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Elaine Tor, David L. Pease, and Kevin A. Ball

During the underwater phase of the swimming start drag forces are constantly acting to slow the swimmer down. The current study aimed to quantify total drag force as well as the specific contribution of wave drag during the underwater phase of the swimming start. Swimmers were towed at three different depths (surface, 0.5 m, 1.0 m) and four speeds (1.6, 1.9, 2.0, 2.5 m·s–1), totaling 12 conditions. Wave drag and total drag were measured for each trial. Mixed modeling and plots were then used to determine the relationships between each towing condition and the amount of drag acting on the swimmer. The results of this study show large decreases in total drag as depth increases, regardless of speed (–19.7% at 0.5 m and –23.8% at 1.0 m). This is largely due to the significant reduction in wave drag as the swimmers traveled at greater depth. It is recommended that swimmers travel at least 0.5 m below the surface to avoid excessive drag forces. Swimmers should also perform efficient breakouts when transitioning into free swimming to reduce the duration spent just below the surface where drag values are reported at their highest.

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Elaine Tor, David L. Pease, and Kevin A. Ball

The swimming start is highly influential to overall competition performance. Therefore, it is paramount to develop reliable methods to perform accurate biomechanical analysis of start performance for training and research. The Wetplate Analysis System is a custom-made force plate system developed by the Australian Institute of Sport—Aquatic Testing, Training and Research Unit (AIS ATTRU). This sophisticated system combines both force data and 2D digitization to measure a number of kinetic and kinematic parameter values in an attempt to evaluate start performance. Fourteen elite swimmers performed two maximal effort dives (performance was defined as time from start signal to 15 m) over two separate testing sessions. Intraclass correlation coefficients (ICC) were used to determine each parameter’s reliability. The kinetic parameters all had ICC greater than 0.9 except the time of peak vertical force (0.742). This may have been due to variations in movement initiation after the starting signal between trials. The kinematic and time parameters also had ICC greater than 0.9 apart from for the time of maximum depth (0.719). This parameter was lower due to the swimmers varying their depth between trials. Based on the high ICC scores for all parameters, the Wetplate Analysis System is suitable for biomechanical analysis of swimming starts.

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Kevin A. Ball, Russell J. Best, and Tim V. Wrigley

Research into the relationship between body sway, aim-point fluctuation, and performance in pistol shooting has been inconclusive. The present study reex-amined this relationship on an interindividual basis, as done in previous studies, and via intraindividual analysis, not previously examined. Five elite pistol shooters performed 20 shots similar to competition conditions. For each shot, body-sway parameters and aim-point fluctuation parameters were quantified for the time period 1 s to shot. An AMTI LG6-4 force plate was used to measure body-sway parameters, while a SCATT shooting analysis system was used to measure aim-point fluctuation and shooting performance. Multiple regression analysis indicated that body sway was related to performance for one shooter, aim-point fluctuation was related to performance for three shooters, and body sway was related to aim-point fluctuation for four shooters. These relationships were specific to the individual, with the strength of association and parameters of importance being different for different shooters. However, interindividual analysis indicated that only aim-point fluctuation was related to performance. It was concluded that body sway, aim-point fluctuation, and performance are important in elite level pistol shooting, and performance errors at the elite level are individual-specific. Individual analysis should be a priority when examining elite level sports performance.

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Elaine Tor, David L. Pease, Kevin A. Ball, and Will G. Hopkins

Time trials are commonly used in the lead-up to competition. A method that evaluates the relationship between time trial and competition performance in swimming would be useful for developing performance-enhancement strategies.


To use linear mixed modeling to identify key parameters that can be used to relate time-trial and competition performance.


Ten swimmers participated in the study. Each swimmer was analyzed during 3 time trials and 1 competition. Race video footage was analyzed to determine several key parameters. Pooling of strokes and distances was achieved by modeling changes in parameters between time trials and competition within each subject as linear predictors of percent change in performance using mixed modeling of log-transformed race times.


When parameters were evaluated as the effect of 2 SD on performance time, there were very large effects of start time (2.6%, 90% confidence interval 1.8–3.3%) and average velocity (–2.3%, –2.8% to –1.8%). There was also a small effect for stroke rate (–0.6%, –1.3% to 0.2%). Further analysis revealed an improvement in performance time of 2.4% between time trials and competition, of which 1.8% (large; 1.4–2.1%) was due to a change in average velocity and 0.9% (moderate; 0.6–1.1%) was due to a change in start time; changes in remaining parameters had trivial effects on performance.


This study illustrates effective analytical strategies for identifying key parameters that can be the focus of training to improve performance in small squads of elite swimmers and other athletes.

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Janice O’Connor, Elizabeth J. Ball, Kate S. Steinbeck, Peter S.W. Davies, Connie Wishart, Kevin J. Gaskin, and Louise A. Baur

The aim of this study of 56 children aged 6-9 years was to identify measures of physical activity that could be used in either clinical or population studies. Comparisons were made between four measures of physical activity: a three day parent-reported activity diary, a parent-reported physical activity questionnaire, the Tritrac-R3D™ accelerometer (worn three days) and physical activity energy expenditure calculated over 10 days by the doubly labeled water (DLW) technique. The strongest correlation between methods was for the diary and Tritrac-R3D™ during the two hour after-school period (1530-1730 hours) (r = 0.75, P < 0.0001). Activity level in this after-school period was positively correlated with average activity level over three days for both Tritrac-R3D™ (r = 0.53, P < 0.01) and diary (r = 0.54, P < 0.0001). No associations were found between measures of activity from DLW and activity measures from the Tritrac-R3D™, diary or questionnaire. These results suggest that the two hour after-school period is of high interest for future population studies of physical activity in school-age children.