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.

Performance and micro-pacing in sprint cross-country skiing: A comparison of individual time-trial and head-to-head race formats.

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.

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.

Performance and micro-pacing strategies in sit para-biathlon.

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 ± 6%) compared to the Sprint (86 ± 5%) and Middle-distance (86 ± 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 ± 6%) compared to the Sprint (5 ± 4%) and Middle-distance (4 ± 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.

Heart Rate-Blood Lactate Profiling in World-Class Biathletes During Cross-Country Skiing: The Difference Between Laboratory and Field Tests.

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 or HR@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.

A Framework for the Standardization of Game Analysis in Ice Hockey.

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.

Heart Rate Does Not Accurately Predict Metabolic Intensity During Variable-Intensity Roller Skiing or Cycling.

PURPOSE: To critically appraise the utility of heart rate (HR) and power output (PO) to predict metabolic rate (MR) and oxygen consumption (V˙O2) during variable-intensity roller skiing and cycling. METHODS: National-level cyclists (n = 8) and cross-country skiers (n = 9) completed a preliminary session to determine V˙O2max, and a variable-intensity protocol with 3 high-intensity stages at 90% V˙O2max for 3 minutes interspersed with 3 moderate-intensity stages at 70% V˙O2max for 6 minutes. Cardiorespiratory measures were recorded throughout. Linear HR-MR, HR-V˙O2, PO-MR, and PO-V˙O2 regressions were computed from the preliminary session, individually, for all athletes and used to predict MR and V˙O2 from both HR and PO, separately, during the variable-intensity protocol. Mean differences with 95% limits of agreement (LOA) between measured and predicted MR and V˙O2 were calculated. RESULTS: MR and V˙O2 estimated from HR displayed a mean bias close to zero but wide LOA. HR overestimated MR and V˙O2 during moderate intensity but underestimated MR and V˙O2 during high intensity, for both roller skiing and cycling. MR and V˙O2 estimated from PO were more consistent across the experimental trial, displaying a mean bias farther from zero but with tighter LOA. CONCLUSIONS: This study has demonstrated that HR has limited utility to predict metabolic intensity during variable-intensity roller skiing and cycling because of wide LOA. On the other hand, metabolic intensity predicted from PO had tighter LOA, suggesting better consistency. PO might provide a better prediction of metabolic intensity compared with HR, particularly when longer-duration steps are performed during preliminary testing.

Anaerobic work capacity in cycling: the effect of computational method.

PURPOSE: To compare the anaerobic work capacity (AnWC, i.e., attributable anaerobic mechanical work) assessed using four different approaches/models applied to time-trial (TT) cycle-ergometry exercise. METHODS: Fifteen male cyclists completed a 7 × 4-min submaximal protocol and a 3-min all-out TT (TTAO). Linear relationships between power output (PO) and submaximal metabolic rate were constructed to estimate TT-specific gross efficiency (GE) and AnWC, using either a measured resting metabolic rate as a Y-intercept (7 + YLIN) or no measured Y-intercept (7-YLIN). In addition, GE of the last submaximal bout (GELAST) was used to estimate AnWC, and critical power (CP) from TTAO (CP3´AO) was used to estimate mechanical work above CP (W', i.e., "AnWC"). RESULTS: Average PO during TTAO was 5.43 ± 0.30 and CP was 4.48 ± 0.23 W∙kg-1. The TT-associated GE values were ~ 22.0% for both 7 + YLIN and 7-YLIN and ~ 21.1% for GELAST (both P < 0.001). The AnWC were 269 ± 60, 272 ± 55, 299 ± 61, and 196 ± 52 J∙kg-1 for the 7 + YLIN, 7-YLIN, GELAST, and CP3´AO models, respectively (7 + YLIN and 7-YLIN versus GELAST, both P < 0.001; 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO, all P < 0.01). For the three pair-wise comparisons between 7 + YLIN, 7-YLIN, and GELAST, typical errors in AnWC values ranged from 7 to 11 J∙kg-1, whereas 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO revealed typical errors of 55-59 J∙kg-1. CONCLUSION: These findings demonstrate a substantial disagreement in AnWC between CP3´AO and the other models. The 7 + YLIN and 7-YLIN generated 10% lower AnWC values than the GELAST model, whereas 7 + YLIN and 7-YLIN generated similar values of AnWC.

The Effect of Rifle Carriage on the Physiological and Accelerometer Responses During Biathlon Skiing.

