| 1. |
- Born, Dennis-Peter, et al.
(författare)
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Predicting future stars : Probability and performance corridors for elite swimmers
- 2024
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Ingår i: Journal of Science and Medicine in Sport. - : Elsevier BV. - 1440-2440 .- 1878-1861. ; 27:2, s. 113-118
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesTo evaluate the new age groups of the World Junior Championships in swimming from a scientific perspective, establish benchmarks and performance corridors that predict success at peak performance age and compare performance corridors between men and women and short-, middle-, and long-distance freestyle races.DesignLongitudinal big data analysis.MethodsIn total, 347,186 annual best times of male (n = 3360, 561 ± 177 Swimming Points) and female freestyle swimmers (n = 2570, 553 ± 183 Swimming Points) were collected across all race distances at peak performance age and retrospectively analyzed throughout adolescence. Cumulative Poisson distribution was used to calculate probabilities of becoming world-class finalist, international-class, or national-class swimmer for each age group. Performance corridors were expressed relative to the World Record and compared between performance levels, sex, race distances, and age groups with a 2-way analysis of variance.ResultsFemales are required to swim faster relative to the World Record at a younger age and show earlier performance plateaus than males at national and international levels. Additionally, world-class long-distance finalists show higher Swimming Points earlier in their career compared to short-distance swimmers. This effect is more distinctive in females than males.ConclusionsBased on the sex-specific performance corridors and developments, the newly aligned age groups for the World Junior Championships are questionable regarding long-term athlete development. Based on race times from 131 nations, the present benchmarks provide valid international normative values to predict success chances at peak performance age and guide young swimmers along their talent pathway.AbbreviationsFINA, Fédération Internationale de Natation; 850 swimmers, world-class finalists; 750 swimmers, international-class swimmers; 650 swimmers, national-class swimmers
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| 2. |
- Born, Dennis-Peter, et al.
(författare)
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Specialize Early and Select Late : Performance Trajectories of World-Class Finalists and International- and National-Class Swimmers
- 2024
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Ingår i: International Journal of Sports Physiology and Performance. - : Human Kinetics. - 1555-0265 .- 1555-0273. ; 19:2, s. 164-172
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To investigate performance progression from early-junior to peak performance age and compare variety in race distances and swimming strokes between swimmers of various performance levels. Methods: Using a longitudinal data analysis and between-groups comparisons 306,165 annual best times of male swimmers (N = 3897) were used to establish a ranking based on annual best times at peak performance age. Individual performance trajectories were retrospectively analyzed to compare distance and stroke variety. Performances of world-class finalists and international- and national-class swimmers (swimming points: 886 [30], 793 [28], and 698 [28], respectively) were compared across 5 age groups—13–14, 15–16, 17–18, 19–20, and 21+ years—using a 2-way analysis of variance with repeated measures. Results: World-class finalists are not significantly faster than international-class swimmers up to the 17- to 18-year age group (F2|774 = 65, P < .001, η2p=.14) but specialize in short- or long-distance races at a younger age. World-class breaststroke finalists show faster breaststroke times compared to their performance in other swimming strokes from an early age (P < .05), while world-class freestyle and individual medley finalists show less significant differences to their performance in other swimming strokes. Conclusions: While federation officials should aim for late talent selection, that is, not before the 17- to 18-year age group, coaches should aim to identify swimmers’ preferred race distances early on. However, the required stroke variety seems to be specific for each swimming stroke. Breaststroke swimmers could aim for early and strong specialization, while freestyle and individual medley swimmers could maintain large and very large stroke variety, respectively.
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| 3. |
- Born, Dennis-Peter, et al.
(författare)
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Variation vs. specialization : the dose-time-effect of technical and physiological variety in the development of elite swimmers
- 2024
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Ingår i: BMC Research Notes. - : Springer Nature. - 1756-0500. ; 17:1
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveIt is heavily discussed whether larger variety or specialization benefit elite performance at peak age. Therefore, this study aimed to determine technical (number of different swimming strokes) and physiological (number of different race distances) variety required to become an international-class swimmer (> 750 swimming points) based on 1′522′803 race results.ResultsCorrelation analyses showed lower technical variety in higher ranked swimmers (P < 0.001), yet with small effects (0.11–0.30). However, Poisson distribution revealed dose-time-effects and specified number of swimming strokes required during each age group. Specifically, freestyle swimmers showed highest chances when starting to compete in three to four swimming strokes but reduced their variety to three swimming strokes at the ages of 12/13yrs with another transition to two swimming strokes at the ages of 19/21yrs (female/male swimmers, respectively). Although both sexes showed similar specialization pattern throughout their career, earlier specialization was generally evident in female compared to male swimmers. At peak performance age, freestyle was most frequently combined with butterfly. Swimmers who either kept competing in all five swimming strokes or focused on only one at the beginning of their careers showed lowest probability of becoming an international-class swimmer. Physiological variety increased during junior age but declined again to three race distances towards elite age.
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| 4. |
- Staunton, Craig A., et al.
