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Philippe Hellard, Robin Pla, Ferran A. Rodríguez, David Simbana, and David B. Pyne

Purpose: To compare the dynamics of maximal oxygen uptake (V˙O2), blood lactate ([La]b), total energy expenditure (E tot), and contributions of the aerobic (E aer), alactic anaerobic (E an,al), and lactic anaerobic (E an,lac) metabolic energy pathways over 4 consecutive 25-m laps (L0–25, L25–50, etc) of a 100-m maximal freestyle swim. Methods: Elite swimmers comprising 26 juniors (age = 16 [1] y) and 23 seniors (age = 24 [5] y) performed 100 m at maximal speed and then 3 trials (25, 50, and 75 m) at the same pace as that of the 100 m. [La]b was collected, and V˙O2 was measured 20 s postexercise. Results: The estimated energetic contributions for the 100-m trial are presented as mean (SD): E aer, 51% (8%); E an,al, 18% (2%); E an,lac, 31% (9%). V˙O2 increased from L0–25 to L25–50 (mean = 3.5 L·min−1; 90% confidence interval [CI], 3.4–3.7 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.3 L·min−1) and then stabilized in the 2nd 50 m (mean = 4.1 L·min−1; 90% CI, 3.9–4.3 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.4 L·min−1). E tot (juniors, 138 [18] kJ; seniors, 168 [26] kJ), E an,al (juniors, 27 [3] kJ; seniors, 30 [3] kJ), and E an,lac (juniors, 38 [12] kJ; seniors, 62 [24] kJ) were 11–58% higher in seniors. Faster swimmers (n = 26) had higher V˙O2(4.6L·min1, 90% CI 4.4–4.8 L·min−1 vs 3.9 L·min−1, 90% CI 3.6–4.2 L·min−1), and E aer power was associated with fast performances (P < .001). Conclusion: Faster swimmers were characterized by higher V˙O2 and less time to reach the highest V˙O2 at ∼50 m of the 100-m swim. Anaerobic qualities become more important with age.

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Katie E. McGibbon, David B. Pyne, Laine E. Heidenreich, and Robin Pla

Purpose: Pacing, or the distribution of energy expenditure, is particularly important in swimming; however, there is limited research examining pacing profiles in long-distance freestyle events. This study aimed to characterize the pacing profiles of elite male 1500-m freestyle swimmers using a novel method to provide a detailed analysis of different race segments. Methods: The race data for 327 male 1500-m freestyle long-course races between 2010 and 2019 were analyzed retrospectively. The raw 50-m split times for each lap were converted to a percentage of overall race time. The races were classified as a fast-, average-, or slow-start strategy (laps 1–2); as an even, negative, or positive pacing strategy (laps 3–28); and as a fast-, average-, or slow-finish strategy (laps 29–30) to give an overall pacing profile. Results: Slow- and average-start strategies were associated with faster overall 1500-m times than a fast-start strategy (mean = −21.2 s; 90% confidence interval, −11.4 to −32.3 s, P = .00). An even pacing strategy in laps 3 to 28 yielded faster overall 1500-m times than a positive pacing strategy (−8.4 s, −3.9 to −13.0 s, P = .00). The overall 1500-m times did not differ substantially across the finish strategies (P = .99). The start strategy differed across age groups and nationalities, where younger swimmers and swimmers from Australia and Great Britain typically spent a lower percentage of race time in laps 1 to 2 (faster start strategy; −0.10%, −0.01% to −0.23%, P ≤ .02). Conclusion: Adopting a relatively slower start strategy helps conserve energy for the latter stages of a 1500-m freestyle race.