Purpose: Investigate the effect of biathlon rifle carriage on physiological and accelerometer-derived responses during biathlon skiing. Methods: Twenty-eight biathletes (11F, 17M) completed two XC skiing time-trials (~2,300 m), once with and once without the biathlon rifle, with concurrent measurements of HR, skiing speed and accelerations recorded from three triaxial accelerometers attached at the Upper-spine, Lower-spine and Pelvis. Exercise intensity was quantified from HR, skiing speed as well from accelerometry-derived PlayerLoad™ per minute (PL·min-1) and average net force (AvFNet). All metrics were analyzed during Uphill, Flat and Downhill sections of the course. Relationships between accelerometry-derived metrics and skiing speed were examined. Results: Time-trials were faster for males compared with females (mean difference: 97 ± 73 s) and No-Rifle compared to With-Rifle (mean difference: 16 ± 9 s). HR was greatest during Downhill (183 ± 5 bpm), followed by Uphill (181 ± 5 bpm) and was lowest in the Flat sections (177 ± 6 bpm, p <0.05). For PL·min-1 and AvFNet there were 3-way Rifle x Gradient x Sensor-Position interactions. Typically, these metrics were greatest during Uphill and Flat sections and were lowest during Downhill sections. Rifle carriage had no impact on the AvFNet at the Lower-Spine or Pelvis. Significant positive linear relationships were identified between skiing speed and accelerometer-derived metrics during Uphill, Flat and Downhill skiing (r = 0.12-0.61, p < 0.05). Conclusions: The accelerometry-derived approach used in this study provides the potential of a novel method of monitoring the external demands during skiing. In particular, AvFNet with sensors located close to the center of mass displayed greatest utility because it followed the expected response of external intensity where responses were greatest during uphill sections, followed by flats and lowest during downhills. In addition, there were significant positive relationships between AvFNet and skiing speed ranging from small to large. Accelerometry-derived measures could provide useful estimates of the external demands in XC skiing and biathlon.

Performance and Micro-Pacing Strategies in a Freestyle Cross-Country Skiing Distance Race.

This study examined the micro-pacing strategies during a distance freestyle cross-country (XC) skiing competition. Nine female and 10 male highly trained XC skiers wore a GNSS device during a FIS-sanctioned race. The course was ~4900 m; women completed two-laps; men completed three-laps. The course was divided into uphill (S1, S3, S5, S7), downhill (S2, S4, S6, S8), and flat (S9) sections for analyses. Statistical parametric mapping was used to determine the course positions (clusters) where total race time or section time was significantly associated with instantaneous skiing speed. Total race time was associated with instantaneous skiing speed during a cluster in S1 on lap 2 for both sexes (t ≥ 5.899, p ≤ 0.008). The two longest uphill sections (S1; S5) and the flat section (S9) contained clusters where section times were related to instantaneous skiing speed for both sexes (p < 0.05). The fastest woman gained 6.9 s on the slowest woman during a cluster in S1 on lap 1 and 7.3 s during a cluster in S9 on lap 1. The fastest man gained 51.7 s on the slowest man over all clusters in S5 over the 3 laps combined. Compared to skiers with longer total race times, skiers with shorter race times skied with faster instantaneous speeds in some clusters of the uphill sections, as well as on the flat section of the course. This study also identified different relative micro-pacing strategies for women and men during freestyle distance XC skiing races. Finally, statistical parametric mapping analyses can help to identify individual strengths and weaknesses for guiding training programs and optimise competition pacing strategies.

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.

Misuse of the term 'load' in sport and exercise science.

Despite the International System of Units (SI), as well as several publications guiding researchers on correct use of terminology, there continues to be widespread misuse of mechanical terms such as 'work' in sport and exercise science. A growing concern is the misuse of the term 'load'. Terms such as 'training load' and 'PlayerLoad' are popular in sport and exercise science vernacular. However, a 'load' is a mechanical variable which, when used appropriately, describes a force and therefore should be accompanied with the SI-derived unit of the newton (N). It is tempting to accept popular terms and nomenclature as scientific. However, scientists are obliged to abide by the SI and must pay close attention to scientific constructs. This communication presents a critical reflection on the use of the term 'load' in sport and exercise science. We present ways in which the use of this term breaches principles of science and provide practical solutions for ongoing use in research and practice.

The influence of playing surface on external demands and physiological responses during a soccer match simulation.

