Race Pace Research Articles

Specific Intensity for Peaking: Is Race Pace the Best Option?

Background:The peaking period for endurance competition is characterized for a relative increase of the intensity of training, after a longer period of training relatively dominated by lower intensity and higher volumeObjectives:The present study was designed to compare physiological and 10 km performance effects of high intensity training (HIT) versus race pace interval training (RP) during peaking for competition in well-trained runners.Patients and Methods:13 athletes took part in the study, they were divided into two groups: HIT and RP. HIT performed short intervals at ~105% of the maximal aerobic velocity (MAV), while RP trained longer intervals at a speed of ~90% of the MAV (a speed approximating 10 km race pace). After 12 weeks of baseline training, the athletes trained for 6 weeks under one of the two peaking regimes. Subjects performed 10 km prior to and after the intervention period. The total load of training was matched between groups during the treatment phase. Subjects completed a graded treadmill running test until volitional exhaustion prior to each 10 km race. MAV was determined as the minimal velocity eliciting maximal oxygen consumption (VO2max).Results:Both groups significantly improved their 10 km time (35 minutes 29 seconds ± 1 minutes 41 seconds vs 34 minutes 53 seconds ± 1 minutes 55 seconds, P < 0.01 for HIT; 35 minutes 27 seconds ± 1 minutes 40 seconds vs 34 minutes 53 seconds ± 1 minutes 18 seconds P < 0.01 for RP). VO2max increased after HIT (69 ± 3.6 vs 71.5 ± 4.2 ml.Kg-1.min-1, P < 0.05); while it didn’t for RP (68.4 ± 6 vs 69.8 ± 3 ml.Kg-1.min-1, p>0.05). In contrast, running economy decreased significantly after HIT (210 ± 6 ml.Kg-1.km-1 vs 218 ± 9, P < 0.05).Conclusions:A 6 week period of training at either 105% of MAV or 90% of MAV yielded similar performance gains in a 10km race performed at ~90% MAV. Therefore, the physiological impact of HIT training seems to be positive for VO2max but negative for running economy.

Imposed Cold-water Ingestion during Open Water Swimming in Internationally Ranked Swimmers.

The authors explored the effects of open water swimming in a tropical environment on both core temperature (T c) and thermal perceptions of high-level swimmers during an official international 10-km race and two 5-km swimming tests. The swimmers drank neutral water (i. e., 28.0±3.0°C) ad libitum every 2,000 m during Competition, whereas the ingested volume was imposed in the 5-km tests: every 1,000 m, they drank 190 mL of cold water (CW, 1.1±0.7°C) or neutral water (NW, 28.0±3.0°C). They also self-rated their thermal comfort and sensation (TC and TS), and their T c was recorded. The study demonstrated that adequate fluid intake significantly decreased T c in swimmers swimming at race pace in hot water (i. e., 37.5±0.3°C vs. 38.3±0.4°C, in NW vs. Competition, respectively). This effect was more pronounced with cold water (i. e., 36.7±1.1°C, in CW). No significant changes were noted in mean heart rate (i. e., 145±5, 143±4 and 141±5 bpm for NW, CW and Competition, respectively). Further studies are needed to explore the effect of this cooling method on the performances of international swimmers during tropical swimming events.

Performance analysis and prediction in triathlon

Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008–2012). The analysis reveals patterns of performance in five components of triathlon (three race “legs” and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

The relationship between steeplechase hurdle economy, mechanics, and performance

BackgroundResearch surrounding the steeplechase is scarce, with most research focusing primarily on how biomechanical factors relate to maintaining running speed while crossing barriers. One area that has not been well explored is the relationship between biomechanical factors and hurdling economy. The purpose of this study was to investigate how performance times and biomechanical variables relate to hurdling economy during the steeplechase. MethodsThis was accomplished by measuring running economy of collegiate and professional steeplechasers while running with and without hurdles. Biomechanical measures of approach velocity, takeoff distance, clearance height, and lead knee extension while hurdling, as well as steeplechase performance times were correlated to a ratio of running economy with and without hurdles. ResultsWhile oxygen uptake was 2.6% greater for the laps requiring five barriers, there was no correlation between steeplechase performance time and the ratio of running economy during the hurdle and non-hurdle laps. Results also indicated no correlation between the aforementioned biomechanical variables and ratio of running economy during the hurdle and non-hurdle laps. ConclusionIncreasing approach velocity did not negatively affect running economy. Increased approach velocity is a benefit for maintenance of race pace, but does not hurt economy of movement.

