Mid Sweden University

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. 

This study compared performance strategies and sub-technique selection in cross-country skate skiing sprint races, specifically individual time-trial (ITT) and head-to-head (H2H) formats. Fourteen male cross-country skiers from the Chinese national team participated in the FIS-sanctioned sprint race day. GNSS and heart rate sensors recorded positioning, skiing speeds, heart rate, sub-technique usage, and skiing kinematics. Statistical parametric mapping (SPM) was used to determine the course positions (clusters) where instantaneous skiing speed was significantly associated with section time. One-way analyses of variance were used to examine differences between the ITT and H2H. H2H race speeds were 2.4 +/- 0.2% faster than the ITT race (p < 0.05).Variations in sub-technique and skiing kinematics were observed between race formats, indicating different strategies and tactics employed by athletes. SPM identified specific clusters (primarily uphill) where the fastest athlete gained significant time over the slowest. The greatest time gains were associated with higher G3 sub-technique usage and longer G3 cycle length on steep uphill terrain (9-13% gradients). Integrating SPM analyses and sub-technique assessments can help optimise performance and tactics in sprint races. This study enhances our understanding of cross-country skiing dynamics and performance variations among elite competitors.

Purpose To examine the micro-pacing (within-lap) strategies during biathlon skiing with and without the biathlon rifle. Methods Twenty biathletes (7 women, 13 men) performed two crosscountry skiing time-trials on a ≈2300 m course, once with and once without the biathlon rifle. During time-trials, biathletes wore a sensor that recorded position, distance and skiing-speed. A trajectory correction and statistical parametric mapping procedure determined the course positions (clusters) where instantaneous skiing-speed was significantly related to time-trial performance. The time differences between the fastest and slowest skier in these clusters were calculated. Results The fastest biathletes skied with greater instantaneous speeds in specific clusters, which included both uphill and downhill sections. The clusters represented time gains for the fastest skier over the slowest skier of between 16.1 and 25.8 s for the women and between 18.9 and 21.9 s for the men. The largest time gains between the fastest and slowest biathletes were observed in a downhill section that was preceded by a 180° turn, where time gains were between 2.9 and 4.1 s in clusters of between just 12 to 62 m. In biathlon skiing with-rifle, there were more clusters that were not present during without-rifle. When skiing with-rifle, there were additional clusters in the uphill sections that represented time gains of 5.2 s and 2.3 s for the women and men, respectively. Conclusions Statistical parametric mapping can be used in biathlon to provide pacing and performance feedback to athletes and coaches.

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.

Background:

Compared with other major global team sports such as football or basketball, ice hockey has received considerably less attention in sport-science research. However, the research focus on ice hockey performance is growing rapidly. Unfortunately, despite the growing interest in ice hockey, among the little research that has been conducted there are inconsistencies in terminology and methodology in the study of physiology and performance during games. The need for systematic and standardized reporting of study methodology is vital, as a lack of methodological detail or methodological inconsistencies make it impossible to replicate published studies, and alterations in the methodologies used can influence the measured demands imposed on players. Accordingly, this prohibits the ability of coaches to generate game-replicating training programs, decreasing the application of research findings to practice. In addition, a lack of methodological detail or methodological inconsistencies can result in incorrect conclusions being made from research.

Purpose:

In this invited commentary, we aim to increase awareness regarding the current standard of methodological reporting in ice hockey game-analysis research. In addition, we have developed a framework for the standardization of game analysis in ice hockey in order to allow for greater replication in future research and to increase the application of published findings to practice.

Conclusions:

We implore researchers in the field to consult the Ice Hockey Game Analysis Research Methodological Reporting Checklist in order to adopt a detailed reporting standard of methodologies in future work to help improve the applicability of research outcomes.

Aim To identify how riding rein direction (left and right) and rider asymmetry affect tölt performance in Icelandic horses. Methods Two horses were ridden in tölt by four riders on both left and right reins. Riders wore pressure insoles that measured the total absolute force (FAbs) and absolute force difference (FDiff) in their left and right feet in the stirrups. A 3D motion-analysis system recorded the degrees of side-to-side movement in the pelvis (RollP) and in the thoracolumbar region (RollT). Lateral advanced placement (LAP) and duty factor (DF) were calculated to determine tölt performance. One-way ANOVAs were used to assess the effect of rein direction on rider asymmetry variables (FAbs, FDiff, RollP and RollT) and tölt performance (LAP, DF) on a group level (n = 8). Within-subject Spearman rank correlations (ρ) were computed to determine the effect of rider asymmetry variables on tölt performance on an individual level. Results LAP was closer to 25% on the left rein compared to the right rein (mean difference: 1.8 ±1.2%; F(1,7) = 16.333; p = 0.005, η2p = 0.700). In addition, DF was lower on the left rein compared to the right rein (mean difference: 1.9±0.8%; F(1,7) = 41.299; p<0.001, η2p = 0.855). Individual relationships between RollT and LAP ranged from small negative to very large positive and reached significance for one rider (ρ = 0.730; p = 0.040). Individual relationships between RollP and DF ranged from very large negative to very large positive and reached significance for two riders (ρ = 0.731; p = 0.040; ρ = -0.723 p = 0.043). Conclusion Rein direction might influence tölt performance. Individual relationships between rider asymmetry and tölt performance were highly variable and reached significance in some instances, indicating that the relationship between rider asymmetry and tölt performance is highly individual. This type of biomechanical data can be used to provide valuable feedback to guide equestrians and coaches. 

