Diving into a pool of data: Using principal component analysis to optimize performance prediction in women's short-course swimming.

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.

Variation vs. specialization: the dose-time-effect of technical and physiological variety in the development of elite swimmers.

OBJECTIVE: It 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. RESULTS: Correlation 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.

Streamlining performance prediction: data-driven KPIs in all swimming strokes.

OBJECTIVE: This 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. RESULTS: Duration 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.

Specialize Early and Select Late: Performance Trajectories of World-Class Finalists and International- and National-Class Swimmers.

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, ηp2=.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.

Predicting future stars: Probability and performance corridors for elite swimmers.

OBJECTIVES: To 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. DESIGN: Longitudinal big data analysis. METHODS: In total, 347,186 annual best times of male (n = 3360, 561 ±â€¯177 Swimming Points) and female freestyle swimmers (n = 2570, 553 ±â€¯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. RESULTS: Females 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. CONCLUSIONS: Based 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.

Short-course performance variation across all race sections: How 100 and 200†m elite male swimmers progress between rounds.

Introduction: To investigate performance variation in all race sections, i.e., start, clean swimming, and turns, of elite short-course races for all swimming strokes and to determine the effect of performance variation on race results. Methods: Comparing finalists and non-qualified swimmers, a total of 256 races of male swimmers (n = 128, age: 23.3 ± 3.1, FINA points: 876 ± 38) competing in the European short-course swimming championships were analyzed. The coefficient of variation (CV) and relative change in performance (Δ%) were used to compare intra-individual performance progression between rounds and inter-individual differences between performance levels using a linear mixed model. Results: While most performance variables declined during the races (P < 0.005), performance was better maintained in 200 m compared to 100 m races, as well as in finalists compared to non-qualified swimmers. In 100 m races, Start Times improved between heats, semi-finals, and finals (P < 0.005) and contributed to the improved Split Times of Lap 1 in freestyle (P = 0.001, Δ = -1.09%), breaststroke (P < 0.001; Δ = -2.48%), and backstroke (P < 0.001; Δ = -1.72%). Swimmers increased stroke rate from heats/semi-finals to finals in freestyle (P = 0.015, Δ = 3.29%), breaststroke (P = 0.001, Δ = 6.91%), and backstroke (P = 0.005; Δ = 3.65%). Increases in stroke length and clean-swimming speed were only significant between rounds for breaststroke and backstroke (P < 0.005). In 200 m races, Total Time remained unchanged between rounds (P > 0.05), except for breaststroke (P = 0.008; CV = 0.7%; Δ = -0.59%). Start (P = 0.004; Δ = -1.72%) and Split Times (P = 0.009; Δ = -0.61%) only improved in butterfly. From the turn variables, OUT_5 m times improved towards the finals in breaststroke (P = 0.006; Δ = -1.51%) and butterfly (P = 0.016; Δ = -2.19%). No differences were observed for SR and SL, while clean-swimming speed improved between rounds in breaststroke only (P = 0.034; Δ = 0.96%). Discussion: Performance of finalists progressed between rounds in 100 m but not 200 m races, most probably due to the absence of semi-finals. Progression in 100 m races was mainly attributed to improved Start and Split Times in Lap 1, while turn performances remained unchanged. Within round comparison showed higher performance maintenance in 200 m compared to 100 m events, which showed more pronounced positive pacing. Success of finalists was attributed to their overall higher performance level and superior progression between rounds.

Why age categories in youth sport should be eliminated: Insights from performance development of youth female long jumpers.

