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.

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.

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.

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.

New insights from Norwegian and Swedish sports coaches' employment, practices, and beliefs during the first COVID-19 restriction period.

Introduction: This study (i) examined Norwegian and Swedish sports coaches' employment, practices, and beliefs during the first wave of the COVID-19 pandemic, (ii) compared these aspects between coaches in Norway and Sweden, two countries with clearly different movement restrictions strategies in this period. Methods: An online survey was distributed to coaches via email and social media. The survey was open between June and August 2020. In total, 348 coaches responded, 141 from Norway, and 207 from Sweden. Results: Among responders, 2% had lost their job due to the pandemic, 17% had been furloughed, 28% worked from home office, and 39% worked as usual. Norwegian coaches were more likely to work from home (48% vs. 15%, p < .001), while Swedish coaches were more likely to work as usual (60% vs. 9%, p < .001). Coaches in both countries communicated less frequently with their athletes (p < .001) and had less in-person communication (p < .001) compared to pre-Covid levels. Larger declines existed among Norwegian coaches regarding communication frequency (p < .001) and in-person communication (p < .001). Video calls and phone calls usage increased (p < .001 and p = .009 respectively). We recorded low levels of concern among coaches about the effects of the pandemic on their relationship with their athletes. There were considerable levels of concern about athletes' maintaining their motivation to train (Norway: 43.3%, Sweden: 50.7%), and low levels of concern about the coaches' relationships with their athletes (Norway: 14.1%, Sweden: 17.8%). Discussion: Overall, this study showed the imposed movement restrictions had several negative consequences for the employment and work practices of sports coaches in Norway and Sweden. However, it also highlighted that coaches were able to adapt their work practices to the constraints and were able to maintain relationships with their athletes. The consequences raised in this paper can act as a guide during possible future lockdowns.

School's out for summer-Differences in training characteristics between adolescent biathletes of different performance levels.

The purpose of this study was to retrospectively describe the longitudinal changes of training variables in adolescent biathletes based on performance level. Thirty biathletes (15 men and 15 women) were included in the study and categorized as either national level biathletes (NLB, n = 21) or national team biathletes (NTB, n = 9). Retrospective training data was collected from training diary covering the biathletes' four years (Y1-Y4) as student-athletes at upper secondary school. Training data was divided into physical and shooting training variables. A linear mixed-effect model was used for comparing the difference of the performance group and year of upper secondary school on training characteristics. The NTB group achieved a greater annual training volume than the NLB group, especially during Y4 (594±71 h·y-1 vs 461±127 h·y-1, p < 0.001), through an increase in duration of each session and by completing more weekly training volume during the general phase (13.7±4.6 vs 10.0±4.9 h·w-1, p = 0.004). No difference was observed in relative training intensity distribution between the groups. The total number of shots fired was also greater for the NTB (9971±4716 vs 7355±2812 shots·y-1, p = 0.003). There was an equal frequency in illness and injury for both the NLB and NTB. Accordingly, the results of the present study describe longitudinal changes of biathlon training in adolescent biathletes that also may affect performance development.

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.

How Does the Starting Order in the First and Second Run Affect the Final Rank in the FIS World Cup Giant Slalom?

The aim of this study was to determine the impact of runs 1 and 2 on overall rank in Giant Slalom. Data from 15 seasons (2005/2006-2019/2020) including and unique starts for women (n = 2,294) and men (n = 2,328) were analyzed. Skiers were grouped based on final ranks 1-3 (G3), 4-10 (G10), and 11-20 (G20) and separately analyzed for women and men. A Wilcoxon-signed rank test was used for comparisons between runs 1 and 2, while a multi-nominal logistic regression was used to identify odds ratios (OR) associated with group rank. Women had similar run times for runs 1 and 2 (p = 0.734), while men had faster times on run 2 (p < 0.001). The strongest association to G3 was during run 1 for run time (men: OR 1.06-1.12; women: OR 1.06-1.11, all p < 0.01) and gate-to-gate times (men: OR 33-475; women: OR 81-2,301, all p < 0.001). Overall, this study demonstrates the importance of a fast first run for improving the final ranking group and the need to increase the tempo going from the first to the second run for men.

The Determinants of Performance in Biathlon World Cup Sprint and Individual Competitions.

