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Jason C. Tee, Mike I. Lambert and Yoga Coopoo


In team sports, fatigue is manifested by a self-regulated decrease in movement distance and intensity. There is currently limited information on the effect of fatigue on movement patterns in rugby union match play, particularly for players in different position groups (backs vs forwards). This study investigated the effect of different match periods on movement patterns of professional rugby union players.


Global positioning system (GPS) data were collected from 46 professional match participations to determine temporal effects on movement patterns.


Total relative distance (m/min) was decreased in the 2nd half for both forwards (–13%, ±8%, ES = very likely large) and backs (–9%, ±7%, ES = very likely large). A larger reduction in high-intensity-running distance in the 2nd half was observed for forwards (–27%, ±16%, ES = very likely medium) than for backs (–10%, ±15%; ES = unclear). Similar patterns were observed for sprint (>6 m/s) frequency (forwards –29%, ±29%, ES = likely small vs backs –13% ±18%, ES = possibly small) and acceleration (>2.75 m/s2) frequency (forwards –27%, ±24%, ES = likely medium vs backs –5%, ±46%, ES = unclear). Analysis of 1st- and 2nd-half quartiles revealed differing pacing strategies for forwards and backs. Forwards display a “slow-positive” pacing strategy, while the pacing strategy of backs is “flat.”


Forwards suffered progressively greater performance decrements over the course of the match, while backs were able to maintain performance intensity. These findings reflect differing physical demands, notably contact and running loads, of players in different positions.

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Angus M. Hunter, Allan St, Clair Gibson, Malcolm Collins, Mike Lambert and Timothy D. Noakes

This study analyzed the effect of caffeine ingestion on performance during a repeated-measures, 100-km, laboratory cycling time trial that included bouts of 1- and 4-km high intensity epochs (HIE). Eight highly trained cyclists participated in 3 separate trials—placebo ingestion before exercise with a placebo carbohydrate solution and placebo tablets during exercise (Pl), or placebo ingestion before exercise with a 7% carbohydrate drink and placebo tablets during exercise (Cho), or caffeine tablet ingestion before and during exercise with 7% carbohydrate (Caf). Placebo (twice) or 6 mg · kg−1 caffeine was ingested 60 min prior to starting 1 of the 3 cycling trials, during which subjects ingested either additional placebos or a caffeine maintenance dose of 0.33 mg · kg−1 every 15 min to trial completion. The 100-km time trial consisted of five 1-km HIE after 10, 32, 52, 72, and 99 km, as well as four 4-km HIE after 20, 40, 60, and 80 km. Subjects were instructed to complete the time trial and all HIE as fast as possible. Plasma (caffeine) was significantly higher during Caf (0.43 ± 0.56 and 1.11 ± 1.78 mM pre vs. post Pl; and 47.32 ± 12.01 and 72.43 ± 29.08 mM pre vs. post Caf). Average power, HIE time to completion, and 100-km time to completion were not different between trials. Mean heart rates during both the 1-km HIE (184.0 ± 9.8 Caf; 177.0 ± 5.8 Pl; 177.4 ± 8.9 Cho) and 4-km HIE (181.7 ± 5.7 Caf; 174.3 ± 7.2 Pl; 175.6 ± 7.6 Cho; p < .05) was higher in Caf than in the other groups. No significant differences were found between groups for either EMG amplitude (IEMG) or mean power frequency spectrum (MPFS). IEMG activity and performance were not different between groups but were both higher in the 1-km HIE, indicating the absence of peripheral fatigue and the presence of a centrally-regulated pacing strategy that is not altered by caffeine ingestion. Caffeine may be without ergogenic benefit during endurance exercise in which the athlete begins exercise with a defined, predetermined goal measured as speed or distance.

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Dale E. Rae, Andrew N. Bosch, Malcolm Collins and Mike I. Lambert

The aim of this study was to examine the interaction between aging and 10 years of racing in endurance runners. Race-time data from 194 runners who had completed 10 consecutive 56-km ultramarathons were obtained. The runners were either 20.5 ± 0.7, 30.0 ± 1.0, 39.9 ± 0.9, or 49.4 ± 1.0 years old at their first race. Each runner’s race speed was determined for each race over the 10 years. Data were analyzed using repeated-measures ANOVA, one-way ANOVA, and independent t tests and showed that performance improved and declined at greater rates for younger runners; younger runners had a greater capacity for improvement than older runners; ≈4 years were required to reach peak racing speed, regardless of age; it was not possible to compete at peak speed for more than a few years; and the combined effects of 10 years of aging and racing neither improve nor worsen net performance. In conclusion, these data suggest that although these runners showed similar patterns of change in race speed over a 10-year period, the extent of change in performance was greater in younger than in older runners.

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Mike I. Lambert, Lise Bryer, David B. Hampson, Les Nobbs, Andrea M. Rapolthy, M. Sharhidd Taliep and L. Wayne Viljoen

The aim of this study was to measure the change in running performance in a runner from age 27–64 years. During this time the runner had a history of high-volume training and racing. The change in his average running speed over 10-, 21.1-, 42.2-, and 90-km races was compared with the changes in the age-group records for each distance. He trained an average of 4,051 ± 1,762 km/year and ran 16,604 km during races. His training load reached a peak of 7,596 km/year at the age of 33. His rate of decline in running performance was higher than the expected age decline at 47 years for 10-km, 47 years for 21.1-km, 40 years for the 42.2-km, and 48 years for 90-km races. Decreases in performance with increasing age could be explained by reduced training volume, or, alternatively, high volumes of training and racing might accelerate the normal age-related decrements in running performance.