Long-term sports participation and performance development are major issues in popular sports and talent development programs. This study aimed to provide longitudinal trends in youth female long jump performance development, participation, and relative age effects (RAEs), as longitudinal data for female athletes are missing. 51'894 season's best results of female long jump athletes (n = 16'189) were acquired from the Swiss Athletics online database and analyzed within a range of 6-22 years of age. To examine longitudinal performance development and RAEs, data from athletes who participated in at least three seasons were selected (n = 41'253) and analyzed. Performance development was analyzed using age groups (AGs) and exact chronological age (CA) at competition. Differences between performances of birth quarters were analyzed using 83% confidence intervals (CIs) and smallest worthwhile change. Odds ratios (ORs) with 95% CI were used to quantify RAEs. With the traditional classification into age groups (AG), performances of athletes born between January and March (Q1) were significantly better than those born between October and December (Q4) from U8 to U17. Using exact CA resulted in similar performances in Q1 and Q4 until the U20 age category. The peak of participation was reached in the U12 category, and then decreased until the U23 category with a substantial drop at U17. Significant RAEs were observed from U8 to U19 and at U22. RAEs continuously decreased from U8 (large effect) to U14 (small effect). The present results show that differences in performance arise from the comparison of athletes in AGs. Thus, going beyond AGs and using exact CA, Q4 athletes could benefit from a realistic performance comparison, which promotes fair performance evaluation, un-biased talent development, realistic feedback, and long-term participation.

Key performance indicators and leg positioning for the kick-start in competitive swimmers.

The aim of the study was to (1) assess the test-retest reliability of a novel performance analysis system for swimming (KiSwim) including an instrumented starting block and optical motion capture system, (2) identify key performance indicators (KPI) for the kick-start, (3) determine the most beneficial position of the strong leg and (4) investigate the effect of acute reversal of leg positioning. During three sessions, kick-starts of 15 competitive swimmers were investigated. Eighteen kinematic and kinetic parameters showed high reliability (ICC>0.75) from which principal component analysis identified seven KPI (i.e., time to 15 m, time on-block, depth at 7.5 m, horizontal take-off velocity, horizontal impulse back plate, horizontal peak force back plate and vertical peak force front plate). For the preferred start position, the back plate showed a higher horizontal peak force (0.71 vs. 0.96 x body mass; p < 0.001) and impulse (0.191 vs. 0.28Ns/BW; p < 0.001) compared to front plate. Acute reversal of the leg position reduced performance (i.e., increased time to 15 m and reduced horizontal take-off velocity). However, plate-specific kinetic analysis revealed a larger horizontal peak force (p < 0.001) and impulse (p < 0.001) for the back compared to the front plate in any start position investigated. Therefore, swimmers are encouraged to position the strong leg in the back.

Differences in Race Characteristics between World-Class Individual-Medley and Stroke-Specialist Swimmers.

The purpose of the present study was to investigate differences between world-class individual medley (IM) swimmers and stroke-specialists using race analyses. A total of eighty 200 m races (8 finalists × 2 sexes × 5 events) at the 2021 European long-course swimming championships were analysed. Eight digital video cameras recorded the races, and the video footage was manually analysed to obtain underwater distance, underwater time, and underwater speed, as well as clean-swimming speed, stroke rate, and distance per stroke. Each lap of the IM races was compared with the first, second, third, and fourth laps of butterfly, backstroke, breaststroke, and freestyle races, respectively. Differences between IM swimmers and specialists in each analysed variable were assessed using an independent-sample t-test, and the effects of sex and stroke on the differences were analysed using a two-way analysis of variance with relative values (IM swimmers' score relative to the mean specialists' score) as dependent variables. Breaststroke specialists showed faster clean-swimming speed and longer distance per stroke than IM swimmers for both males (clean-swimming speed: p = 0.011; distance per stroke: p = 0.023) and females (clean-swimming speed: p = 0.003; distance per stroke: p = 0.036). For backstroke and front crawl, specialists exhibited faster underwater speeds than IM swimmers (all p < 0.001). Females showed faster relative speeds during butterfly clean-swimming segments (p < 0.001) and breaststroke underwater segments than males (p = 0.028). IM swimmers should focus especially on breaststroke training, particularly aiming to improve their distance per stroke.

