Virtual Training of Endurance Cycling - A Summary of Strengths, Weaknesses, Opportunities and Threats

Training, environmental and nutritional practices in indoor cycling: an explorative cross-sectional questionnaire analysis

Introduction

Indoor cycling at home has grown rapidly in recent years facilitated by advances in technology and gamification. However, there is limited data on individual's training practices when cycling indoors.

Methods

Using a single-time point, cross-sectional questionnaire, we gathered information on equipment, environmental considerations, training practices and nutrition during indoor cycling.

Results

Following 492 responses, external variables (weather; 88.4%, lack of daylight; 56.3%), time efficiency (81.9%) and general fitness (70.9%) were most frequently cited as reasons to engage in indoor cycling. "Smart" turbo trainers linked to a mixed-reality cycling software were most frequently reported in equipment set-up. 78% of participants attempted to control temperature with 96% of these participants using at least 1 fan to control airflow. The volume of indoor training differed between seasons (winter: 6h10 ± 3 h 30, summer 2h52 ± 2h57, p < 0.001), and structured (61.9%) and unstructured work-outs (64.7%) were completed more than once a week with fewer participants engaging in competitive/racing events (20.9%). 98% percent of participants consumed fluids with an average fluid intake of 0.74 ± 0.28 L/h. Dependent on type of work-out, participants reported less planning of carbohydrate and protein intake during short-duration work-outs (∼40%-60%) relative to longer-duration work-outs (∼56%-80%). Caffeine use was the most frequently reported ergogenic aid.

Conclusion

Together we report indoor cycling practices with respect to training equipment, considerations of environmental and nutritional strategies and training habits. Our findings could be used to support the development of future research and indoor training guidelines.

The arena or E-games triathlon as a unique real world and virtual mixed-model endurance sports event

The sport of triathlon has evolved to become a discipline comprising races of different lengths and formats. It has also undergone significant growth in popularity and exposure with several variations in format from the classic swim - bike - run combination attracting significant television and media coverage. Since 2021 an original and unique format called the Arena Games Triathlon (or in 2024 the E-Games) has evolved that involves athletes competing against each other in swimming, cycling and running combining both the real and virtual worlds in one race. This model of endurance sport is currently unique, provides instantaneous data on performance and has the potential to be a tool for performance prediction, talent selection and sport development. The goal of this perspective paper is to provide context around the emergence of the Arena Games Triathlon series, describe the format of this type of racing, outline how it has the potential to drive training and evaluation of triathletes and discuss the attractiveness of its future inclusion as an Olympic discipline.

The Additional Effect of Training Above the Maximal Metabolic Steady State on VO2peak, Wpeak and Time-Trial Performance in Endurance-Trained Athletes: A Systematic Review, Meta-analysis, and Reality Check

BACKGROUND

To improve sport performance, athletes use training regimens that include exercise below and above the maximal metabolic steady state (MMSS).

OBJECTIVE

The objective of this review was to determine the additional effect of training above MMSS on VO2peak, Wpeak and time-trial (TT) performance in endurance-trained athletes.

METHODS

Studies were included in the review if they (i) were published in academic journals, (ii) were in English, (iii) were prospective, (iv) included trained participants, (v) had an intervention group that contained training above and below MMSS, (vi) had a comparator group that only performed training below MMSS, and (vii) reported results for VO2peak, Wpeak, or TT performance. Medline and SPORTDiscus were searched from inception until February 23, 2023.

RESULTS

Fourteen studies that ranged from 2 to 12 weeks were included in the review. There were 171 recreational and 128 competitive endurance athletes. The mean age and VO2peak of participants ranged from 15 to 43 years and 38 to 68 mL·kg-1·min-1, respectively. The inclusion of training above MMSS led to a 2.5 mL·kg-1·min-1 (95% CI 1.4-3.6; p < 0.01; I2 = 0%) greater improvement in VO2peak. A minimum of 81 participants per group would be required to obtain sufficient power to determine a significant effect (SMD 0.44) for VO2peak. No intensity-specific effect was observed for Wpeak or TT performance, in part due to a smaller sample size.

CONCLUSION

A single training meso-cycle that includes training above MMSS can improve VO2peak in endurance-trained athletes more than training only below MMSS. However, we do not have sufficient evidence to conclude that concurrent adaptation occurs for Wpeak or TT performance.

Effect of Video Camera Angle on the Detection of Compensatory Movements during Motion Observation

When exercise instructions are provided over the Internet, such as in online personal training, an instructor checks the user's form by watching their motion video recorded using a single camera device. However, fixed shooting angles may affect the detection of incorrect forms, including compensatory movements. This study aimed to verify whether differences in the shooting direction could influence compensatory movement detection by conducting motion observation using training motion videos shot from two angles. Videos of four training movements, including compensatory movements, were simultaneously captured from the front and side. Ten university students studying physical therapy watched the videos from each angle to detect compensatory movements. This study revealed significant differences between the plane of motion in which the compensatory action occurred and the direction of shooting for the false responses in the compensatory action detection for the three movements (p < 0.05). The results indicated that the shooting direction and the plane of motion in which the compensatory action occurred affected the detection of compensatory movements, which was attributable to differences in information on the amount of joint change depending on the direction of joint motion observation and to a lack of binocular visual information necessary for depth motion detection.