We investigated the effects of playing surfaces with different impact absorption characteristics on external demand and physiological responses. Fifteen participants completed a soccer match simulation on natural grass, synthetic turf and concrete surfaces. Accelerometry-derived PlayerLoadTM per minute (PL·min-1) and average net force (AvFNet) were used to quantify external demands at the centre of mass (CoM), upper-back, mid-back and hip. Heart rate, oxygen uptake, energy expenditure and RPE quantified physiological responses. The concrete surface exhibited the least impact absorption, with peak decelerations ~3.5x synthetic turf and ~10x natural grass (p < 0.001). Despite this, there was no differences in external demand between surfaces (surface: p ≥ 0.194; η2p≤0.092). Both AvFNet and PL·min-1 (location: p < 0.001; η2p≥0.859) were higher at the hip (613(91)N; 12.5(1.2)arb.u), reduced at the mid-back (521(67)N; 8.8(0.7)arb.u) and upper-back (502(60)N; 8.8(0.7)arb.u) when compared to CoM (576(78)N; 10.7(1.0)arb.u). Although playing surface did not influence the external demands, heart rate or oxygen uptake (p > 0.05), energy expenditure was highest on natural grass compared to synthetic turf (P = 0.034) and RPE was highest on synthetic turf compared to concrete (p = 0.026). Different playing surfaces can alter physiological responses to soccer-specific activity even when the external demands are similar.

Criterion Validity of a MARG Sensor to Assess Countermovement Jump Performance in Elite Basketballers.

ABSTRACT: Staunton, CA, Stanger, JJ, Wundersitz, DW, Gordon, BA, Custovic, E, and Kingsley, MI. Criterion validity of a MARG sensor to assess countermovement jump performance in elite basketballers. J Strength Cond Res 35(3): 797-803, 2021-This study assessed the criterion validity of a magnetic, angular rate, and gravity (MARG) sensor to measure countermovement jump (CMJ) performance metrics, including CMJ kinetics before take-off, in elite basketballers. Fifty-four basketballers performed 2 CMJs on a force platform with data simultaneously recorded by a MARG sensor located centrally on the player's back. Vertical accelerations recorded from the MARG sensor were expressed relative to the direction of gravity. Jumps were analyzed by a blinded assessor and the best jump according to the force platform was used for comparison. Pearson correlation coefficients (r) and mean bias with 95% ratio limits of agreement (95% RLOA) were calculated between the MARG sensor and the force platform for jumps performed with correct technique (n = 44). The mean bias for all CMJ metrics was less than 3%. Ninety-five percent RLOA between MARG- and force platform-derived flight time and jump height were 1 ± 7% and 1 ± 15%, respectively. For CMJ performance metrics before takeoff, impulse displayed less random error (95% RLOA: 1 ± 13%) when compared with mean concentric power and time to maximum force displayed (95% RLOA: 0 ± 29% and 1 ± 34%, respectively). Correlations between MARG and force platform were significant for all CMJ metrics and ranged from large for jump height (r = 0.65) to nearly perfect for mean concentric power (r = 0.95). Strong relationships, low mean bias, and low random error between MARG and force platform suggest that MARG sensors can provide a practical and inexpensive tool to measure impulse and flight time-derived CMJ performance metrics.

Haemodynamics of aerobic and resistance blood flow restriction exercise in young and older adults.

PURPOSE: Light-load blood flow restriction exercise (BFRE) may provide a novel training method to limit the effects of age-related muscle atrophy in older adults. Therefore, the purpose of this study was to compare the haemodynamic response to resistance and aerobic BFRE between young adults (YA; n = 11; 22 ± 1 years) and older adults (OA; n = 13; 69 ± 1 years). METHOD: On two occasions, participants completed BFRE or control exercise (CON). One occasion was leg press (LP; 20 % 1-RM) and the other was treadmill walking (TM; 4 km h(-1)). Haemodynamic responses (HR, Q, SV and BP) were recorded during baseline and exercise. RESULT: At baseline, YA and OA were different for some haemodynamic parameters (e.g. BP, SV). The relative responses to BFRE were similar between YA and OA. Blood pressures increased more with BFRE, and also for LP over TM. Q increased similarly for BFRE and CON (in both LP and TM), but with elevated HR and reduced SV (TM only). CONCLUSION: While BFR conferred slightly greater haemodynamic stress than CON, this was lower for walking than leg-press exercise. Given similar response magnitudes between YA and OA, these data support aerobic exercise being a more appropriate BFRE for prescription in older adults that may contribute to limiting the effects of age-related muscle atrophy.