Purpose: The present study aimed to determine the association of skiing speed (SS), range time (RT), and the number of missed targets (MT) with rank in sprint and individual biathlon competitions. Methods: Data were collected from the International Biathlon Union's database for 17 seasons (2002/2003-2018/2019). Furthermore, the biathletes were divided into three rank groups (G3, rank 1-3; G10, rank 4-10; and G20, rank 11-20). Multinominal regression was used to detect odds ratios associated with group rank for both sexes, separately. Results: MT was the only variable that was constantly related to G3 (OR 1.90-6.35, all p < 0.001) for both women and men. SS was associated with G3 in the last lap in the sprint for both sexes (OR 0.46-0.66, all p < 0.001) and RT for standing shooting (OR 1.04-1.14, all p < 0.05). Conclusion: These results show that shooting is the fundamental factor for performance in both competitions, but that SS is increasingly important for the last lap in the sprint for both sexes. Further, a fast RT in the standing shooting for women in individual and men in the sprint seems important for improving final rank.

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.

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.

The balancing act between skiing and shooting - the determinants of success in biathlon pursuit and mass start events.

This study aimed to investigate how skiing speed (SS), number of missed targets (MT) and range time (RT) were associated with final rank in biathlon pursuit and mass start competitions. Data were collected from the International Biathlon Union's database over 17 seasons. Biathletes were categorised into three groups (rank 1-3, G3; rank 4-10, G10; rank 11-20, G20).  Multinomial regression was used to identify odds ratios associated with group rank in both sexes. The only variable found to be consistently related to G3 in both pursuit and mass start was MT (men OR 1.206-1.729 and women OR 1.340-3.124, all p < 0.01). SS during lap four of pursuit and mass start was most strongly related to G3 for both sexes (men OR 0.231-0.094 and women OR 0.339-0.126, all p < 0.001). RT during shooting four in pursuit was most strongly related to G3 compared to G10 and G20 (men OR 1.067; 95% CI, 1.030-1.105 and women OR 1.076; 95% CI, 1.020-1.134, all p < 0.001, respectively). Accordingly, MT was most strongly related to final rank in both sexes, while SS during lap four and last RT was also significant.

Rifle carriage affects gear distribution during on-snow skiing in female and male biathletes.

The aim was to investigate whether rifle carriage affects gear distribution during on-snow skiing in highly-trained biathletes, and whether there were any associated sex differences. Twenty-eight biathletes (11 women, 17 men) skied a 2230-m lap at competition speed twice, one lap with the rifle (WR) and the other lap without the rifle (NR). The biathletes wore a portable 3D-motion analysis system while skiing, which enabled characterisation of distance and time in different gears. Skiing WR increased lap time compared to NR (412 (90) vs. 395 (91) s, p < 0.001). The biathletes used gear 2 to a greater extent WR compared to NR (distance: 413 ± 139 vs. 365 ± 142 m; time: 133 (95) vs. 113 (86) s; both p < 0.001) and gear 3 less (distance: 713 ± 166 vs. 769 ± 182 m, p < 0.001; time: 141 ± 33 vs. 149 ± 37 s, p = 0.008), with similar patterns for women and men. Differences between WR and NR in the use of gears 3 and 2 were more extensive for moderate compared to steeper uphill terrain. Rifle carriage increased the use of gear 2, which was negatively associated with performance. Therefore, preparing biathletes to be able to cover more distance in gear 3 WR, especially in moderate uphill terrain, may improve biathlon skiing performance.

Anaerobic Capacity in Running: The Effect of Computational Method.

