L−1 vs 1 [5] mmol·L−1; P < .05). Plasma volume change was not different between trials (P > .05) but was strongly correlated with sodium balance in SODIUM (r = .880, P < .01). No effect of sodium replacement was observed for heart rate, rectal temperature, thermal comfort, perceived exertion, or physiological strain index. During the 24 hours postexercise, ad libitum fluid intake was greater following SODIUM (2541 [711] mL vs 1998 [727] mL; P = .04), as was urinary sodium excretion (NaCl: 66 [35] mmol, Pl: 21 [12] mmol; P < .01). Conclusions: Personalized sweat sodium replacement during ultraendurance running in hot conditions, with ad libitum fluid intake, exacerbated the rise in plasma sodium concentration compared to no sodium replacement but did not substantially influence overall body-water balance or thermophysiological strain. A large sodium deficit incurred during exercise leads to substantial renal sodium conservation postexercise.

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Performance-Determining Variables of a Simulated Sprint Cross-Country Skiing Competition

Rune Kjøsen Talsnes, Jan-Magnus Brattebø, Tore Berdal, Trine Seeberg, Knut Skovereng, Thomas Losnegard, Jan Kocbach, and Øyvind Sandbakk

Purpose: To investigate performance-determining variables of an on-snow sprint cross-country skiing competition and the evolvement in their relationship with performance as the competition progresses from the individual time trial (TT) to the final. Methods: Sixteen national-level male junior skiers (mean [SD] age, 18.6 [0.8] y; peak oxygen uptake [VO2peak], 67.6 [5.5] mL·min−1·kg−1) performed a simulated sprint competition (1.3 km) in the skating style, comprising a TT followed by 3 finals (quarterfinals, semifinals, and final) completed by all skiers. In addition, submaximal and incremental roller-ski treadmill tests, on-snow maximal speed tests, and strength/power tests were performed. Results: VO2peak and peak treadmill speed during incremental testing and relative heart rate, rating of perceived exertion, blood lactate concentrations, and gross efficiency during submaximal testing were all significantly correlated with performance in the TT and subsequent finals (mean [range] r values: .67 [.53–.86], all P < .05). Relative VO2peak and submaximal relative heart rate and blood lactate concentration were more strongly correlated with performance in the semifinals and final compared with the TT (r values: .74 [.60–.83] vs 0.55 [.51–.60], all P < .05). Maximal speed in uphill and flat terrain was significantly correlated with performance in the TT and subsequent finals (r values: .63 [.38–.70], all P < .05), while strength/power tests did not correlate significantly with sprint performance. Conclusions: VO2peak and high-speed abilities were the most important determinants of sprint cross-country skiing performance, with an increased importance of VO2peak as the competition format progressed toward the final.

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Volume 18 (2023): Issue 11 (Nov 2023)

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Evolution of 1500-m Olympic Running Performance

Carl Foster, Brian Hanley, Renato Barroso, Daniel Boullosa, Arturo Casado, Thomas Haugen, Florentina J. Hettinga, Andrew M. Jones, Andrew Renfree, Philip Skiba, Alan St Clair Gibson, Christian Thiel, and Jos J. de Koning

Purpose: This study determined the evolution of performance and pacing for each winner of the men’s Olympic 1500-m running track final from 1924 to 2020. Methods: Data were obtained from publicly available sources. When official splits were unavailable, times from sources such as YouTube were included and interpolated from video records. Final times, lap splits, and position in the peloton were included. The data are presented relative to 0 to 400 m, 400 to 800 m, 800 to 1200 m, and 1200 to 1500 m. Critical speed and D′ were calculated using athletes’ season’s best times. Results: Performance improved ∼25 seconds from 1924 to 2020, with most improvement (∼19 s) occurring in the first 10 finals. However, only 2 performances were world records, and only one runner won the event twice. Pacing evolved from a fast start–slow middle–fast finish pattern (reverse J-shaped) to a slower start with steady acceleration in the second half (J-shaped). The coefficient of variation for lap speeds ranged from 1.4% to 15.3%, consistent with a highly tactical pacing pattern. With few exceptions, the eventual winners were near the front throughout, although rarely in the leading position. There is evidence of a general increase in both critical speed and D′ that parallels performance. Conclusions: An evolution in the pacing pattern occurred across several “eras” in the history of Olympic 1500-m racing, consistent with better trained athletes and improved technology. There has been a consistent tactical approach of following opponents until the latter stages, and athletes should develop tactical flexibility, related to their critical speed and D′, in planning prerace strategy.