Whole Blood Lactate Levels Measured Using the YSI Analyzer and the NOVA Lactate Plus

The NOVA Lactate Plus is often used to measure blood lactate levels from a drop of blood taken from a finger prick. The NOVA can also be used to measure blood lactate from a drop of blood taken from an intravenous blood draw. Whole blood lactate can be measured from the same intravenous blood sample using the NOVA Lactate Plus and a “gold standard” device such as the YSI 2300 Analyzer. PURPOSE: The purpose of this study was to compare blood lactate levels measured using the handheld NOVA Lactate Plus and the YSI from the same blood samples. METHODS: Six well-trained men, 18-39 years of age with VO2max values ranging between 56 and 65 mL/kg/min volunteered to participate in this study. As part of a larger scale study, each participant completed an exercise test to determine VO2max and lactate threshold. Participants then completed multiple submaximal 30-minute steady-state runs on the treadmill to determine maximal lactate steady state (MLSS). During the steady-state runs, blood was withdrawn from the antecubital vein using an intravenous catheter. Whole blood lactate levels were measured from each blood sample using the NOVA Lactate Plus and the YSI. RESULTS: Blood lactate measures using the NOVA and the YSI from the same blood sample were significantly correlated (R=0.997). Nevertheless, blood lactate levels as measured by the NOVA handheld device significantly overestimated blood lactate levels as measured using the YSI by an average of 1.29 mmol/L (p=0.0001). CONCLUSIONS: While there was a significant correlation between lactate measurements between the two devices, the NOVA Lactate Plus significantly overestimated blood lactate concentrations compared to the YSI. When using the NOVA Lactate Plus device, use caution when interpreting the results. Overestimating blood lactate levels could result in an underestimation of training or race paces.

A Comparison Of The Intensity Of Exercise At Different Definitions Of The “Lactate Threshold”

Endurance athletes use information about their “lactate threshold” to design an effective training program, to monitor training progress, and to estimate a race pace. Various definitions of the “lactate threshold” are available in the literature. PURPOSE: The purpose of this study was to compare the intensities of exercise at which the “lactate threshold” occurs based on common definitions. METHODS: Six well-trained men, 18-39 years of age with VO2max values ranging between 56 and 65 mL/kg/min volunteered to participate in this study. Each participant completed an exercise test to determine VO2max and lactate threshold. Intravenous blood samples were taken during the last 30 s of each 3 min stage. Blood lactate levels were measured using the YSI analyzer and corrected for changes in hemoglobin and hematocrit. The “lactate threshold” was identified in each subject using each of the following methods: (1) visual detection of the inflection point of the lactate response curve, (2) a blood lactate level of 1 mmol/L greater than the previous value, (3) a blood lactate level of 1 mmol/L above a baseline value, (4) a fixed blood lactate of 4 mmol/L, and (5) the ventilatory threshold. RESULTS: An ANOVA indicated that the VO2 (mL/kg/min), HR (bpm), running speed, RER, and plasma blood lactate levels were not significantly different between four definitions of the “lactate threshold”: visual detection of the inflection point of the lactate response curve, ventilatory threshold, and 1 mmol/L above the previous lactate value and above the baseline value. The fixed blood lactate value of 4 mmol/L resulted in VO2 and HR values that were not significantly different from maximal values, and an RER value significantly greater than RER values at all other definitions. CONCLUSIONS: Although there were no significant differences in VO2. HR, RER, running speed, and blood lactate between four of the definitions of “lactate threshold”, there were practical differences that could influence training and performance.