Start Fast, Swim Faster, Turn Fastest: Section Analyses and Normative Data for Individual Medley.

The aims of the study were to provide benchmarks and normative data for 100 m, 200 m, and 400 m short-course individual medley (IM) races, investigate differences between the various swimming strokes and turns involved in IM, and quantify the effect and contribution of various race sections on swimming performance. All IM races (n = 320) at the 2019 European Short-Course Swimming Championships were video monitored and digitized with interrater reliability described by a mean intra-class correlation coefficient of 0.968. Normative data were provided for the eight finalists of each event (FINA points = 886 ± 37) and the eight slowest swimmers from each event (FINA points = 688 ± 53). Contribution and effects of race sections on swimming performance were investigated using stepwise regression analysis based on all races of each event. Regression analysis explained 97-100% of total variance in race time and revealed turn time (ß ≥ 0.53) as distinguishing factor in short-course IM races in addition to swim velocity (ß ≥ -0.28). Start time only affected 100 m (ß ≥ 0.14) and 200 m (ß ≥ 0.04) events. Fastest turn times were found for the butterfly/backstroke turn. Breaststroke showed slowest swim velocities and no difference between fastest and slowest 100 m IM swimmers. Therefore, breaststroke may provide largest potential for future development in IM race times. Correlation analyses revealed that distance per stroke (r ≥ -0.39, P < 0.05) rather than stroke rate (r ≤ -0.18, P > 0.05) is a performance indicator and may be used by coaches and performance analysts to evaluate stroke mechanics in male IM swimmers despite its more complex assessment. Performance analysts, coaches, and swimmers may use the present normative data to establish minimal and maximal requirements for European Championship participation and to create specific drills in practice.

Comparing cross-sectional and longitudinal tracking to establish percentile data and assess performance progression in swimmers.

To provide percentile curves for short-course swimming events, including 5 swimming strokes, 6 race distances, and both sexes, as well as to compare differences in race times between cross-sectional analysis and longitudinal tracking, a total of 31,645,621 race times of male and female swimmers were analyzed. Two percentile datasets were established from individual swimmers' annual best times and a two-way analysis of variance (ANOVA) was used to determine differences between cross-sectional analysis and longitudinal tracking. A software-based percentile calculator was provided to extract the exact percentile for a given race time. Longitudinal tracking reduced the number of annual best times that were included in the percentiles by 98.35% to 262,071 and showed faster mean race times (P < 0.05) compared to the cross-sectional analysis. This difference was found in the lower percentiles (1st to 20th) across all age categories (P < 0.05); however, in the upper percentiles (80th to 99th), longitudinal tracking showed faster race times during early and late junior age only (P < 0.05), after which race times approximated cross-sectional tracking. The percentile calculator provides quick and easy data access to facilitate practical application of percentiles in training or competition. Longitudinal tracking that accounts for drop-out may predict performance progression towards elite age, particularly for high-performance swimmers.

Performance Development of European Swimmers Across the Olympic Cycle.

The aims of the study were to (1) quantify the performance development of race times and key performance indicators of European swimmers across the last Olympic cycle (from 2016 to 2021) and (2) provide reference values for long-course swimming pool events for both sexes from 50 m to 1,500 m including butterfly, backstroke, breaststroke, freestyle, and individual medley. Individual events from the 2016 and 2021 European swimming championships were included. Specifically, 246 men (age: 24.2 ± 3.4 years, FINA points: 890 ± 40) and 256 women races (age: 24.2 ± 4, FINA points: 879 ± 38) of the finalists were recorded and key performance indicators and split times analyzed. Performance differences in finalists of the 2016 and 2021 European championships were determined by an independent t-test and Cohen's d effect size. Reference values were retrieved from 2021 European championship finalists and are provided for all key performance indicators. Race times improved significantly (P < 0.05) or showed moderate (d = 0.5-1) to large effect sizes (d > 1) in 14 (men) and 6 (women) out of 16 events. Improvements were primarily evident in 100 m and 200 m events for males, as well as BR and sprint events for female swimmers. While start times improved in 15 (men) and 14 (women) events, turn times remained inconclusive in both sexes. Generally, breakout distances increased. Clean swimming velocities were faster in 12 (men) and 5 (women) events. In particular, for alternating swimming strokes, i.e., backstroke and freestyle, effect sizes indicated improved swimming efficiency with an inverse relationship between reduced stroke rate and increased distance per stroke. Coaches and performance analysts may use the present reference values as comparative data for race analyses and to specifically prepare swimmers for the various race sections. Data on the performance development should be used to analyze swimmers' potential and set goals for the various events and the next Olympic cycle.

