Mid Sweden University

This study examined physiological recovery between repeated tennis drills in elite adolescent tennis players. Ten tennis players (5 males, 5 females; age 17 ± 2 years) underwent treadmill testing to establish maximal physiological characteristics. Several days later participants completed three standardized on-court tennis drills with fixed rest intervals, during which physiological parameters were monitored. A one-way repeated-measures ANOVA was used to compare physiological responses across the three drills.   utilization stayed above 75% in all drills, peaking during the first drill (p = 0.003). During recovery,   utilization decreased from 58 ± 8% in the first recovery to 50 ± 9% (p = 0.018) and 47 ± 12% (p = 0.022) in the second and third recovery, respectively. The respiratory exchange ratio (RER) stayed below 1.0 during drills, while increasing during recovery periods, (1.07 ± 0.08, 1.00 ± 0.01, 1.04 ± 0.05; p = 0.014). Ventilatory equivalents for oxygen ( ) were stable (p = 0.054), while those for carbon dioxide ( ) increased progressively for each recovery period (29.5 ± 3.6, 31.5 ± 3.8, 32.3 ± 4.3; p < 0.001). Blood lactate concentration differed significantly across recovery periods (p = 0.035) with the lowest value in recovery period two (5.9 ± 2.0, 4.9 ± 1.9 and 5.6 ± 2.0 mmol·l-1). These findings highlight a sustained metabolic demand extending into the recovery phase during standardized tennis drills, characterized by substantial   utilization and elevated respiratory compensation. This suggests a significant anaerobic contribution and underscores the intensity of the physiological load imposed even after exercise cessation.

Purpose

Biathlon is an endurance sport that combines high-intensity cross-country skiing with precision shooting, requiring athletes to carry a rifle while skiing. This study examined the effect of rifle carriage on angular kinematics involving hip and knee range of motion (ROM) in on-snow biathlon skiing.

Methods

29 tier 3 level biathletes (11 F; 18 M) skied two maximal effort time trials (2300 m), once with and once without carrying the biathlon rifle. A 3D motion analysis system, comprising of twelve inertial measurement units, was used to measure hip and knee ROM in the sagittal plane. Multilevel linear models, considering slope, stance (dominant/non-dominant), and side (leading/lagging, left/right), were employed to analyze the effects of rifle carriage on knee and hip ROM in gears 2 and 3.

Results

In gear 2, rifle carriage was associated with reduced knee (p < .001) and hip ROM.

(p < .001). In gear 3, rifle carriage was associated with reduced knee ROM (p < .001) but greater hip ROM (p = .003).

Conclusion

Biathletes change their skiing kinematics when carrying a rifle during on-snow skiing. Rifle carriage was associated with decreased knee and hip ROM in gear 2, and reduced knee but increased hip ROM in gear 3. Future research should determine the relationships between rifle-induced changes to skiing kinematics with performance.

Objectives: To investigate performance development and variety in swimming strokes of female swimmers from early junior to elite age. Methods: A total of 194,788 race times of female 200 m swimmers representing 77 nations were ranked at peak performance age and clustered into world-class finalists (>850 swimming points), international-class (750–850), national-class (650–750) and regional-class swimmers (550–650). Annual best times for each swimming stroke were retrospectively extracted throughout adolescence from 13 years of age. Longitudinal performance development and differences between the swimmers’ main and their secondary swimming strokes were analyzed using linear mixed model. Results: World-class freestyle swimmers show significantly (p ≤ 0.042) higher swimming points across all age categories compared to international-, national- and regional-class swimmers. Linear mixed model analysis indicates a significant performance progression for international- and national-class freestyle swimmers up to the 19–20-year-old category (p ≤ 0.038), but an earlier plateau was observed for regional-class swimmers (p = 0.714). Comparing main and secondary swimming strokes, freestyle swimmers show the highest degree of specialization. For breaststroke and individual medleys, specialization increases with increasing performance level and the closer an athlete is to elite age. World-class butterfly and backstroke finalists show the lowest specializations in terms of the smallest number of significant differences compared to performances in their secondary swimming strokes. Conclusions: Higher ranked swimmers show a greater degree of specialization. As different specialization patterns are evident for the various swimming strokes, decision makers and talent specialists should align development guidelines accordingly and base them on the most advantageous combinations of swimming strokes.

Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots, alongside traditional training metrics, might provide a more detailed understanding of heart rate (HR) intensity patterns, aiding in the evaluation of training quality and compliance.

Methods: Fifteen elite-level youth biathletes from two national academy programmes were monitored over 5–6 weeks using HR monitors. Training sessions were measured via time-in-zone (TIZ) within a five-zone HR model with any time accumulated below the threshold for Zone 1, considered Zone 0. Sessions were dichotomised into those planned as low-intensity training (LIT) or those planned with high-intensity training (HIT). KDE analyses were conducted in MATLAB (Version R2020b) using the “ksdensity” function to create 2D KDE plots that visualise HR intensity accumulation across each programme, session type (e.g., Low-intensity training: LIT; High-intensity training: HIT), and individual athlete responses. Traditional histogram plots and grouped bar charts were also used for comparison.

Results: For LIT sessions, athletes performed less time in Zone 1 than planned, while performed time exceeded planned time in Zone 2. For HIT sessions, performed time in Zone 5 was lower than planned. All sessions contained unplanned time in Zone 0. The 2D KDE plots provided a continuous and detailed representation of HR intensity accumulation throughout training sessions, revealing patterns and intensity fluctuations that complement traditional TIZ analyses.

Conclusions: 2D KDE plots might serve as a valuable complementary tool for assessing TID in biathlon, offering a more nuanced and continuous view of HR intensity. By identifying discrepancies between planned and performed training intensity, coaches can refine strategies and provide individualised feedback. Incorporating KDE plots into training monitoring could improve training alignment, helping reduce overtraining or undertraining risks and optimising athlete development.

This study aimed to investigate how different legs as well as cross-country skiing and shooting performances, associate to final rankings in biathlon relay competitions for both women and men. Data including rank, finish/leg time (LT), course (CT), range (RT) and penalty (PT) times, as well as number of shots (NS) and penalty loops (NPL), were collected from the International Biathlon Union’s database over two seasons, comprising 12 competitions for all teams ranked 1–20. Teams were categorized as G3 (rank 1–3), G10 (rank 4–10) and G20 (rank 11–20). Kruskal-Wallis’ test was used to compare the variables between the groups in total for an entire relay competition, and for each leg. For women, LT was longer for G20 across all four legs due to longer CT, and for G10 during legs 2 and 4 due to longer RT compared to G3 (p < 0.05). For men, LT was longer for G20 during all legs due to longer CT and RT (legs 2–4), and for G10 during legs 3 and 4 due to longer CT compared to G3 (p < 0.05). The present results suggest therefore that the shooting performance for women (especially shorter RT) during legs 2 and 4, and skiing performance for men during legs 3 and 4, are most decisive for final performance during a biathlon relay.

Purpose: This study aimed to differentiate external and internal training loads during on-snow biathlon training by adding an accelerometer-derived metric.

Methods: Eleven adolescent athletes were fitted with a combined heart rate (HR) and accelerometer to be worn during all training sessions. Duration, HR, training impulse (TRIMP), and average net force (AvFNetAvFNet) were used as training variables. All training was divided into either low-intensity training (LIT), or high-intensity training (HIT) based on reported intensity. The training was further categorized as training without any shooting practice (NS) or as a combination of skiing and shooting (COMB). Duration, HR, TRIMP, and AvFNetAvFNet were analyzed in a linear mixed model for the different training modalities.

Results: All training was similar in duration for LIT and HIT sessions (p = .0521) and NS and COMB sessions (p = .988). TRIMP did not differentiate between LIT or HIT training (p = .350) or for NS compared to COMB (p = .298). While AvFNetAvFNet decreased during COMB compared to NS during LIT sessions (p < .001) it remained similar during HIT training (p = 1.00).

Conclusion: The study’s findings indicated that there were no notable differences in internal training load (TRIMP) when comparing various training intensities and modes. However, the type of training had a significant impact on AvFNetAvFNet, especially leading to a decrease during COMB sessions under LIT conditions. Incorporating an external load metric could offer a fresh approach when prescribing and evaluating training, providing deeper insights into the training load.

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.