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  • Author: Tom J. Vandenbogaerde x
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Sian V. Allen, Tom J. Vandenbogaerde and Will G. Hopkins

Many national sporting organizations recruit talented athletes to well-resourced centralized training squads to improve their performance.

Purpose:

To develop a method to monitor performance progression of swimming squads and to use this method to assess the progression of New Zealand’s centralized elite swimming squad.

Methods:

Best annual long-course competition times of all New Zealand swimmers with at least 3 y of performances in an event between 2002 and 2013 were downloaded from takeyourmarks.com (~281,000 times from ~8500 swimmers). A mixed linear model accounting for event, age, club, year, and elite-squad membership produced estimates of mean annual performance for 175 swim clubs and mean estimates of the deviation of swimmers’ performances from their individual quadratic trajectories after they joined the elite squad. Effects were evaluated using magnitude-based inferences, with a smallest important improvement in swim time of –0.24%.

Results:

Before 2009, effects of elite-squad membership were mostly unclear and trivial to small in magnitude. Thereafter, both sexes showed clear additional performance enhancements, increasing from large in 2009 (males –1.4% ± 0.8%, females –1.5% ± 0.8%; mean ± 90% confidence limits) to extremely large in 2013 (males –6.8% ± 1.7%, females –9.8% ± 2.9%). Some clubs also showed clear performance trends during the 11-y period.

Conclusions:

Our method of quantifying deviations from individual trends in competition performance with a mixed model showed that Swimming New Zealand’s centralization strategy took several years to produce substantial performance effects. The method may also be useful for evaluating performance-enhancement strategies introduced at national or club level in other sports.

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Rita M. Malcata, Tom J. Vandenbogaerde and Will G. Hopkins

There is a need for fair measures of country sport performance that include athletes who do not win medals.

Purpose:

To develop a measure of country performance based on athlete ranks in the sport of swimming.

Methods:

Annual top-150 ranks in Olympic pool-swimming events were downloaded for 1990 through 2011. For each athlete of a given rank, a score representing the athlete’s performance potential was estimated as the proportion of athletes of that rank who ever achieved top rank. A country’s scores were calculated by summing its athletes’ scores over all 32 events. Reliability and convergent validity were assessed via year-to-year correlations and correlations with medal counts at major competitions. The method was also applied to ranks at the 2012 Olympics to evaluate countries’ swimming performance.

Results:

The performance score of an athlete of a given rank was closely approximated by 1/rank. This simpler score has 1 practical interpretation: An athlete ranked 7th (for example) has a chance of 1/7 of ever achieving top rank; for purposes of evaluating country performance, 7 such athletes are equivalent to 1 athlete of the top rank. Country scores obtained by summing 1/rank of the country’s athletes had high reliability and validity. This approach produced scores for 168 countries at the Olympics, whereas only 17 countries won medals.

Conclusions:

The authors used the sport of swimming to develop a fair and inclusive measure representing a country’s performance potential. This measure should be suitable for assessing countries in any sports with world rankings or with athletes at major competitions.

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Sian V. Allen, Tom J. Vandenbogaerde, David B. Pyne and Will G. Hopkins

Talent identification and development typically involve allocation of resources toward athletes selected on the basis of early-career performance.

Purpose:

To compare 4 methods for early-career selection of Australia’s 2012 Olympic-qualifying swimmers.

Methods:

Performance times from 5738 Australian swimmers in individual Olympic events at 101 competitions from 2000 to 2012 were analyzed as percentages of world-record times using 4 methods that retrospectively simulated early selection of swimmers into a talent-development squad. For all methods, squad-selection thresholds were set to include 90% of Olympic qualifiers. One method used each swimmer’s given-year performance for selection, while the others predicted each swimmer’s 2012 performance. The predictive methods were regression and neural-network modeling using given-year performance and age and quadratic trajectories derived using mixed modeling of each swimmer’s annual best career performances up to the given year. All methods were applied to swimmers in 2007 and repeated for each subsequent year through 2011.

Results:

The regression model produced squad sizes of 562, 552, 188, 140, and 93 for the years 2007 through 2011. Corresponding proportions of the squads consisting of Olympic qualifiers were 11%, 11%, 32%, 43%, and 66%. Neural-network modeling produced similar outcomes, but the other methods were less effective. Swimming Australia’s actual squads ranged from 91 to 67 swimmers but included only 50−74% of Olympic qualifiers.

Conclusions:

Large talent-development squads are required to include most eventual Olympic qualifiers. Criteria additional to age and performance are needed to improve early selection of swimmers to talent-development squads.