Sex differences in cardiac function after prolonged strenuous exercise.

To evaluate sex differences in left ventricular (LV) function after an ultramarathon, and the association of vascular and training indices with the magnitude of exercise-induced cardiac fatigue. Descriptive field study. Fat Dog 100 Ultramarathon Trail Race, Canada. Thirty-four (13 women) recreational runners (aged 28-56 years). A 100-km or 160-km mountain marathon. Baseline baroreceptor sensitivity, heart rate variability, and arterial compliance; Pre-exercise and postexercise echocardiographic evaluations of LV dimensions, volumes, Doppler flow velocities, tissue velocities, strain, and strain rate. Finishers represented 17 men (44.8 ± 6.6 years) and 8 women (45.9 ± 10.2 years; P = 0.758). After ultraendurance exercise, significant reductions (P < 0.05) in fractional shortening (men: 40.9 ± 6.9 to 34.1 ± 7.6%; women: 42.5 ± 6.5 to 34.6 ± 7.9%) diastolic filling (E/A, men: 1.28 ± 0.68 to 1.26 ± 0.33; women: 1.55 ± 0.51 to 1.30 ± 0.27), septal and lateral tissue velocities (E'), and longitudinal strain (men: -21.02 ± 1.98 to -18.44 ± 0.34; women: -20.28 ± 1.90 to -18.44 ± 2.34) were observed. Sex differences were found for baseline cardiac structure and global function, peak late transmitral flow velocity, and estimates of LV filling pressures (P < 0.05). Regression analysis found that higher baseline arterial compliance was associated with lower reductions in cardiac function postexercise, to which sex was a significant factor for E' of the lateral wall. Faster race pace and greater lifetime ultramarathons were associated with lower reductions in LV longitudinal strain (P < 0.05). Cardiac responses after an ultramarathon were similar between men and women. Greater evidence of exercise-induced cardiac fatigue was found to be associated with lower baseline arterial compliance and training status/experience. These findings suggest that vascular health is an important contributor to the degree of cardiovascular strain incurred as the result of an acute bout of prolonged strenuous exercise.

Paddling Force Profiles at Different Stroke Rates in Elite Sprint Kayaking.

In sprint kayaking the role that paddling technique plays in optimizing paddle forces and resultant kayak kinematics is still unclear. The aim of this study was to analyze the magnitude and shape of the paddle force-time curve at different stroke rates, and their implications for kayak performance. Ten elite kayak paddlers (5 males and 5 females) were analyzed while performing 2000-m on-water trials, at 4 different paces (60, 80, and 100 strokes per minute, and race pace). The paddle and kayak were instrumented with strain gauges and accelerometers, respectively. For both sexes, the force-time curves were characterized at training pace by having a bell shape and at race pace by a first small peak, followed by a small decrease in force and then followed by a main plateau. The force profile, represented by the mean force/peak force ratio, became more rectangular with increasing stroke rate (F[3,40] = 7.87, P < .01). To obtain a rectangular shape to maximize performance, kayak paddlers should seek a stronger water phase with a rapid increase in force immediately after blade entry, and a quick exit before the force dropping far below the maximum force. This pattern should be sought when training at race pace and in competition.

Effects of training and anthropometric factors on marathon and 100 km ultramarathon race performance.

BackgroundMarathon (42 km) and 100 km ultramarathon races are increasing in popularity. The aim of the present study was to investigate the potential associations of anthropometric and training variables with performance in these long-distance running competitions.MethodsTraining and anthropometric data from a large cohort of marathoners and 100 km ultramarathoners provided the basis of this work. Correlations between training and anthropometric indices of subjects and race performance were assessed using bivariate and multiple regression analyses.ResultsA combination of volume and intensity in training was found to be suitable for prediction of marathon and 100 km ultramarathon race pace. The relative role played by these two variables was different, in that training volume was more important than training pace for the prediction of 100 km ultramarathon performance, while the opposite was found for marathon performance. Anthropometric characteristics in terms of body fat percentage negatively affected 42 km and 100 km race performance. However, when this factor was relatively low (ie, less than 15% body fat), the performance of 42 km and 100 km races could be predicted solely on the basis of training indices.ConclusionMean weekly training distance run and mean training pace were key predictor variables for both marathon and 100 km ultramarathon race performance. Predictive correlations for race performance are provided for runners with a relatively low body fat percentage.

