Flat and Uphill Climb Time Trial Performance Prediction in Elite Amateur Cyclists

Intensified training before Olympic-distance triathlon in recreational triathletes: "Less pain, more gain"

Objectives

To examine 1) the contribution of physiological performance variables to Olympic-distance (OD) triathlon performance, and 2) the links between an 8-wk intensified training plus competition preceding the main OD triathlon race and the changes in the physiological status in triathletes.

Study Design

An observational longitudinal study.

Methods

Endurance performance variables during maximal incremental running and cycling tests, and average velocity during an all-out 400-m swimming performance test (V400) were assessed before (T1) and after (T2) the intensified training in 7 recreational-level triathletes.

Results

Overall main OD triathlon time was extremely largely (r = -0.94; P = 0.01) correlated with peak running velocity (PRV). Best correlation magnitude between exercise modes' partial race times and the corresponding specific physiological criterion tests was observed for swimming (r = -0.97; P < 0.001). Improvement in V400 (2.9%), PRV (1.5%) and submaximal running blood lactate concentration (17%) was observed along the training period, whereas no changes were observed in the cycling endurance performance variables. Higher volume of training plus competition at high intensity zones during cycling, running and swimming were associated with lower improvements or declines in their corresponding exercise mode-specific criterion performance variables (r = 0.81-0.90; P = 0.005-0.037).

Conclusion

Results indicate that: 1) PRV is highly associated with overall OD triathlon performance, and 2) spending much time at high relative intensities during swimming, cycling or running may lead, in a dose-response manner, to lower improvements or decreases on those exercise-specific physiological performance variables. This may favor the emergence of overreaching or diminished performance.

Sprint Performance in Arms-Only Front Crawl Swimming Is Strongly Associated With the Power-To-Drag Ratio

To date, optimal propulsion in swimming has been studied predominantly using physical or computational models of the arm and seldom during real-life swimming. In the present study we examined the contributions of selected power, technique and anthropometric measures on sprint performance during arms-only front crawl swimming. To this end, 25 male adult competitive swimmers, equipped with markers on their arms and hands, performed four 25-m sprint trials, which were recorded on video. For the fastest trial of each swimmer, we determined the average swim speed as well as two technique variables: the average stroke width and average horizontal acceleration. Each participant also swam 10–12 trials over a custom-made system for measuring active drag, the MAD system. Since the propelling efficiency is 100% while swimming over the MAD system, the power output of the swimmer is fully used to overcome the drag acting on the body. The resulting speed thus represents the ratio between power output and drag. We included this power-to-drag ratio, the power output and the drag coefficient of the fastest trial on the MAD system in the analysis. Finally, the body height and hand surface area of each swimmer were determined as anthropometric variables. A model selection procedure was conducted to predict the swim speed from the two technique variables, three power variables and the two anthropometric variables. The ratio between power output and the drag was the only significant predictor of the maximal swimming speed (v = 0.86·power/drag). The variations in this ratio explained 65% of the variance in swimming performance. This indicates that sprint performance in arms-only front crawl swimming is strongly associated with the power-to-drag ratio and not with the isolated power variables and the anthropometric and technique variables selected in the present study.

Laboratory-Based Physical and Physiological Test Results That Serve as Predictors of Male, Amateur Road Cyclists' Performance Levels

Coetzee, B, and Malan, D. Laboratory-based physical and physiological test results that serve as predictors of male, amateur road cyclists' performance levels. J Strength Cond Res 32(10): 2897-2906, 2018-The purposes of this study were first, to determine the practical significant differences of laboratory-based physical and physiological test results between a selected group of successful and less successful amateur, male road cyclists from Africa; and second, to determine the significance, adequacy, accurateness, and usefulness of laboratory-based physical and physiological test results to serve as predictors of these amateur, male road cyclists' performance levels. Male road cyclists, identified as the top amateur road cyclists of the cycling federations of 13 African countries, were subjected to a test battery for the measurement of lower-body flexibility, abdominal strength, peak and average anaerobic power output as well as maximum aerobic power. Practical significant differences between the successful and less successful road cyclists were found for almost all the Wingate related variables, some of the sub-maximum parameters, and most of the maximum physiological variables. Finally, the abdominal muscle strength test value, vertical jump distance, Wingate relative peak power, and respiratory compensation point expressed as percentage of V[Combining Dot Above]O2max and as relative power output were the physiological components that acted as adequate, accurate, and useful predictors of performance levels. Coaches and sport scientists should therefore include these components in testing protocols that are aimed at evaluating and improving cyclists' physical conditioning programs.