Turn Performance Variation in European Elite Short-Course Swimmers.

Turn performances are important success factors for short-course races, and more consistent turn times may distinguish between higher and lower-ranked swimmers. Therefore, this study aimed to determine coefficients of variation (CV) and performance progressions (∆%) of turn performances. The eight finalists and eight fastest swimmers from the heats that did not qualify for the semi-finals, i.e., from 17th to 24th place, of the 100, 200, 400, and 800 (females only)/1500 m (males only) freestyle events at the 2019 European Short Course Championships were included, resulting in a total of 64 male (finalists: age: 22.3 ± 2.6, FINA points: 914 ± 31 vs. heats: age: 21.5 ± 3.1, FINA points: 838 ± 74.9) and 64 female swimmers (finalists: age: 22.9 ± 4.8, FINA points: 904 ± 24.5 vs. heats: age: 20.1 ± 3.6, FINA points: 800 ± 48). A linear mixed model was used to compare inter- and intra-individual performance variation. Interactions between CVs, ∆%, and mean values were analyzed using a two-way analysis of variance (ANOVA). The results showed impaired turn performances as the races progressed. Finalists showed faster turn section times than the eight fastest non-qualified swimmers from the heats (p < 0.001). Additionally, turn section times were faster for short-, i.e., 100 and 200 m, than middle- and long-distance races, i.e., 400 to 1500 m races (p < 0.001). Regarding variation in turn performance, finalists showed lower CVs and ∆% for all turn section times (0.74% and 1.49%) compared to non-qualified swimmers (0.91% and 1.90%, respectively). Similarly, long-distance events, i.e., 800/1500 m, showed lower mean CVs and higher mean ∆% (0.69% and 1.93%) than short-distance, i.e., 100 m events (0.93% and 1.39%, respectively). Regarding turn sections, the largest CV and ∆% were found 5 m before wall contact (0.70% and 1.45%) with lower CV and more consistent turn section times 5 m after wall contact (0.42% and 0.54%). Non-qualified swimmers should aim to match the superior turn performances and faster times of finalists in all turn sections. Both finalists and non-qualified swimmers should pay particular attention to maintaining high velocities when approaching the wall as the race progresses.

Competition age: does it matter for swimmers?

OBJECTIVE: To establish reference data on required competition age regarding performance levels for both sexes, all swimming strokes, and race distances and to determine the effect of competition age on swimming performance in the context of other common age metrics. In total, 36,687,573 race times of 588,938 swimmers (age 14.2 ± 6.3 years) were analyzed. FINA (Fédération Internationale de Natation) points were calculated to compare race times between swimming strokes and race distances. The sum of all years of race participation determined competition age. RESULTS: Across all events, swimmers reach top-elite level, i.e. > 900 FINA points, after approximately 8 years of competition participation. Multiple-linear regression analysis explained up to 40% of variance in the performance level and competition age showed a stable effect on all race distances for both sexes (ß = 0.19 to 0.33). Increased race distance from 50 to 1500 m, decreased effects of chronological age (ß = 0.48 to - 0.13) and increased relative age effects (ß = 0.02 to 0.11). Reference data from the present study should be used to establish guidelines and set realistic goals for years of competition participation required to reach certain performance levels. Future studies need to analyze effects of transitions between various swimming strokes and race distances on peak performance.