Kinematic Analysis of Butterfly Swimming

This study aimed to examine the relative phase of the arm and leg movements and the percentage of each of the 4 arm movement phases at three race paces of the butterfly swimming between two levels of swimmers based on the temporal analysis. Eight elite male swimmers and eight club level college male swimmers participated in the study. Two underwater high-speed cameras (200Hz) were set in the transverse and sagittal plane under the water and synchronized to capture one cycle of butterfly stroke movement. The kinematics data were digitized and calculated with the Kwon 3D software. The continuous relative phase was calculated using the normalized time series of the angular displacement and angular velocity of the shoulder and knee joints angles. Macroscopically, one cycle of the arm-leg coordination pattern can be observed between two levels at three race paces in butterfly stroke: a consistent relationship (2:1) exists between two dolphin kicks and one arm stroke in butterfly swimming. The continuous relative phase analyses showed that, in the beginning of the stroke-catch phase, the continuous relative phase was from anti-phase (-180°) to in-phase (50°). For the pull phase, the in-phase relation (±50°) remained unchanged throughout the stage. During the push phase, the relative phase gradually increased toward anti-phase (180°). The percentage of catch, pull, push, and recovery phases were not evenly distributed across one cycle of the butterfly stroke. Especially in elite group, there is a trend of decreasing the percentage of catch phase. In conclusion, these results provide useful information for swimmers as well as coaches to examine the swimming movement of the butterfly stroke.

An electromyographic evaluation of dual role breathing and upper body muscles in response to front crawl swimming.

The upper body trunk musculature is key in supporting breathing, propulsion, and stabilization during front crawl swimming. The aim of this study was to determine if the latissimus dorsi, pectoralis major, and serratus anterior contributed to the development of inspiratory muscle fatigue observed following front crawl swimming. Fourteen trained swimmers completed a 200-m front crawl swim at 90% of race pace. Maximal inspiratory and expiratory mouth pressures (PImax and PEmax) were assessed before (baseline) and after each swim, and electromyography was recorded from the three muscles. Post-swim PImax fell by 11% (P < 0.001, d = 0.57) and the median frequency (MDF: a measure of fatigue) of the latissimus dorsi, pectoralis major, and serratus anterior fell to 90% (P = 0.001, d = 1.57), 87% (P = 0.001, r = -0.60) and 89% (P = 0.018, d = 1.04) of baseline, respectively. The fall in serratus anterior MDF was correlated with breathing frequency (r = 0.675, P = 0.008) and stroke rate (r = 0.639, P = 0.014). The results suggest that the occurrence of inspiratory muscle fatigue was partly caused by fatigue of these muscles, and that breathing frequency and stroke rate particularly affect the serratus anterior.

Current warm-up practices and the contemporary issues faced by elite swimming coaches