INTRODUCTION: To date, no study has compared anaerobic capacity (AnC) estimates computed with the maximal accumulated oxygen deficit (MAOD) method and the gross energy cost (GEC) method applied to treadmill running exercise. PURPOSE: Four different models for estimating anaerobic energy supply during treadmill running exercise were compared. METHODS: Fifteen endurance-trained recreational athletes performed, after a 10-min warm-up, five 4-min stages at ∼55-80% of peak oxygen uptake, and a 4-min time trial (TT). Two linear speed-metabolic rate (MR) regression models were used to estimate the instantaneous required MR during the TT (MR TT_req ), either including (5+Y LIN ) or excluding (5-Y LIN ) a measured Y-intercept. Also, the average GEC (GEC AVG ) based on all five submaximal stages, or the GEC based on the last submaximal stage (GEC LAST ), were used as models to estimate the instantaneous MR TT_req . The AnC was computed as the difference between the MR TT_req and the aerobic MR integrated over time. RESULTS: The GEC remained constant at ∼4.39 ± 0.29 J⋅kg-1⋅m-1 across the five submaximal stages and the TT was performed at a speed of 4.7 ± 0.4 m⋅s-1. Compared with the 5-Y LIN , GEC AVG , and GEC LAST models, the 5+Y LIN model generated a MR TT_req that was ∼3.9% lower, with corresponding anaerobic capacities from the four models of 0.72 ± 0.20, 0.74 ± 0.16, 0.74 ± 0.15, and 0.54 ± 0.14 kJ⋅kg-1, respectively (F 1.07,42 = 13.9, P = 0.002). The GEC values associated with the TT were 4.22 ± 0.27 and 4.37 ± 0.30 J⋅kg-1⋅m-1 for 5+Y LIN and 5-Y LIN , respectively (calculated from the regression equation), and 4.39 ± 0.28 and 4.38 ± 0.27 J⋅kg-1⋅m-1 for GEC AVG and GEC LAST , respectively (F 1.08,42 = 14.6, P < 0.001). The absolute typical errors in AnC ranged between 0.03 and 0.16 kJ⋅kg-1 for the six pair-wise comparisons and the overall standard error of measurement (SEM) was 0.16 kJ⋅kg-1. CONCLUSION: These findings demonstrate a generally high disagreement in estimated anaerobic capacities between models and show that the inclusion of a measured Y-intercept in the linear regression (i.e., 5+Y LIN ) is likely to underestimate the MR TT_req and the GEC associated with the TT, and hence the AnC during maximal 4-min treadmill running.

Effects of Plyometric Training on Soft and Hard Surfaces for Improving Running Economy.

The present study investigated the effects of plyometric jump training on hard and soft surfaces on running economy (RE), maximal oxygen uptake (VO2max), running performance and the rate of force development in orienteers. Nineteen orienteers (11 women and 8 men, body mass 61.1 ± 7.3 kg, age 21 ± 5.8 yrs) were randomly stratified based on sex, age, VO2max and RE to plyometric jumping training (8 sessions over 4 weeks) on either a hard or a soft surface. RE, VO2max and running performance were assessed on a treadmill and outdoor on- and off-trail loops. Moreover, ground reaction forces and force development were assessed during a one leg drop-jump test. The training intervention led to an overall 2-7% improvement in treadmill and off-trail RE, independent of the jumping surface and running velocity assessed. These improvements were not explained by force development during drop jump tests, which remained unchanged following the intervention. The changes in time-trial performance were associated with changes in RE. Plyometric training improved RE with no difference between the hard or the soft training surface and improved RE was also independent of the running speed assessed. Furthermore, improved running performance was associated with changes in RE after the intervention.

Runners Adapt Different Lower-Limb Movement Patterns With Respect to Different Speeds and Downhill Slopes.

The aim of this study was to investigate the influence of slope and speed on lower-limb kinematics and energy cost of running. Six well-trained runners (VO2max 72 ± 6 mL·kg-1·min-1) were recruited for the study and performed (1) VO2max and energy cost tests and (2) an experimental running protocol at two speeds, 12 km·h-1 and a speed corresponding to 80% of VO2max (V80, 15.8 ± 1.3 km·h-1) on three different slopes (0°, -5°, and -10°), totaling six 5-min workload conditions. The workload conditions were randomly ordered and performed continuously. The tests lasted 30 min in total. All testing was performed on a large treadmill (3 × 5 m) that offered control over both speed and slope. Three-dimensional kinematic data of the right lower limb were captured during the experimental running protocol using eight infrared cameras with a sampling frequency of 150 Hz. Running kinematics were calculated using a lower body model and inverse kinematics approach. The generic model contained three, one, and two degrees of freedom at the hip, knee, and ankle joints, respectively. Oxygen uptake was measured throughout the experimental protocol. Maximum hip extension and flexion during the stance phase increased due to higher speed (p < 0.01 and p < 0.01, respectively). Knee extension at the touchdown and maximal knee flexion in the stance phase both increased on steeper downhill slopes (both p < 0.05). Ground contact time (GCT) decreased as the speed increased (p < 0.01) but was unaffected by slope (p = 0.73). Runners modified their hip movement pattern in the sagittal plane in response to changes in speed, whereas they altered their knee movement pattern during the touchdown and stance phases in response to changes in slope. While energy cost of running was unaffected by speed alone (p = 0.379), a shift in energy cost was observed for different speeds as the downhill gradient increased (p < 0.001). Energy cost was lower at V80 than 12 km·h-1 on a -5° slope but worse on a -10° slope. This indicates that higher speeds are more efficient on moderate downhill slopes (-5°), while lower speeds are more efficient on steeper downhill slopes (-10°).