Heavy strength training improves running and cycling performance following prolonged submaximal work in well-trained female athletes

The purpose of this study was to investigate the effects of adding heavy strength training to female duathletes' normal endurance training on both cycling and running performance. Nineteen well‐trained female duathletes (VO_2max cycling: 54 ± 3 ml∙kg⁻¹∙min⁻¹, VO_2max running: 53 ± 3 ml∙kg⁻¹∙min⁻¹) were randomly assigned to either normal endurance training (E, n = 8) or normal endurance training combined with strength training (E+S, n = 11). The strength training consisted of four lower body exercises [3 × 4‐10 repetition maximum (RM)] twice a week for 11 weeks. Running and cycling performance were assessed using 5‐min all‐out tests, performed immediately after prolonged periods of submaximal work (3 h cycling or 1.5 h running). E+S increased 1RM in half squat (45 ± 22%) and lean mass in the legs (3.1 ± 4.0%) more than E. Performance during the 5‐min all‐out test increased in both cycling (7.0 ± 4.5%) and running (4.7 ± 6.0%) in E+S, whereas no changes occurred in E. The changes in running performance were different between groups. E+S reduced oxygen consumption and heart rate during the final 2 h of prolonged cycling, whereas no changes occurred in E. No changes occurred during the prolonged running in any group. Adding strength training to normal endurance training in well‐trained female duathletes improved both running and cycling performance when tested immediately after prolonged submaximal work.

Laboratory predictors of uphill cycling performance in trained cyclists

This study aimed to assess the relationship between an uphill time-trial (TT) performance and both aerobic and anaerobic parameters obtained from laboratory tests. Fifteen cyclists performed a Wingate anaerobic test, a graded exercise test (GXT) and a field-based 20-min TT with 2.7% mean gradient. After a 5-week non-supervised training period, 10 of them performed a second TT for analysis of pacing reproducibility. Stepwise multiple regressions demonstrated that 91% of TT mean power output variation (W kg^-1) could be explained by peak oxygen uptake (ml kg^-1.min^-1) and the respiratory compensation point (W kg^-1), with standardised beta coefficients of 0.64 and 0.39, respectively. The agreement between mean power output and power at respiratory compensation point showed a bias ± random error of 16.2 ± 51.8 W or 5.7 ± 19.7%. One-way repeated-measures analysis of variance revealed a significant effect of the time interval (123.1 ± 8.7; 97.8 ± 1.2 and 94.0 ± 7.2% of mean power output, for epochs 0-2, 2-18 and 18-20 min, respectively; P < 0.001), characterising a positive pacing profile. This study indicates that an uphill, 20-min TT-type performance is correlated to aerobic physiological GXT variables and that cyclists adopt reproducible pacing strategies when they are tested 5 weeks apart (coefficients of variation of 6.3; 1 and 4%, for 0-2, 2-18 and 18-20 min, respectively).

Field-measured drag area is a key correlate of level cycling time trial performance

Drag area (Ad ) is a primary factor determining aerodynamic resistance during level cycling and is therefore a key determinant of level time trial performance. However, Ad has traditionally been difficult to measure. Our purpose was to determine the value of adding field-measured Ad as a correlate of level cycling time trial performance. In the field, 19 male cyclists performed a level (22.1 km) time trial. Separately, field-determined Ad and rolling resistance were calculated for subjects along with projected frontal area assessed directly (AP ) and indirectly (Est AP ). Also, a graded exercise test was performed to determine [Formula: see text] peak, lactate threshold (LT), and economy. [Formula: see text] peak ([Formula: see text]) and power at LT were significantly correlated to power measured during the time trial (r = 0.83 and 0.69, respectively) but were not significantly correlated to performance time (r = - 0.42 and -0.45). The correlation with performance time improved significantly (p < 0.05) when these variables were normalized to Ad . Of note, Ad alone was better correlated to performance time (r = 0.85, p < 0.001) than any combination of non-normalized physiological measure. The best correlate with performance time was field-measured power output during the time trial normalized to Ad (r = - 0.92). AP only accounted for 54% of the variability in Ad . Accordingly, the correlation to performance time was significantly lower using power normalized to AP (r = - 0.75) or Est AP (r = - 0.71). In conclusion, unless normalized to Ad , level time trial performance in the field was not highly correlated to common laboratory measures. Furthermore, our field-measured Ad is easy to determine and was the single best predictor of level time trial performance.

