Assessment of bike handling during cycling individual time trials with a novel analytical technique adapted from motorcycle racing

A methodology to study bike handling of cyclists during individual time trials (ITT) is presented. Lateral and longitudinal accelerations were estimated from GPS data of professional cyclists (n=53) racing in two ITT of different length and technical content. Acceleration points were plotted on a plot (g-g diagram) and they were enclosed in an ellipse. A correlation analysis was conducted between the area of the ellipse and the final ITT ranking. It was hypothesized that a larger area was associated to a better performance. An analytical model for the bike-cyclist system dynamics was used to conduct a parametric analysis on the influence of riding position on the shape of the g-g diagram. A moderate (n=27, r=-0.40, p=0.038) and a very large (n=26, r=-0.83, p<0.0001) association were found between the area of the enclosing ellipse and the final ranking in the two ITT. Interestingly, this association was larger in the shorter race with higher technical content. The analytical model suggested that maximal decelerations are highly influenced by the cycling position, road slope and speed. This investigation, for the first time, explores a novel methodology that can provide insights into bike handling, a large unexplored area of cycling performance.

Sprint Tactics in the Tour de France: A Case Study of a World-Class Sprinter (Part II)

PURPOSE

To describe the performance and tactical sprint characteristics of a world-class sprinter competing in the Tour de France. In addition, differences in the sprint tactics of 2 teams and won versus lost sprints are highlighted.

METHOD

Power output (PO) and video footage of 21 sprints were analyzed. Position in the peloton and number of teammates supporting the sprinter at different times before the finish line together with PO for different time intervals were determined. Sprints were classified as team Shimano (2013-2014) and team Quick-step (2016-2017), as well as won or lost.

RESULTS

The sprinter was highly successful, winning 14 out of the 21 sprints. At time intervals 10 to 5, 3 to 2, and 1.5 to 1 minute, POs were significantly lower in team Quick-step compared with team Shimano, but the sprinter was positioned further away from the front at 10, 2, 1.5, 1, and 0.5 minutes at team Quick-step compared with team Shimano. The PO was higher at time interval 0.5 to 0.25 minutes before the finish line with team Quick-step when compared with team Shimano. The position of the sprinter in the peloton in lost sprints was further away from the front at 0.5 minutes before the finish compared with won sprints, while no differences were noted for PO and the number of teammates between won and lost sprints.

CONCLUSIONS

Differences in sprint tactics (Shimano vs Quick-step) influence the PO and position in the peloton during the sprint preparation. In addition, the position at 0.5 minutes before the finish line influences the outcome (won or lost) of the sprint.

Aerodynamic benefits for a cyclist by drafting behind a motorcycle

Motorcycles are present in cycling races for reasons including television broadcasting. During parts of the race, these motorcycles ride in front of individual or groups of cyclists. Concerns have been expressed in the professional cycling community that these motorcycles can provide aerodynamic benefits in terms of drag reduction for the cyclists drafting behind them. However, to the best of our knowledge, no information about the extent of these benefits is present in the scientific literature. Therefore, this paper analyses the potential drag reduction for a cyclist by drafting behind a motorcycle. Wind tunnel measurements and numerical simulations with computational fluid dynamics were performed. It was shown that drafting at separation distances d = 2.64, 10, 30 and 50 m can reduce the drag of the cyclist down to 52, 77, 88 and 93% of that of an isolated cyclist, respectively. A cyclist power model is used to convert these drag reductions into potential time gains. For a non-drafting cyclist at a speed of 54 km/h on level road in calm weather, the time gains by drafting at d = 2.64, 10, 30 and 50 m are 12.7, 5.4, 2.7 and 1.6 s per km, respectively. These time differences can influence the outcome of cycling races. The current rules of the International Cycling Union do not prevent these aerodynamic benefits from occurring in races.