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A Comparison of Critical Speed and Critical Power in Runners Using Stryd Running Power

Cody R. van Rassel, Kate M. Sales, Oluwatimilehin O. Ajayi, Koki Nagai, and Martin J. MacInnis

Purpose: Although running traditionally relies on critical speed (CS) as an indicator of critical intensity, portable inertial measurement units offer a potential solution for estimating running mechanical power to assess critical power (CP) in runners. The purpose of this study was to determine whether CS and CP differ when assessed using the Stryd device, a portable inertial measurement unit, and if 2 running bouts are sufficient to determine CS and CP. Methods: On an outdoor running track, 10 trained runners ( V ˙ O 2 max , 59.0 [4.2] mL·kg−1·min−1) performed 3 running time trials (TT) between 1200 and 4400 m on separate days. CS and CP were derived from 2-parameter hyperbolic speed–time and power–time models, respectively, using 2 (CS2TT and CP2TT) and 3 (CS3TT and CP3TT) TTs. Subsequently, runners performed constant-intensity running for 800 m at their calculated CS3TT and CP3TT. Results: Running at the calculated CS3TT speed (3.88 [0.44] m·s−1) elicited an average Stryd running power (271 [28] W) not different from the calculated CP3TT (270 [28]; P = .940; d = 0.02), with excellent agreement between the 2 values (intraclass correlation coefficient = .980). The CS2TT (3.97 [0.42] m·s−1) was not higher than CS3TT (3.89 [0.44] m·s−1; P = .178; d = 0.46); however, CP2TT (278 [29] W) was greater than CP3TT (P = .041; d = 0.75). Conclusion: The running intensities at CS and CP were similar, supporting the use of running power (Stryd) as a metric of aerobic fitness and exercise prescription, and 2 trials provided a reasonable, albeit higher, estimate of CS and CP.

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Physiological Responses and Swimming-Performance Changes Induced by Altering the Sequence of Training Sets

Ioannis S. Nikitakis, Gregory C. Bogdanis, Giorgos P. Paradisis, and Argyris G. Toubekis

Purpose: Interval-training sets may be applied in a different sequence within a swimming training session. The aim of this study was to investigate the effect of different set sequences on performance and physiological responses in a training session. Methods: Twelve highly trained male swimmers performed 4 sessions in randomized order. Each session included a different combination of 2 training sets: set A–set C, set C–set A, set B–set C, or set C–set B. Set A consisted of 8 × 200 m at speed corresponding to lactate threshold (30-s recovery), set B included 8 × 100 m at maximum aerobic speed (30-s recovery), and set C included 4 × 50-m all-out swimming (2-min recovery). Performance and physiological responses (lactate concentration, pH, base excess, bicarbonate, heart rate, and heart-rate variability) were measured. Results: Performance in each set was similar between sessions irrespective of set sequence. Blood lactate, heart rate, and acid–base responses during set C were similar in all sessions, but blood lactate was higher in sets A and B during C–A and C–B sessions (P = .01). The overall blood lactate and acid–base response was higher in C–A and C–B sessions compared with A–C and B–C sessions, respectively (P = .01). Heart-rate variability in each set, separately as well as the overall session effect, did not differ and was thus independent to the set sequence applied. Conclusions: Training sessions including all-out swimming as a first set increase the magnitude of metabolic responses to the subsequent aerobic-dominated training set.

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Load–Velocity Profile and Active Drag in Young Female Swimmers: An Age-Group Comparison

Christina Wettengl, Rebecca Karlsson, Bjørn H. Olstad, and Tomohiro Gonjo

Purpose: The present study aimed to establish differences in load–velocity profiling, active drag (AD), and drag coefficient (Cd) between 3 age groups of female swimmers. Methods: Thirty-three swimmers (11, 13, or 16 y old) were recruited. The individual load–velocity profile was determined for the 4 competitive swimming strokes. The maximal velocity (V0), maximal load (L0), L0 normalized to the body mass, AD, and Cd were compared between the groups. A 2-way analysis of variance and correlation analysis were conducted. Results: Compared with their younger counterparts, 16-year-old swimmers generally had larger V0, L0, and AD, which was particularly evident when comparing them with 11-year-old swimmers (P ≤ .052). The exception was breaststroke, where no differences were observed in L0 and AD and Cd was smaller in the 16-year-old group than the 11-year-old group (P = .03). There was a negative correlation between Cd and V0 for all groups in backstroke (P ≤ .038) and for the 11-year-old group and 13-year-old group in breaststroke (P ≤ .022) and front crawl (P ≤ .010). For the 16-year-old group, large correlations with V0 were observed for L0, L0 normalized to the body mass, and AD (P ≤ .010) in breaststroke and for L0 and AD with V0 in front crawl (P ≤ .042). In butterfly, large negative correlations with V0 were observed in the 13-year-old group for all parameters (P ≤ .027). Conclusions: Greater propulsive force is likely the factor that differentiates the oldest age group from the younger groups, except for breaststroke, where a lower Cd (implying a better technique) is evident in the oldest group.