ECSS Paris 2023: OP-AP32
INTRODUCTION: Performance decline over time has been reported in cycling [1] and running [2]. However, whether and how this deterioration is transferred across disciplines (e.g., from cycling to running) in sports such as triathlon remains unknown. Therefore, the aim of this study was to determine the effect of a prolonged cycling protocol on paced and all-out running performance. METHODS: Eleven trained male triathletes (VO₂max 61.7±4.9 ml/kg/min) completed a 45-min paced treadmill run at the first lactate threshold (LT1) speed, followed by a 45-min all-out outdoor run, on two separate occasions. One was performed in fresh (FRE) condition, while the other, referred to as the ‘fatigued’ (FAT) condition, was performed after a cycling bout of 150 min at 90% of the LT1 power. Carbohydrate intake was regulated at 60 g/h. VO₂REL, heart rate (HR) and running economy (RE) were measured during the treadmill running test. Running speed, HR and completed distance were captured during the outdoor session. Changes over time were examined by comparing data from each third of the 45-minute running sessions (T1, T2, and T3). A two-way repeated-measures ANOVA was used to analyze condition, time, and interaction effects, while a Tukey post-hoc test was used when significance was found. A t-test was used to compare overall running speed and completed distance during the outdoor run. Significance was accepted at p<.05. RESULTS: Analyses of paced treadmill running session showed interaction effects for all performance parameters (p<.04), indicating that VO₂REL (4.8–5.8%,p≤.01), HR (1.5–2.2%,p≤.05) were higher and RE (4.8–5.8%,p≤.02) was poorer in the FAT compared to the FRE condition at all time points. In addition, a deterioration of these parameters was seen over time, which occurred earlier in the FAT (T1–T2: 1.5–1.9%,p<.01; T1–T3: 2.9–4.1%,p<.001) than in the FRE condition (T1–T3: 2.1–3.7%,p<.01). Analysis of the outdoor run showed that total covered distance (11.5 vs. 11.0 km,p<.001) and, consequently, overall running speed (15.3 vs. 14.6 km/h,p<.001) were lower in the FAT condition. In line with this, running speed in FAT was slower at all the time intervals (3.4–4.0%,p≤.03), while no change in speed over time was observed (p=0.68). HR was similar between the FRE and FAT during the outdoor run and did not change over time (p>0.05). CONCLUSION: This is the first study to show that prolonged cycling significantly impairs subsequent paced running parameters and self-paced running performance. While differences in all performance parameters were observed between the FAT and FRE conditions, changes over time were observed only during the paced running session. This finding suggests that, during the self-paced session, runners from the start follow an adapted pacing strategy. These findings provide valuable insights for coaches and athletes that may assist in optimizing pacing and training strategies in multidisciplinary sports. REFERENCES: 1. Stevenson J, EJAP 2022:122:2673-82 2. Zanini M, SJMSS 2025:35:e7006
Read CV Andrea FukECSS Paris 2023: OP-AP32
INTRODUCTION: In draft-legal triathlon, the cycling leg is a decisive link between disciplines and conditions running performance. While technical and tactical factors influence power demands, large-scale evidence comparing cycling external loads across sex, formats, and competitive contexts in elite athletes is lacking. This study aimed to characterize cycling power output and distribution across sex and race formats in international-level triathletes. METHODS: Twenty-five international triathletes (8 women/17 men; 18.9 ± 1.6 years old; V̇O2max: 64.0 ± 4.5 and 75.4 ± 5.9 ml/min/kg respectively) were monitored over three consecutive seasons on French, European and World Triathlon circuits. Race data were retained only when a laboratory test from the same season was available, yielding 152 races across Super-Sprint (SS: 10km bike), Sprint (S: 20km), and Short Distance (SD: 40km) formats. The physiological assessment protocol consisted of an incremental step cycling test to determine Lactate threshold (LT) and Lactate Turning Point (LTP) to individualize intensity domains and quantify the cycling external load. Normalized Power (NP) was computed as the fourth root of the mean fourth power of 30-s rolling-averaged power. The NP to mean power ratio was used to define Variability Index (VI). Linear mixed-effects models (random