Anaerobic power in road cyclists is improved after 10 weeks of whole-body vibration training

Whole-body vibration (WBV) training has previously improved muscle power in various athletic groups requiring explosive muscle contractions. To evaluate the benefit of including WBV as a training adjunct for improving aerobic and anaerobic cycling performance, road cyclists (n = 9) performed 3 weekly, 10-minute sessions of intermittent WBV on synchronous vertical plates (30 Hz) while standing in a static posture. A control group of cyclists (n = 8) received no WBV training. Before and after the 10-week intervention period, lean body mass (LBM), cycling aerobic peak power (Wmax), 4 mM lactate concentration (OBLA), VO2peak, and Wingate anaerobic peak and mean power output were determined. The WBV group successfully completed all WBV sessions but reported a significant 30% decrease in the weekly cycling training time (pre: 9.4 ± 3.3 h·wk(-1); post: 6.7 ± 3.7 h·wk(-1); p = 0.01) that resulted in a 6% decrease in VO2peak and a 4% decrease in OBLA. The control group reported a nonsignificant 6% decrease in cycling training volume (pre: 9.5 ± 3.6 h·wk(-1); 8.6 ± 2.9 h·wk(-1); p = 0.13), and all measured variables were maintained. Despite the evidence of detraining in the WBV group, Wmax was maintained (pre: 258 ± 53 W; post: 254 ± 57 W; p = 0.43). Furthermore, Wingate peak power increased by 6% (668 ± 189 to 708 ± 220 W; p = 0.055), and Wingate mean power increased by 2% (553 ± 157 to 565 ± 157 W; p = 0.006) in the WBV group from preintervention to postintervention, respectively, without any change to LBM. The WBV training is an attractive training supplement for improving anaerobic power without increasing muscle mass in road cyclists.

Personal best time and training volume, not anthropometry, is related to race performance in the 'Swiss Bike Masters' mountain bike ultramarathon

We investigated in 73 male ultraendurance mountain bikers, with (mean and SD) age 39.1 (8.6) years, weight 74.4 (8.3) kg, height 1.78 (0.07) m, and a body mass index of 23.3 (1.9) kg·m⁻², whether variables of anthropometry, training, or prerace experience were associated with race time using bi and multivariate analysis. Our investigation was conducted at the "Swiss Bike Masters," which covers a distance of 120 km and an altitude of 5,000 m. In the bivariate analysis, body mass index (r = 0.29), circumference of upper arm (r = 0.28), sum of upper body skinfolds (r = 0.38), sum of lower body skinfolds (r = 0.25), sum of 8 skinfolds (r = 0.36), percent body fat (r = 0.41), total cycling kilometers per year (r = -0.47), yearly volume in both mountain bike (r = -0.33) and road cycling (r = -0.52), number of training units per week (r = -0.48), distance per unit in road cycling (r = -0.33), average speed during training in road cycling (r = -0.33), and personal best time in the "Swiss Bike Masters"(r = 0.67) were related to race time. In the multiple linear regression analysis, personal best time in the "Swiss Bike Masters" (p = 0.000), total yearly cycling kilometers (p = 0.004), and yearly training kilometers in road cycling (p = 0.017) were related to race time. When the personal best time was the dependent variable in a separate regression model, total yearly cycling kilometers (p = 0.002) remained the single predictor variable. We concluded that finishing a particular mountain bike ultramarathon does not seem to require a special anthropometry but rather a specific skill and experience for this selective kind of race coupled with a high training volume. For practical use, we concluded that successful athletes in a mountain bike ultramarathon, in a special environment and using sophisticated equipment, need prerace experience coupled with high training volume, rather than any special anthropometry.