The Relationship Between Cardiorespiratory and Accelerometer-Derived Measures in Trail Running and the Influence of Sensor Location.

PURPOSE: To examine the relationship between cardiorespiratory and accelerometer-derived measures of exercise during trail running and determine the influence of accelerometer location. METHODS: Eight trail runners (7 males and 1 female; age 26 [5] y; maximal oxygen consumption [V˙O2] 70 [6] mL·kg-1·min-1) completed a 7-km trail run (elevation gain: 486 m), with concurrent measurements of V˙O2, heart rate, and accelerations recorded from 3 triaxial accelerometers attached at the upper spine, lower spine, and pelvis. External exercise intensity was quantified from the accelerometers using PlayerLoad™ per minute and accelerometry-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 V˙O2-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 sensor locations (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 accelerometer metrics 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 is recommended.

Normative data and percentile curves for long-term athlete development in swimming.

OBJECTIVES: To provide normative data and establish percentile curves for long-course (50 m pool length) swimming events and to compare progression of race times longitudinally for the various swimming strokes and race distances. DESIGN: Descriptive approach with longitudinal tracking of performance data. METHODS: A total of 2,884,783 race results were collected from which 169,194 annual best times from early junior to elite age were extracted. To account for drop-outs during adolescence, only swimmers still competing at age of peak performance (21-26 years) were included and analyzed retrospectively. Percentiles were established with z-scores around the median and the Lambda-Mu-Sigma (LMS) method applied to account for potential skewness. A two-way analysis of variance (ANOVA) with repeated measure and between-subject factor was applied to compare race times across the various events and age groups. RESULTS: Percentile curves were established based on longitudinal tracking of race times specific to sex, swimming stroke, and race distance. Comparing performance progression, race times of freestyle sprint events showed an early plateau with no further significant improvement (p > 0.05) after late junior age (15-17 years). However, the longer the race distance, the later the race times plateaued (p < 0.05). Female swimmers generally showed an earlier performance plateau than males. Backstroke and freestyle showed an earlier performance plateau compared to the other swimming strokes (p < 0.05). CONCLUSIONS: Performance progression varied between sex, swimming strokes, and race distances. Percentile curves based on longitudinal tracking may allow an objective assessment of swimming performance, help discover individual potentials, and facilitate realistic goal setting for talent development.

Turn Fast and Win: The Importance of Acyclic Phases in Top-Elite Female Swimmers.

The aim of the study was to investigate the effect of start and turn performances on race times in top-elite female swimmers and provide benchmarks for all performance levels, all swimming strokes, and all race distances of the European Short-Course Championships (EC). The individual races (n = 798) of all female competitors (age: 20.6 ± 3.9 years, FINA points: 792 ± 78) were video-monitored for subsequent analysis of start and turn performances. Benchmarks were established across all competitors of each event based on the 10th, 25th, 50th, 75th, and 90th percentiles. Start and turn performances contributed up to 27.43% and 56.37% to total race time, respectively. Mechanistic analysis revealed that the fastest swimmers had the lowest contribution of the acyclic phases to race time. Therefore, relative to their faster race times, these swimmers were even faster during starts and turns. Multiple linear regression analysis showed large effects of turn performance on 50, 100, 200, 400, and 800 m race times (ß = 0.616, 0.813, 0.988, 1.004, and 1.011, respectively), while the effect of start performance continuously decreased the longer the race distance. As turn performance may be the distinguishing factor in modern short-course races, benchmarks should be used to set goals and establish training guidelines depending on the targeted race time.

How Relative Age Effects Associate with Football Players' Market Values: Indicators of Losing Talent and Wasting Money.

