european college of sport science

PP-TT17 Training and Testing 17
Results: Time to complete LM20 was 65.76 ± 6.32 min (average speed: 5.18 ± 0.50 km/h) respectively 77.46 ± 11.36 min (average speed:
4.40 ± 0.65 km/h) for LM30. Significant correlations (p < .05) were found between LM20 time and strength/power (bench press power: r
= -.39, bench row power: r = -.32) and aerobic fitness measurements (Queen’s College Step Test: r = .36, 1.5 mile run: r = .30). Besides
significant correlations existed between LM30 and anthropometric (fat-free mass: r = -.60, body height: r = -.42, leg length: r = -.38, body
fat: r = .38, body weight: r = -.36), strength/power (bench press power: r = -.51, bench row power: r = -.47, sit-ups: r = -.34, back extensions:
r = -.32) and aerobic fitness variables (1.5 mile run: r = .57). Stepwise multiple regression analysis was performed to generate
prediction equations for both loads. The best model for LM20 (adjusted R-square = .22, F = 7.222, p = .002, SEE = 5.64, Beta(bench press
power) = -.351, Beta(Queen’s College Step Test) = .317) was LM20 (min) = 49.913 - [0.043 * bench press power (Watt)] + [0.185 * Queen’s
College Step Test (bpm)]. For LM30 the most accurate estimation (adjusted R-square = .53, F = 25.472, p < .001, SEE = 7.89, Beta(fat-free
mass) = -.491, Beta(1.5 mile run) = .447) revealed the following equation: LM30 (min) = 45.731 - [0.962 * fat-free mass (kg)] + [9.498 * 1.5
mile run (min)].
Conclusion: Results of this study indicate that variables of physical fitness relate to uphill load carriage performance. The influence of
these parameters increased when the carried load was augmented. Moreover, anthropometric parameters became relevant. Models for
each load included an index of aerobic fitness and certain parameters linked to muscle mass. Anyhow the regression equation for the
heavier load caused a higher explained variance. Loaded marching performance seems too complex and inconsistent to be assessed
by unspecific surrogate tests.
INFLUENCE OF GENDER ON PACING ADOPTED BY ELITE TRIATHLETES DURING A COMPETITION
LE MEUR, Y., HAUSSWIRTH, C., BRISSWALTER, J., BERNARD, T.
UNIVERSITY OF TOULON-VAR
Purpose
The aim of the present research was to improve the description of the pacing strategies adopted by female and male elite triathletes
during a World Cup triathlon and to discuss possible factors influencing the self-selection of such strategies.
Methods : Twelve elite triathletes (6 females, 6 males) performed three maximal tests: an all-out 400-m front-crawl to determine their
swimming maximal heart rate (swimming HRmax), an incremental cycling test during which power output (PO), heart rate (HR), at ventilatory
thresholds (VT1, VT2), maximal aerobic power (MAP) were assessed, and an incremental running test to evaluate their maximal
running HRmax. Throughout a World Cup short distance competition, speed and HR were measured. The amount of time spent below
10% of PO (zone 1), between 10% MAP and PO at V1 (zone 2), between PO at VT1 and VT2 (zone 3), between PO at VT2 and MAP (zone 4)
and above MAP (zone 5) was analyzed during the cycling leg.
Results : Swimming and running speeds decreased similarly for both genders (P < 0.05) and HR values were similar through the whole
race (92±2% and 92±3% HRmax for women and men, respectively). The distribution of time spent in the 5 intensity zones during the
cycling leg was the same for both genders (17 ± 5% and 17 ± 3% for zone 1, 36 ± 5% and 31 ± 5% for zone 2, 13 ± 2% and 19 ± 7% for
zone 3, 13 ± 6 and 14 ± 3% for zone 4, 22 ± 2% and 19 ± 2% for zone 5 for women and men, respectively). Men’s speed and PO decreased
after the first bike lap (P < 0.05) and women spent more relative time above MAP in the hilly sections (45±4% vs. 32±4%). Men’s
running speed decreased significantly over all the circuit, whereas women slowed only over uphill and downhill sections (P < 0.05).