Background: Only limited scientific evidence is available on the best for competition warm-up design in elite swimming. Given the recent occurrence of several major technical and technological changes in elite swimming competitions, coaches are left to draw upon outdated guidelines when designing athlete’s warm-up strategies. The aim of the present study was to describe current warm-up practices and identify contemporary issues faced by elite swimming coaches within the competition environment. Methods: A total of 46 state- to international-level swimming coaches from Australia, Britain and Canada completed a questionnaire consisting of 18 questions (9 multiple choice and 9 short answer) relating to their views on the value of competition warmups, the volume, intensity and recovery used in their pool and out of pool warm-ups and other related issues. Results: The coaches identified three main aims of the competition warm-up: physiological (to elevate body temperature and increase muscle activation), physical (to increase feel of the water) and mental (to improve focus and relax nerves). Total warm-up volume employed ranged from 800 to 2400 m, beginning with 300–900m of continuous, low intensity (typically 30–70% of perceived exertion) swimming, followed by 200–600mof increasing intensity (60–90%) with efforts lasting 100–300min length and concluding with several 25–50mrace or near race pace (90–100%) efforts totalling 100–300 m. Some land-based warm-up strategies are encouraged but are typically limited to static stretching and core activation exercises. The preferred time frame between pool warmup end and race start (transition phase) was 20 min. Extended marshalling periods (>15 min), delayed competition schedules and the lengthy time required to change into racing suits (>10 min) were all identified as issues faced during competition. These issues extend the transition phase beyond the preferred time frame. Discussion: Although pool warm-ups are thoroughly prescribed they do not appear to address issues relating to the extended duration of the marshalling periods and the time required to don racing suits. Elevated body temperatures in addition to increased muscle activation are two of the main purported benefits of warming-up but have a limited effect beyond ∼15–20 min following exercise cessation, a scenario common in the contemporary swimming environment. Given these constraints, sport scientists should investigate methods for improving body temperature maintenance such as passive heating techniques and muscle reactivation strategies like postactivation potentiation during the transition phase. These approaches may lead to the optimisation of competition performance in the contemporary swimming environment.

Quantification of vibrations during mountain biking

Background:  During cross-country mountain biking, riders are subjected to vibrations due to the terrain, which must be damped before reaching the central nervous system.  Damping vibrations requires work, which may help to explain the decrease in economy for mountain biking as compared to road cycling (Titlestad et al., 2006 Journal of Sports Sciences, 24(2), 125-135).  Purpose: To describe the relationship between vibration mechanics and their interaction with terrain, bicycle and rider during a race pace effort on a cross country mountain bike track.  Methods: Participants (n=8) completed two separate laps on a cross country track using 26” and 29” wheels, at race speed. Power, cadence, speed, heart rate, and geographical position were sampled and logged every second for control purposes. Tri-axial accelerometers located at handlebar centre, lower left arm, lower left leg, seat post, lower back and medial forehead, recorded accelerations with a output rate 128 Hz to measure vibrations experienced during the whole lap and over terrain sections (uphill and downhill). Vibrations were quantified using a root mean square (RMS) and using Fourier analyses.  Results: RMS data showed greater total accelerations for 29” vs 26” wheels (p=0.0020), and a significant interaction of terrain and accelerometer location (p<.0001). While climbing, accelerations were generally low and concentrated at low movement frequencies. While descending, however, high RMS values were seen on the bicycle (handlebar and seat post) and the parts of the body near the interface with the bicycle (left arm and left leg), while lower accelerations at the lower back and head were not significantly different than the accelerations during climbing.  In addition, Fourier analyses showed that the accelerations occurred at a higher frequency when compared to uphill sections.  No differences between overall power output (p=0.3062) and heart rate (p=0.8423), yet overall time was greater for 26” compared to 29” wheels (p=0.0061). Discussion: The results show that mountain bikers are subjected to large accelerations, or vibrations, particularly during downhill sections.  These vibrations are damped before reaching the lower back and head, which requires metabolic work.  In addition, 29 inch wheels showed a clear performance advantage, going faster for the same average power, although resulting in greater vibrations for the riders.  Conclusion: This study demonstrates an additional non-propulsive, muscular challenge to riding during cross country mountain biking represented by a change in accelerations at the point of interface between bike-body compared to lower back and head.