Perceptions of Cheating and Doping in E-Cycling

E-cycling is a growing area of cycling appealing to competitive cyclists and fitness enthusiasts. Zwift is the most popular e-cycling platform, with approx. 1 million subscribers and is a virtual environment that hosts regular races, including the UCI e-cycling world championships. The popularity of Zwift has given rise to cases of cheating and hacking the system to gain an advantage in e-racing. As a result, some high-profile professional riders have faced bans. We set out to understand the thoughts and concerns e-cyclists have about cheating, hacking, and doping in e-cycling. A total of 337 females and 1130 males were recruited over a 7-week period via social networking sites to complete an online survey. Forty-four per cent had experienced cheating during e-racing, which made them feel angry, annoyed, disappointed, and cheated. However, 15% of those who experienced cheating said they did not care, possibly because many see e-racing as a game or training tool rather than a competitive event. Eighty-seven per cent of participants were in favour of enforcing a ban on cheaters in e-cycling, while 34% wanted cheaters to be banned during in-person cycling events too. Results indicate that many e-cyclists have experienced cheating and would like clearer rules and bans for cheaters during e-races.

Influence of Air Velocity on Self-Paced Exercise Performance in Hot Conditions

PURPOSE

This study aimed to determine the effect of different air velocities on heat exchange and performance during prolonged self-paced exercise in the heat.

METHODS

Twelve male cyclists performed a 700-kJ time trial in four different air velocity conditions (still air, 16, 30, and 44 km·h -1 ) in 32°C and 40% relative humidity. Performance, thermal, cardiovascular, and perceptual responses were measured, and heat balance parameters were estimated using partitional calorimetry, including the maximum potential for sweat evaporation ( Emax ).

RESULTS

Mean power output was lower in still air (232 ± 42 W) than 16 (247 ± 30 W), 30 (250 ± 32 W), and 44 km·h -1 (248 ± 32 W; all P < 0.001), but similar between the 16-, 30-, and 44-km·h -1 air velocity conditions ( P ≥ 0.275). Emax was lower in still air (160 ± 13 W·m -2 ) than 16 (298 ± 25 W·m -2 ), 30 (313 ± 23 W·m -2 ), and 44 km·h -1 (324 ± 31 W·m -2 ) and lower in 16 than 44 km·h -1 (all P < 0.001). Peak core temperature was higher in still air (39.4°C ± 0.7°C) than 16 (39.0°C ± 0.45°C), 30 (38.8°C ± 0.3°C), and 44 km·h -1 (38.8°C ± 0.5°C; all P ≤ 0.002). Mean skin temperature was lower with greater airflow ( P < 0.001) but similar in 30 and 40 km·h -1 ( P = 1.00). Mean heart rate was ~2 bpm higher in still air than 44 km·h -1 ( P = 0.035). RPE was greater in still air than 44 km·h -1 ( P = 0.017).

CONCLUSIONS

Self-paced cycling in still air was associated with a lower Emax and subsequently higher thermal strain, along with a similar or greater cardiovascular strain, despite work rate being lower than in conditions with airflow. The similarity in performance between the 16-, 30-, and 44-km·h -1 air velocity conditions suggests that airflow ≥16 km·h -1 does not further benefit self-paced exercise performance in the heat because of modest improvements in evaporative efficiency.

The reproducibility of 20-min time-trial performance on a virtual cycling platform

This study aimed to analyse the reproducibility of mean power output during 20-min cycling time-trials, in a remote home-based setting, using the virtual-reality cycling software, Zwift. Forty-four cyclists (11 women, 33 men; 37 ± 8 years old, 180 ± 8 cm, 80.1 ± 13.2 kg) performed 3 x 20-min time-trials on Zwift, using their own setup. Intra-class correlation coefficient (ICC), coefficient of variation (CV) and typical error (TE) were calculated for the overall sample, split into 4 performance groups based on mean relative power output (25% quartiles) and sex. Mean ICC, TE and CV of mean power output between time-trials were 0.97 [0.95-0.98], 9.36 W [8.02-11.28 W], and 3.7% [3.2-4.5], respectively. Women and men had similar outcomes (ICC: 0.96 [0.89-0.99] vs 0.96 [0.92-0.98]; TE: 8.30 W [6.25-13.10] vs. 9.72 W [8.20-12.23]; CV: 3.8% [2.9-6.1] vs. 3.7% [3.1-4.7], respectively), although cyclists from the first quartile showed a lower CV in comparison to the overall sample (Q1: 2.6% [1.9-4.1] vs. overall: 3.7% [3.2-4.5]). Our results indicate that power output during 20-minute cycling time-trials on Zwift are reproducible and provide sports scientists, coaches and athletes, benchmark values for future interventions in a virtual-reality environment.