intercept: athlete) tested sex and race format effects on power output and effort distribution, with Holm-corrected pairwise contrasts and Hedges’ g effect sizes. RESULTS: Across 152 races, triathletes produced a mean relative power of 4.02 ± 0.42W/Kg, evolving at a relative pace of 95.9 ± 15.2% of LTP and spending 43.1 ± 11.9% of the race duration above it. Sex had a large effect on relative power output (men: 4.21 ± 0.34 vs women: 3.68 ± 0.34W/kg; p < 0.001, g = 1.65) and relative NP (4.57 ± 0.32 vs 3.96 ± 0.33 W/kg; p < 0.001, g = 1.78) but not on effort distribution (p = 0.205). While no significant effect of race format was found on relative mean power (p = 0.078), a trend was observed for VI (p = 0.054). Moderate to large effects were observed with higher VI values in SD (1.11 ± 0.04) compared to S (1.08 ± 0.04; p = 0.058; g = 0.73) and SS (1.08 ± 0.03; p = 0.058; g = 0.80). CONCLUSION: Elite draft-legal triathlon cycling shows a polarized power zone distribution with ~40% below LT, ~43% above LTP, and relatively little between thresholds (~17%). Men and women show similar descriptive effort profiles, despite a clear gap in relative power output. Sex was a robust predictor of cycling external load, with men producing higher relative power and normalized power than women, consistently across all race formats. Our findings suggest that the SD format displays greater power VI values compared to shorter formats, reflecting repeated high-intensity surges interspersed within a lower average power output.
Read CV Adrian SiblotECSS Paris 2023: OP-AP32
INTRODUCTION: The Giro NextGen is one of the most important international stage races for under‑23 cyclists. The 2025 edition consisted of eight consecutive stages covering a total distance of 1,029.4 km. Therefore, athlete’s ability to effectively balance stress-recovery is essential for maximizing performance (Kellmann et al., 2018). Previous studies have shown that it is particularly critical during multi‑stage cycling competitions (Filho et al., 2013; Lombardi et al., 2013). The current study aimed to assess stress-recovery balance induced by Giro NextGen using REST-Q Sport 36 questionnaire (Kallus & Kellmann, 2016). METHODS: Fourteen male cyclists (20.5 ± 1.1 years; 64.9 ± 4.1 kg; 179.8 ± 4.1 cm; BMI 20.1 ± 1.0 kg/m²), fulfilled the REST-Q 36 Sport questionnaire at the first and the final stage of the race. Changes across time and subscales were examined using a repeated measures MANOVA, followed by univariate paired ANOVAs for each subscale. Additionally, Pearson correlation analyses were conducted to explore associations between REST Q scores, Hooper index scale, and final ranking. RESULTS: The multivariate analysis did not reveal a significant main effect of time, although a trend toward overall change between T0 and T1 emerged (Χ2(1) = 2.95, p = .086). The main effect of the Second-order dimensions (i.e. general stress - GS, sport specific stress - SSS, general recovery - GR, sport specific recovery - SSR) was significant (Χ2(3) = 14.37, p = .002), and the TIME × dimension interaction showed a trend (Χ2(3) = 12.27, p = .007). Univariate analyses showed significant increases in GS (t = 3.75, p = .002, d = 1.00) and SSS (t = 3.51, p = .004, d = 0.94), while both recovery dimensions displayed non‑significant decreasing trend. Among the 12 REST‑Q subscales, significant increase was observed in Fatigue, Emotional Exhaustion, Injury, Disturbed Breaks, and General Stress (p < .05), alongside significant reductions in Being in Shape and Self‑Efficacy (p < .05). Significant correlations indicated that poorer final ranking was associated with greater increases in muscle fatigue (T0-T1 Δmuscle fatigue, r = –.72, p = .029) and reduced readiness (T0-T1 Δmood, r = –.80, p = .009). T0-T1 ΔSport Stress was also strongly correlated to muscle fatigue in T1 (r = .70, p = .012). CONCLUSION: Overall, the results indicate increased perceived stress and fatigue alongside reductions in specific recovery components. Significant associations showed that greater muscle fatigue and reduced readiness are related to poorer final ranking, highlighting the influence of psychophysiological status on competitive outcomes. The combined pattern of subjective and objective indicators suggests a state of underrecovery (Podlog et al. 2023), emphasizing the need for an integrated monitoring in endurance athletes.
Read CV Matteo FerroECSS Paris 2023: OP-AP32