Comparing bioenergetic models for the optimisation of pacing strategy in road cycling

Road cycling performance is dependent on race tactics and pacing strategy. To optimise the pacing strategy for any race performed with no drafting, a numerical model was introduced, one that solves equations of motion while minimising the finishing time by varying the power output along the course. The power output was constrained by two different hydraulic models: the simpler critical power model for intermittent exercise (CPIE) and the more sophisticated Margaria–Morton model (M–M). These were compared with a constant power strategy (CPS). The simulation of the three different models was carried out on a fictional 75 kg cyclist, riding a 2,000 m course. This resulted in finishing times of 162.4, 155.8 and 159.3 s and speed variances of 0.58, 0.26 and 0.29 % for the CPS, CPIE and M–M simulations, respectively. Furthermore, the average power output was 469.7, 469.7 and 469.1 W for the CPS, CPIE and M–M simulations, respectively. The M–M model takes more physiological phenomena into consideration compared to the CPIE model and, therefore, contributes to an optimised pacing strategy that is more realistic. Therefore, the M–M model might be more suitable for future studies on optimal pacing strategy, despite the relatively slower finishing time.

Transference of 3D accelerations during cross country mountain biking

Investigations into the work demands of Olympic format cross country mountain biking suggest an incongruent relationship between work done and physiological strain experienced by participants. A likely but unsubstantiated cause is the extra work demand of muscle damping of terrain/surface induced vibrations. The purpose of this study was to describe the relationship between vibration mechanics and their interaction with terrain, bicycle and rider during a race pace effort on a cross country mountain bike track, on both 26″ and 29″ wheels. Participants completed one lap of a cross country track using 26″ and 29″ wheels, at race pace. Power, cadence, speed, heart rate and geographical position were sampled and logged every second for control purposes. Tri-axial accelerometers located on the bicycle and rider, recorded accelerations (128Hz) and were used to quantify vibrations experienced during the whole lap and over terrain sections (uphill and downhill). While there were no differences in power output (p=0.3062) and heart rate (p=0.8423), time to complete the lap was significantly (p=0.0061) faster on the 29″ wheels despite increased vibrations in the larger wheels (p=0.0020). Overall accelerometer data (RMS) showed location differences (p<0.0001), specifically between the point of interface of bike–body compared to those experienced at the lower back and head. The reduction in accelerations at both the lower back and head are imperative for injury prevention and demonstrates an additional non-propulsive, muscular, challenge to riding. Stress was greatest during downhill sections as acceleration differences between locations were greater when compared to uphill sections, and thus possibly prevent the recovery processes that may occur during non-propulsive load.

English

The aim of this study was to investigate the relationships between biomechanical variables and running economy (RE). Eleven recreational (RR) and 14 well-trained runners (WT) completed 4 min stages on a treadmill at different speeds. During the test, biomechanical variables such as ground contact time (tc), swing time (tsw), stride length, frequency and angle and the length of the different subphases of ground contact were calculated using an optical measurement system. VO2 was measured in order to calculate RE. The WT runners were more economical than the RR at all speeds and presented lower tc, higher tsw, longer strides, lower stride frequencies and higher stride angles (P<0.05). Similarly, the WT runners experienced a later propulsion subphase than the RR runners (P<0.05). RE was positively related to tc, stride frequency and 10-km race pace, whereas it was negatively related to tsw, stride length, stride angle and the propulsive subphase. Our results suggest that running patterns characterized by longer stride lengths and higher stride angles, lower stride frequencies and tc, higher tsw and later propulsion suphases may enable an efficient energy use per stride.

“Live High–Train High” increases hemoglobin mass in Olympic swimmers

This study tested whether 3-4weeks of classical "Live High-Train High" (LHTH) altitude training increases swim-specific VO2max through increased hemoglobin mass (Hbmass). Ten swimmers lived and trained for more than 3weeks between 2,130 and 3,094m of altitude, and a control group of ten swimmers followed the same training at sea-level (SL). Body composition was examined using dual X-ray absorptiometry. Hbmass was determined by carbon monoxide rebreathing. Swimming VO2peak was determined and swimming trials of 4×50, 200 and 3,000m were performed before and after the intervention. Hbmass (n=10) was increased (P<0.05)after altitude training by 6.2±3.9% in the LHTH group, whereas no changes were apparent in the SL group (n=10). Swimming VO2peak was similar before and after training camps in both groups (LHTH: n=7, SL: n=6). Performance of 4×50m at race pace was improved to a similar degree in both groups (LHTH: n=10, SL: n=10). Maximal speed reached in an incremental swimming step test (P=0.051), and time to complete 3,000m tended (P=0.09) to be more improved after LHTH (n=10) than SL training (n=10). In conclusion, 3-4weeks of classical LHTH is sufficient to increase Hbmass but exerts no effect on swimming-specific VO2peak. LHTH may improve performance more than SL training.

Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance

This study investigated the influence of the regression model and initial intensity during an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and performance in elite-standard runners. Twenty-three well-trained runners completed a discontinuous incremental running test on a treadmill. Speed started at 9 km · h−1 and increased by 1.5 km · h−1 every 4 min until exhaustion, with a minute of recovery for blood collection. Lactate–speed data were fitted by exponential and polynomial models. The lactate threshold was determined for both models, using all the co-ordinates, excluding the first and excluding the first and second points. The exponential lactate threshold was greater than the polynomial equivalent in any co-ordinate condition (P < 0.001). For both models, the lactate threshold was lower when all co-ordinates were used than when the first and the first and second points were excluded (P < 0.001). 10-km race pace was correlated with both the exponential and polynomial lactate thresholds for all the co-ordinate conditions (r ≥ 0.75, P < 0.001 and r ≥ 0.56, P < 0.05, respectively). The results suggest that the exponential lactate threshold should be used instead of the polynomial equivalent since it is more strongly associated with performance and is independent of the initial intensity of the test.

A deterministic model based on evidence for the associations between kinematic variables and sprint kayak performance

The aim of this narrative review was to propose a deterministic model based on a review of previous research documenting the evidence for the associations between average kayak velocity and kinematic variables in sprint kayaking. Literature was reviewed after searching electronic databases using key words ‘kayak,’ ‘biomechanics,’ ‘velocity,’ ‘kinematics,’ and ‘performance.’ Our kinematic deterministic model for sprint kayaking performance shows that the average kayak velocity is determined by kayak stroke displacement and stroke time. Stroke time had the strongest correlation with 200-m race time (r = 0.86, p < 0.001), and stroke rate (inversely proportional to stroke time) was strongly correlated with average horizontal velocity over two consecutive strokes at race pace (r = − 0.83, p < 0.05). Increased stroke rate via decreased absolute water phase time and increased relative water phase time were indicative of more elite performance. There was no significant relationship between stroke displacement and velocity; however, a large decrease in stroke displacement may be detrimental to performance. Individual characteristics may be responsible for a paddlers’ ability to achieve and sustain a given stroke rate. Coaches should theoretically focus interventions on increasing stroke rate while maintaining stroke displacement; however this hypothesis should be confirmed with prospective studies.

Pacing characteristics of international Sprint Kayak athletes

This study aimed to profile pacing strategies and pacing profile of world-class kayakers during world championships. Data were from publically available websites of eight international competitive seasons (2004 - 2011). Data represent percentage average race pace. Mixed ANOVA was used to compare pacing (250 m splits) and race level (A and B-finals) and crew boats. Effect size was calculated converting F-values into r-values (P < 0.05). There were significant interactions between splits and season (F7.99, 255.7=13.08, P <0.001, r=0.05), splits and boat crew (F5.33, 255.7=4.82, P <0.001, r=0.02), race level, the split speed and the competitive season (F8.49, 271.5=2.07, P =0.035, r=0.01) and the race level, the split speed and the boat crews (F5.66, 271.5=2.28, P =0.04, r=0.01) for the 1000 m. There was a significant interaction between race level, split speed and boat crew (F1, 80=4.35, P =0.004, r=0.05) in the 500 m. Performances of A and B-finals were significantly different. In conclusion, pacing of sprint kayakers can vary according to race level (A or B-finals, elite or sub-elite respectively), crew (K1, K2 and K4), split distances (250 m splits) and competitive seasons. Additionally, our data suggests there may exist specific crew boat dynamics and, therefore, specific race demands.