Despite not being recognized by the International System of Units, explosive is a term often applied in sports science and professional practice. While associated with force, strength, power, performance, exercise, movements, contraction, action, and training, readers may be misled to believe that there are further analyses beyond power output, peak force, contractile rate of force development, and impulse. This critical review discusses the misuse of the term explosive in sports science literature, proposes alternatives, and encourages correct definitions of terms, units, and nomenclature to describe exercise performance. The suggestions provided in this review can help to reduce the confusion and perpetuation of an erroneous understanding of mechanical work, energy, and power in sports science.

The current paper discusses the concepts and definitions of external and internal loads in sports science and the quantification of athletes’ performance and psychobiological responses. We provide practical solutions for improving human performance assessment by suggesting related terms and consistent terminology that align with biomechanical standards. This will help to avoid discrepancies in the meaning of terms across various subdisciplines of sport and exercise science and medicine. Where possible, exercise performance should be characterized and quantified according to physical quantities such as time, distance, displacement, speed, velocity, acceleration, force, torque, work, power, and the International System of Units. These quantifications can be performed for exercises, sessions, microcycles, and mesocycles. Standardization of these terms and measurements would enable consistent communication among scientists of all knowledge areas.

Purpose: To identify differences in heart rate (HR) and concentration of blood lactate ([La]) relationships between laboratory and field-based skate-roller-skiing tests.

Methods: Fourteen world-class biathletes (8 women, 6 men) completed a laboratory- and field-based roller-skiing test using the skate technique. The laboratory-based test comprised 5 to 7 submaximal steps at a fixed incline and speed on a roller-skiing treadmill. The field-based test comprised 5 steps on a course where the final hill was designed to mimic the conditions of the laboratory test. HR and [La] were measured for each step. The HR associated with 2 mmol·L−1(HR@2 mmol) and 4 mmol·L−1 (HR@4 mmol) of [La] was calculated using an interpolation method. A 1-way analysis of variance and Bland–Altman analyses with 95% limits of agreement (LoA) were used to determine if test type influenced HR@2 mmol orHR@4 mmol. A second-order polynomial was fitted to group-level data to highlight the HR–[La] relationships for laboratory- and field-based tests.

Results: HR@2 mmol was lower for field tests than for laboratory tests (mean bias: 1.9%HRmax; 95% LoA: −4.5 to+8.3%HRmax; P < .001). HR@4 mmol was also lower for field tests compared to laboratory tests (mean bias: 2.4%HRmax; 95%LoA: −1.2 to +6.0%HRmax; P < .001). On the group level, the lactate threshold occurred at a lower HR during roller skiing in the field compared to the laboratory.

Conclusions: The findings from this study confirm that for a given HR, [La] was greater in field compared with laboratory-based conditions. These results might have implications for how coaches define training-intensity“zones” during skate roller skiing based on laboratory tests.

This study investigated micro-pacing strategies during sit para-biathlon. Six elite sit para-biathletes wore a positioning system device during the world-championships in three different competition formats (Sprint, Middle-distance, and Long-distance). Total Skiing Time (TST), penalty-time, shooting-time, and Total Race Time (TRT) were analysed. One-way analyses of variance were used to compare the relative contributions of TST, penalty-time, and shooting-time to TRT across the three race formats. Statistical parametric mapping (SPM) was used to determine the course positions (clusters) where instantaneous skiing speed was significantly associated with TST. The contribution of TST to TRT was lower for the Long-distance (80 & PLUSMN; 6%) compared to the Sprint (86 & PLUSMN; 5%) and Middle-distance (86 & PLUSMN; 3%) races, however this difference was not statistically significant (p > 0.05). The proportional contribution of penalty-time to TRT was significantly greater (p < 0.05) for the Long-distance (13 & PLUSMN; 6%) compared to the Sprint (5 & PLUSMN; 4%) and Middle-distance (4 & PLUSMN; 3%) races. Statistical parametric mapping (SPM) revealed specific clusters where instantaneous skiing speed was significantly associated with TST. For example, over all laps during the Long-distance race, the fastest athlete gained 6.5 s over the slowest athlete in the section with the steepest uphill. Overall, these findings can provide insights into pacing strategies and help para-biathlon coaches and athletes optimise training programmes to improve performance.