Conclusion : The main finding of this study was that both female and male elite triathletes adopted similar positive pacing strategy during
swimming and running legs. On the contrary, men pushed the pace toughly during the swim-to-cycle transition in contrary to women
and female triathletes were more affected by changes in slope during both cycling and running phases. These effects of gender on
pacing may have strong implications for the differentiation of training for female and male elite triathletes.
References
Hausswirth, C., Brisswalter, J. Strategies for improving performance in long duration events: Olympic distance triathlon. Sports Med.
2008;38:881-91.
Vleck VE, Bürgi A, Bentley DJ. The consequences of swim, cycle, and run performance on overall result in elite olympic distance triathlon.
Int J Sports Med. 2006;27:43-8.
Vleck VE, Bentley DJ, Millet GP, Bürgi A. Pacing during an elite Olympic distance triathlon: Comparison between male and female competitors.
J Sci Med Sport. 2007;11:424-32.
NON-FUNCTIONAL OVERREACHING IN YOUNG SWIMMERS OVER AN 8-MONTH COMPETITIVE SEASON
MATOS, N., WILLIAMS, C., WINSLEY, R.
CHILDREN’S HEALTH & EXERCISE RESEARCH CENTRE, SCHOOL OF SPORT AND HEALTH SCIENCES, UNIVERSITY OF EXETER, EXETER, UK
Little is known about the relationship between training load and non-functional overreaching (NFOR) in child swimmers. Due to the multifactorial
nature of NFOR, previous work has recommended a multidisciplinary framework to address this topic (Matos and Winsley, 2007).
The purpose of our study was to follow a group of young swimmers over an 8-month competitive season and assess the relationship
between training load and the occurrence of NFOR, and its association with physiological and psychological measures. Seven nationallevel
swimmers (3 males and 4 females) with a mean age of 15.4±1.0 yr volunteered to participate. Training load was monitored over the
8 month period using the stress index scale (Mujika et al., 1995). Data collection was performed monthly and involved determination of
Immunoglobulin A (IgA) and cortisol (C) levels from a salivary sample, and the completion of the Training Distress Scale (TDS; Raglin and
Morgan, 1994). Incidence of upper respiratory tract infections (URTI) was also recorded. A submaximal 7x200m step test was performed 2
times during the 8-month period with blood lactates, heart rates and rates of perceived exertion collected. Athletes were classified as
NFOR if their competitive performance (main swimming event calculated by the 2004 FINA International Points Score) had stagnated or
decreased over a period of weeks to months (Meuusen et al., 2006). Of the 7 athletes, 2 females (F3 and F4) were classified as NFOR.
Competitive performance had stagnated/ decreased for more than 6 months (F3’s performance stayed the same and F4 had a 6%
decrement, even though they continued to train); all other athletes improved performance (8±9.8 % improvement) during the season. The
NFOR swimmers monthly swim mean volumes (6-month NFOR period) were 31% (F3; 11.4km) and 22% (F4; 31.7km) greater compared to
the non NFOR swimmers (8-month period). There was no evidence of higher mean cortisol in the NFOR swimmers (NFOR period) compared
with the non-NFOR swimmers (8-month period). Absolute IgA and the incidence of URTIs did not show conclusive results on the F3
and F4 swimmers. TDS scores relative to the 6-month NFOR period were 54% (F3; 2.8) and 32% (F4; 1.9) greater than those of the non-
NFOR swimmer (8-month period). The submaximal performance test data displayed no clear association with NFOR. These data indicate
that young swimmers may become NFOR and that high training volumes may be implicated. Furthermore, high TDS scores may be useful
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ANNUAL CONGRESS OF THE EUROPEAN COLLEGE OF SPORT SCIENCE