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1.
J Strength Cond Res ; 34(7): 1903-1910, 2020 Jul.
Article in English | MEDLINE | ID: mdl-32271289

ABSTRACT

Breen, D, Powell, C, and Anderson, R. Pacing during 200-m competitive masters swimming. J Strength Cond Res 34(7): 1903-1910, 2020-Pacing strategies are key to overall performance outcome, particularly in swimming given the large resistive properties of water. However, no studies examining how swimming stroke, gender, age, or performance level affect pacing strategies during 200-m races. This study aimed to examine masters athletes pacing strategies categorized by stroke, gender, age, and performance level. Data were retrieved from World and European masters swimming championships and contained data for 4,272 performances. Performances were coded for stroke, gender, age, and performance classification (PC). Performance classification was based on comparison to the appropriate masters world record. Performances were then normalized, with split times being expressed as a percentage faster or slower than average 50-m split time to determine relative pace. Coefficient of variation (CV) of 50-m time was examined across splits. The main effect for stroke was examined at each split, whereas gender, age, and PC were examined for split-1 pace and CV. An alpha level of 0.05 was set to denote statistical significance. A main effect for stroke was identified at each split (all p < 0.001; (Equation is included in full-text article.)-split-1 = 0.292; (Equation is included in full-text article.)-split-2 = 0.040; (Equation is included in full-text article.)-split-3 = 0.058; (Equation is included in full-text article.)-split-4 = 0.162). A main effect for PC was identified for split-1 pace and CV within all strokes (all p < 0.001), except for breaststroke (both p > 0.775). Masters athletes exhibit different pacing patterns across strokes, whereas lower ranked athletes also display less even pacing and a faster relative start compared with higher-ranked athletes. Individual analyses of pacing strategies may be necessary.


Subject(s)
Athletic Performance/physiology , Swimming/physiology , Adult , Age Factors , Aged , Aged, 80 and over , Aging , Athletes , Competitive Behavior , Female , Humans , Male , Middle Aged , Sex Factors
2.
Int J Sports Physiol Perform ; 13(3): 332-338, 2018 Mar 01.
Article in English | MEDLINE | ID: mdl-28714744

ABSTRACT

PURPOSE: Pacing strategies are key to overall performance outcome in distance-running events. Presently, no literature has examined pacing strategies used by masters athletes of all running levels during a competitive marathon. Therefore, this study aimed to examine masters athletes' pacing strategies, categorized by gender, age, and performance level. METHODS: Data were retrieved from the 2015 TSC New York City Marathon for 31,762 masters athletes (20,019 men and 11,743 women). Seven performance-classification (PC) groupings were identified via comparison of overall completion time compared with current world records, appropriate to age and gender. Data were categorized via, age, gender, and performance level. Mean 5-km speed for the initial 40 km was calculated, and the fastest and slowest 5-km-split speeds were identified and expressed as a percentage faster or slower than mean speed. Pace range, calculated as the absolute sum of the fastest and slowest split percentages, was then analyzed. RESULTS: Significant main effects were identified for age, gender, and performance level (P < .001), with performance level the most determining factor. Athletes in PC1 displayed the lowest pace range (14.19% ± 6.66%), and as the performance levels of athletes decreased, pace range increased linearly (PC2-PC7, 17.52% ± 9.14% to 36.42% ± 18.32%). A significant interaction effect was found for gender × performance (P < .001), with women showing a smaller pace range (-3.81%). CONCLUSIONS: High-performing masters athletes use more-controlled pacing strategies than their lower-ranked counterparts during a competitive marathon, independent of age and gender.


Subject(s)
Athletes/classification , Athletic Performance/physiology , Running/physiology , Adult , Age Factors , Aged , Competitive Behavior , Female , Humans , Male , Middle Aged , Sex Factors , Time Factors
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