Vibrotactile feedback for correcting aerodynamic position of a cyclist

Guidance to maintain an optimal aerodynamic position is currently unavailable during cycling. This study used real-time vibrotactile feedback to guide cyclists to a reference position with minimal projected frontal area as an indicator of aerodynamic drag, by optimizing torso, shoulder, head and elbow position without compromising comfort when sitting still on the bike. The difference in recapturing the aerodynamic reference position during cycling after predefined deviations from the reference position at different intensities was analysed for 14 participants between three interventions, consisting of 1) vibrotactile feedback with a margin of error of 1.5% above the calibrated reference projected frontal area, 2) vibrotactile feedback with a margin of 3%, and 3) no feedback. The reference position is significantly more accurately achieved using vibrotactile feedback compared to no feedback (p < 0.001), but there is no significant difference between the 1.5% and 3% margin (p = 0.11) in terms of relative projected frontal area during cycling compared to the calibrated reference position (1.5% margin -0.46 ± 1.76%, 3% margin -0.01 ± 2.01%, no feedback 2.59 ± 3.29%). The results demonstrate that vibrotactile feedback can have an added value in assisting and correcting cyclists in recapturing their aerodynamic reference position.

Validity of a novel device for real-time analysis of cyclists' drag area

OBJECTIVES

To assess the reliability, validity, and sensitivity of a novel device (Notio Konect™) which is purported to provide a real-time analysis of aerodynamic drag area (CdA) during cycling.

DESIGN

Observational, cross-sectional study.

METHODS

Fifteen trained cyclists rode in an indoor velodrome using three different positions (upright, aero [holding aero bars], and optimized aero [similar to aero, but wearing a time-trial helmet]). They completed six 1-min trials in each position. The CdA was measured with Notio and with two other systems (Track Aero System™ [TAS] and a validated mathematical model).

RESULTS

The CdA measured with Notio showed good reliability (intra-class correlation coefficient [ICC]=0.92, 90% confidence interval [CI]=0.89-0.95). Notio showed an almost perfect relationship with both TAS (ICC=0.99, 90% CI=0.98-0.99) and the mathematical model (ICC=0.99, 90% CI=0.98-0.99). However, the CdA values provided by the former (0.308±0.051m²) were significantly higher (albeit with a trivial effect size [ES]) compared with TAS (0.300±0.051m², p<0.001, ES=0.15) and the mathematical model (0.303±0.051m², p=0.005, ES=0.09). The CdA was higher in the upright than in the aero position with all systems (all p<0.001, ES=1.84-1.89), and higher in the aero than in the optimized aero position when measured with TAS (p=0.033, ES=0.22) or the mathematical model (p=0.024, ES=0.24), but not with Notio (p=0.220, ES=0.19).

CONCLUSIONS

Notio appears to be reliable, strongly correlated to other established systems, and discerns large (upright vs aero) but not small (aero vs optimized aero) variations in riding position. Further research is needed to confirm its validity in outdoor conditions.

Validity of the Velocomp PowerPod Compared With the Verve Cycling InfoCrank Power Meter

PURPOSE

To determine the validity of the Velocomp PowerPod power meter in comparison with the Verve Cycling InfoCrank power meter.

METHODS

This research involved 2 separate studies. In study 1, 12 recreational male road cyclists completed 7 maximal cycling efforts of a known duration (2 times 5 s and 15, 30, 60, 240, and 600 s). In study 2, 4 elite male road cyclists completed 13 outdoor cycling sessions. In both studies, power output of cyclists was continuously measured using both the PowerPod and InfoCrank power meters. Maximal mean power output was calculated for durations of 1, 5, 15, 30, 60, 240, and 600 seconds plus the average power output in study 2.

RESULTS

Power output determined by the PowerPod was almost perfectly correlated with the InfoCrank (r > .996; P < .001) in both studies. Using a rolling resistance previously reported, power output was similar between power meters in study 1 (P = .989), but not in study 2 (P = .045). Rolling resistance estimated by the PowerPod was higher than what has been previously reported; this might have occurred because of errors in the subjective device setup. This overestimation of rolling resistance increased the power output readings.

CONCLUSION

Accuracy of rolling resistance seems to be very important in determining power output using the PowerPod. When using a rolling resistance based on previous literature, the PowerPod showed high validity when compared with the InfoCrank in a controlled field test (study 1) but less so in a dynamic environment (study 2).