(författare)
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Diving into a pool of data : Using principal component analysis to optimize performance prediction in women’s short-course swimming
- 2024
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Ingår i: Journal of Sports Sciences. - : Informa UK Limited. - 0264-0414 .- 1466-447X. ; 42:6, s. 519-526
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to optimise performance prediction in short-course swimming through Principal Component Analyses (PCA) and multiple regression. All women’s freestyle races at the European Short-Course Swimming Championships were analysed. Established performance metrics were obtained including start, free-swimming, and turn performance metrics. PCA were conducted to reduce redundant variables, and a multiple linear regression was performed where the criterion was swimming time. A practical tool, the Potential Predictor, was developed from regression equations to facilitate performance prediction. Bland and Altman analyses with 95% limits of agreement (95% LOA) were used to assess agreement between predicted and actual swimming performance. There was a very strong agreement between predicted and actual swimming performance. The mean bias for all race distances was less than 0.1s with wider LOAs for the 800 m (95% LOA −7.6 to + 7.7s) but tighter LOAs for the other races (95% LOAs −0.6 to + 0.6s). Free-Swimming Speed (FSS) and turn performance were identified as Key Performance Indicators (KPIs) in the longer distance races (200 m, 400 m, 800 m). Start performance emerged as a KPI in sprint races (50 m and 100 m). The successful implementation of PCA and multiple regression provides coaches with a valuable tool to uncover individual potential and empowers data-driven decision-making in athlete training.
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| 5. |
- Staunton, Craig A., et al.
(författare)
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Streamlining performance prediction : data-driven KPIs in all swimming strokes
- 2024
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Ingår i: BMC Research Notes. - : Springer Nature. - 1756-0500. ; 17:1
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveThis study aimed to identify Key Performance Indicators (KPIs) for men’s swimming strokes using Principal Component Analysis (PCA) and Multiple Regression Analysis to enhance training strategies and performance optimization. The analyses included all men’s individual 100 m races of the 2019 European Short-Course Swimming Championships.ResultsDuration from 5 m prior to wall contact (In5) emerged as a consistent KPI for all strokes. Free Swimming Speed (FSS) was identified as a KPI for 'continuous' strokes (Breaststroke and Butterfly), while duration from wall contact to 10 m after (Out10) was a crucial KPI for strokes with touch turns (Breaststroke and Butterfly). The regression model accurately predicted swim times, demonstrating strong agreement with actual performance. Bland and Altman analyses revealed negligible mean biases: Backstroke (0% bias, LOAs − 2.3% to + 2.3%), Breaststroke (0% bias, LOAs − 0.9% to + 0.9%), Butterfly (0% bias, LOAs − 1.2% to + 1.2%), and Freestyle (0% bias, LOAs − 3.1% to + 3.1%). This study emphasizes the importance of swift turning and maintaining consistent speed, offering valuable insights for coaches and athletes to optimize training and set performance goals. The regression model and predictor tool provide a data-driven approach to enhance swim training and competition across different strokes.
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| 6. |
- Staunton, Craig A., et al.
(författare)
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The Relationship Between Cardiorespiratory and Accelerometer-Derived Measures in Trail Running and the Influence of Sensor Location
- 2022
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Ingår i: International Journal of Sports Physiology and Performance. - : Human Kinetics. - 1555-0265 .- 1555-0273. ; 17:3, s. 474-483
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To examine the relationship between cardiorespiratory and accelerometer-derived measures of exercise during trailrunning and determine the influence of accelerometer location.Methods: Eight trail runners (7 males and 1 female; age 26 [5] y;maximal oxygen consumption [ ̇VO2] 70 [6] mL·kg−1·min−1) completed a 7-km trail run (elevation gain: 486 m), with concurrentmeasurements of ̇VO2, heart rate, and accelerations recorded from 3 triaxial accelerometers attached at the upper spine, lowerspine, and pelvis. External exercise intensity was quantified from the accelerometers using PlayerLoad™ per minute andaccelerometry-derived average net force. External exercise volume was calculated using accumulated PlayerLoad and the product of average net force and duration (impulse). Internal intensity was calculated using heart rate and ̇VO2-metrics; internal volume was calculated from total energy expenditure (work). All metrics were analyzed during both uphill (UH) and downhill(DH) sections of the trail run.Results: PlayerLoad and average net force were greater during DH compared with UH for all sensorlocations (P ≤ .004). For all accelerometer metrics, there was a sensor position × gradient interaction (F2,1429.003;P <.001). The upper spine was lower compared with both pelvis (P ≤ .003) and lower spine (P ≤ .002) for all accelerometermetrics during both UH and DH running. Relationships between accelerometer and cardiorespiratory measures during UH running ranged from moderate negative to moderate positive (r = −.31 to .41). Relationships were stronger during DH running where there was a nearly perfect correlation between work and impulse (r = .91; P < .001).Conclusions: Simultaneous monitoring of cardiorespiratory and accelerometer-derived measures during trail running is suggested because of the disparity between internal and external intensities during changes in gradient. Sensor positioning close to the center of mass isrecommended.
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| 7. |
- Swarén, Mikael, 1980-, et al.
(författare)
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Using machine learning to analyse player-specific ice skating characteristics to generate game-specific skating drills in professional ice hockey.
- 2021
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Konferensbidrag (refereegranskat)abstract
- The purpose of this study was to develop a method which uses positioning data to analyse player-specific skating characteristics and to investigate the possibility to use machine learning to generate new individual and game-specific training drills. A real-time local positioning system was used to collect positioning data from a professional ice hockey team in the Swedish Hockey League. Positioning data and video were synchronized, and nine different skating characteristics were manually identified and tagged for two forwards. A cost function was developed to generate individual, continuous skating sequences and to create new individual and game-specific skating drills. Skating forward was the most commonly used skating characteristic for both player but the numbers of times the players used the different skating characteristics varied, (H(8)=23.2, p=0.003). The number of skating characteristics between the two players varied, (χ2 (8, N=688) =3 4.0, p<0.001) as well as the time spent within each skating characteristic (p<0.001). The presented method can be used for performance analysis and shows promising results for creating individual and game-specific tests and training drills for ice hockey players, based on individual and game-specific skating characteristics
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