BACKGROUND: In football, annual age-group categorization leads to relative age effects (RAEs) in talent development. Given such trends, relative age may also associate with market values. This study analyzed the relationship between RAEs and market values of youth players. METHODS: Age category, birthdate, and market values of 11,738 youth male football players were obtained from the "transfermarkt.de" database, which delivers a good proxy for real market values. RAEs were calculated using odds ratios (OR) with 95% confidence intervals (95%CI). RESULTS: Significant RAEs were found across all age-groups (p < 0.05). The largest RAEs occurred in U18 players (Q1 [relatively older] v Q4 [relatively younger] OR = 3.1) ORs decreased with age category, i.e., U19 (2.7), U20 (2.6), U21 (2.4), U22 (2.2), and U23 (1.8). At U19s, Q1 players were associated with significantly higher market values than Q4 players. However, by U21, U22, and U23 RAEs were inversed, with correspondingly higher market values for Q4 players apparent. While large typical RAEs for all playing positions was observed in younger age categories (U18-U20), inversed RAEs were only evident for defenders (small-medium) and for strikers (medium-large) in U21-U23 (not goalkeepers and midfielders). CONCLUSIONS: Assuming an equal distribution of football talent exists across annual cohorts, results indicate the selection and market value of young professional players is dynamic. Findings suggest a potential biased selection, and undervaluing of Q4 players in younger age groups, as their representation and market value increased over time. By contrast, the changing representations and market values of Q1 players suggest initial overvaluing in performance and monetary terms. Therefore, this inefficient talent selection and the accompanying waste of money should be improved.

How to improve technical and tactical actions of dominant and non-dominant players in children's football?

As young football players develop important technical and tactical skills during competitive matches, this study investigated quantity and quality of technical and tactical actions in real game conditions in a 4v4 compared to the traditional 7v7 match format. In total, three matches of each format were played by 103 young football players (10.3±0.6 years) and video monitored for subsequent manual tagging of technical and tactical events. Based on the number of technical and tactical actions in the 7v7 matches, players were classified as dominant or non-dominant and changes in these subgroups were assessed during the 4v4 match format. The 4v4 match format significantly (P<0.001) increased total number of actions per player per minute compared to the 7v7 matches (5.59±1.44 and 2.78±0.73, respectively) and the number of successful (2.88±0.92 and 1.15±0.49, respectively) and unsuccessful (1.05±0.42 and 0.67±0.23, respectively) actions. Both dominant and non-dominant players increased their number of actions during the 4v4 compared to 7v7 match format. Despite a missing significant interaction effect, there was a larger percentage increase in number of actions for the non-dominant players (143%) compared to dominant players (72%) in 4v4. The 4v4 match format shows twice as many technical and tactical actions in real game conditions and, therefore, may improve players' skill development.

Swimming turn performance: the distinguishing factor in 1500 m world championship freestyle races?

OBJECTIVE: Turn sections represent the second largest part of total race time in 1500 m freestyle races and may substantially affect race results. Therefore, the aim of the study was to investigate individual race strategies and compare the effect of start, swim, and turn performances between short-course and long-course races. Video footages were collected from all 16 male finalists at the 2018 short and 2019 long-course World swimming championships (age 23.06 ± 2.3 years, FINA points 941 ± 42) for subsequently analysis of start, turn, and swim performance. RESULTS: The larger number of turns in short-course races resulted in significantly faster race times (p = 0.004), but slower mean turn times compared to long-course races (p < 0.001). Total race velocity closely correlated with swim and turn but not start section velocity in short- (r ≥ 0.80, p ≤ 0.017) and long-course races (r ≥ 0.83, p ≤ 0.011). Analysis of individual race strategies showed that turn performance affected race results in 6 (75%) and 3 (37.5%) of the 8 world-best 1500 m swimmers in short-course and long-course races, respectively. Medal standing was improved for 1st, 3rd, and 4th ranked short- as well as 1st and 2nd ranked long-course finalist. Coaches, athletes, and performance analysts may carefully consider the importance of turn performance additionally to free-swimming skills.