A longitudinal analysis of start position and the outcome of World Cup cross-country mountain bike racing

Race development and performance-determining factors in a mass-start cross-country skiing competition

Introduction

Although five of six Olympic events in cross-country skiing involve mass-starts, those events are sparsely examined scientifically. Therefore, in this study, we investigated speed profiles, pacing strategies, group dynamics and their performance-determining impact in a cross-country skiing mass-start competition.

Methods

Continuous speed and position of 57 male skiers was measured in a six-lap, 21.8 km national mass-start competition in skating style and later followed up with an online questionnaire. Skiers ranked from 1 to 40 were split into four performance-groups: R1-10 for ranks 1 to 10, R11-20 for ranks 11 to 20, R21-30 for ranks 21 to 30, and R31-40 for ranks 31 to 40.

Results

All skiers moved together in one large pack for 2.3 km, after which lower-performing skiers gradually lost the leader pack and formed small, dynamic packs. A considerable accordion effect occurred during the first half of the competition that lead to additional decelerations and accelerations and a higher risk of incidents that disadvantaged skiers at the back of the pack. Overall, 31% of the skiers reported incidents, but none were in R1-10. The overall trend was that lap speed decreased after Lap 1 for all skiers and thereafter remained nearly unchanged for R1-10, while it gradually decreased for the lower-performing groups. Skiers in R31-40, R21-30, and R11-20 lost the leader pack during Lap 3, Lap 4, and Lap 5, respectively, and more than 60% of the time-loss relative to the leader pack occurred in the uphill terrain sections. Ultimately, skiers in R1-10 sprinted for the win during the last 1.2 km, in which 2.4 s separated the top five skiers, and a photo finish differentiated first from second place. Overall, a high correlation emerged between starting position and final rank.

Conclusions

Our results suggest that (a) an adequate starting position, (b) the ability to avoid incidents and disadvantages from the accordion effect, (c) tolerate fluctuations in intensity, and (d) maintain speed throughout the competition, particularly in uphill terrain, as well as (e) having well-developed final sprint abilities, are key factors determining performance during skating-style mass-start cross-country skiing competitions.

Current Perspectives of Cross-Country Mountain Biking: Physiological and Mechanical Aspects, Evolution of Bikes, Accidents and Injuries

Mountain biking (MTB) is a cycling modality performed on a variety of unpaved terrain. Although the cross-country Olympic race is the most popular cross-country (XC) format, other XC events have gained increased attention. XC-MTB has repeatedly modified its rules and race format. Moreover, bikes have been modified throughout the years in order to improve riding performance. Therefore, the aim of this review was to present the most relevant studies and discuss the main results on the XC-MTB. Limited evidence on the topic suggests that the XC-MTB events present a variation in exercise intensity, demanding cardiovascular fitness and high power output. Nonetheless, these responses and demands seem to change according to each event. The characteristics of the cyclists differ according to the performance level, suggesting that these parameters may be important to achieve superior performance in XC-MTB. Moreover, factors such as pacing and ability to perform technical sections of the circuit might influence general performance. Bicycles equipped with front and rear suspension (i.e., full suspension) and 29″ wheels have been shown to be effective on the XC circuit. Lastly, strategies such as protective equipment, bike fit, resistance training and accident prevention measures can reduce the severity and the number of injuries.

Impact of a Cold Environment on the Performance of Professional Cyclists: A Pilot Study

The practice of physical activity in a variable climate during the same competition is becoming more and more common due to climate change and increasingly frequent climate disturbances. The main aim of this pilot study was to understand the impact of cold ambient temperature on performance factors during a professional cycling race. Six professional athletes (age = 27 ± 2.7 years; height = 180.86 ± 5.81 cm; weight = 74.09 ± 9.11 kg; % fat mass = 8.01 ± 2.47%; maximum aerobic power (MAP) = 473 ± 26.28 W, undertook ~20 h training each week at the time of the study) participated in the Tour de la Provence under cold environmental conditions (the ambient temperature was 15.6 ± 1.4 °C with a relative humidity of 41 ± 8.5% and the normalized ambient temperature (T_awc) was 7.77 ± 2.04 °C). Body core temperature (T_co) was measured with an ingestible capsule. Heart rate (HR), power, speed, cadence and the elevation gradient were read from the cyclists’ onboard performance monitors. The interaction (multivariate analysis of variance) of the T_awc and the elevation gradient has a significant impact (F(1.5) = 32.2; p < 0.001) on the variables (cadence, power, velocity, core temperature, heart rate) and on each individual. Thus, this pilot study shows that in cold environmental conditions, the athlete’s performance was limited by weather parameters (ambient temperature associated with air velocity) and race characteristics. The interaction of T_awc and elevation gradient significantly influences thermal (T_co), physiological (HR) and performance (power, speed and cadence) factors. Therefore, it is advisable to develop warm-up, hydration and clothing strategies for competitive cycling under cold ambient conditions and to acclimatize to the cold by training in the same conditions to those that may be encountered in competition.

Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments

Video-based trajectory analysis might be rather well discussed in sports, such as soccer or basketball, but in cycling, this is far less common. In this paper, a video processing pipeline to extract riding lines in cyclocross races is presented. The pipeline consists of a stepwise analysis process to extract riding behavior from a region (i.e., the fence) in a video camera feed. In the first step, the riders are identified by an Alphapose skeleton detector and tracked with a spatiotemporally aware pose tracker. Next, each detected pose is enriched with additional meta-information, such as rider modus (e.g., sitting on the saddle or standing on the pedals) and detected team (based on the worn jerseys). Finally, a post-processor brings all the information together and proposes ride lines with meta-information for the riders in the fence. The presented methodology can provide interesting insights, such as intra-athlete ride line clustering, anomaly detection, and detailed breakdowns of riding and running durations within the segment. Such detailed rider info can be very valuable for performance analysis, storytelling, and automatic summarization.

Influence of environmental factors on Olympic cross-country mountain bike performance

Olympic distance cross-country cycling (XCO) is a discipline subject to wide performance variability due to uncontrollable environmental factors such as altitude, ambient temperature and/or humidity. This study therefore aimed to investigate the impact of environmental factors on XCO performance in under-23 and elite female and male categories.Individual data were collected from Continental Cup, World Cup, World Championship, and Olympics Games for U23 and elite female and male categories from 2009 to 2018. Factors included were race time (range: 55-157 min), average speed (range: 7.6-32.2 km/h), distance (range: 15.2-48.4 km), altitude (range: 50-2680 m), ambient temperature (range 7-41°C), relative and absolute humidity (range: 8-97% and 2.4-25.3 g/m³, respectively), and categories.The analysis represents 10,966 individual data which indicate a continuous progression of the performance for all categories. Principal component analysis reveals that the slowest XCO performance was resulting from high ambient temperature and absolute humidity. Regressions revealed that only altitude (P < 0.0001) have a direct linear negative effect on XCO average speed. A significant negative interaction effect of altitude with absolute humidity (P < 0.0001) on XCO average speed was also found. In addition, the higher the absolute humidity, the higher is the impact of ambient temperature (P < 0.0001) on XCO average speed.While XCO performance progressed over time regardless of the categories, results also indicate that altitude, ambient temperature, and absolute humidity negatively impact XCO performance.

Abbreviations

LOESS: local estimated scatterplot smoothing; PCA: Principal component analysis; UCI: Union Cycliste Internationale; U23: under-23; VO₂max: maximal oxygen uptake; XCO: cross-country cycling.

Power Output and Pacing During International Cross-Country Mountain Bike Cycling

PURPOSE

To characterize the physiological profiles of elite cross-country mountain-bike (XCO-MTB) cyclists and to examine their pacing and power-output (PO) distribution during international races.

METHODS

Over 2 competitive seasons, 8 male XCO-MTB cyclists (VO₂max 79.9 [5.2] mL·min^-1·kg^-1, maximal aerobic power [MAP] 411 [18] W and 6.3 [0.4] W·kg^-1) regularly undertook incremental tests to assess their PO and heart rate (HR) at first and second ventilatory thresholds (VT1 and VT2) and at VO₂max. During the same period, their PO, HR, speed, and cadence were recorded over 13 international races (total of 30 recorded files).

RESULTS

Mean PO, speed, cadence, and HR during the races were 283 (22) W (4.31 [0.32] W·kg^-1, 68% [5%] MAP), 19.7 (2.1) km·h^-1, 68 (8) rpm, and 172 (11) beats·min^-1 (91% [2%] HR_max), respectively. The average times spent below 10% of MAP, between 10% of MAP and VT1, between VT1 and VT2, between VT2 and MAP, and above MAP were 25% (5%), 21% (4%), 13% (3%), 16% (3%), and 26% (5%), respectively. Both speed and PO decreased from the start loop to lap 1 before stabilizing until the end of the race.

CONCLUSIONS

Elite off-road cyclists demonstrated typical values of world-class endurance cyclists with an excellent power-to-mass ratio. This study demonstrated that XCO-MTB races are performed at higher intensities than reported in previous research and are characterized by a fast start followed by an even pace.

Pacing Strategy During Simulated Mountain Bike Racing

Cross-country mountain biking (XCO) is a popular high-intensity endurance cycling event, but XCO pacing strategy has not been fully examined. This study examined the pacing strategies of different XCO athletes during a laboratory-simulated XCO performance test. Brazilian cyclists classified as performance-cohort level 3 performed an XCO race simulation. The simulation consisted of four 10-km laps with a gradient of 0-10%. No group-vs-time interaction was found in lap time (P = .169), absolute (P = .719) and relative (P = .607) power output, ratings of perceived exertion (P = .182), or heart rate (P = .125). There was a time main effect, as athletes decreased power output by 0.3 W/kg throughout the XCO simulation, thereby resulting in a 1.6-min decrement per lap. The power output corresponding to the onset of blood lactate accumulation adequately represented the mean power of the first lap. These results showed that 2 groups of cyclists with different training status adopted similar pacing strategies during an XCO race simulation, as they both used a fast-starting pacing strategy followed by positive pacing that resulted in a linear decrease in power output at every lap.

Predictive ability of a comprehensive incremental test in mountain bike marathon

Objectives

Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands.

Methods

Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data).

Results

All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=−0.72; r=−0.59; r=−0.61), 1 min maximal effort (r=−0.85; r=−0.84; r=−0.82), 5 min maximal effort (r=−0.57; r=−0.85; r=−0.76), PPO (r=−0.77; r=−0.73; r=−0.76) and IAT (r=−0.71; r=−0.67; r=−0.68). The best-fitting multiple regression models for race 3 (r²=0.868) and across all races (r²=0.757) comprised 1 min maximal effort, IAT and body weight.

Conclusion

Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely.

Quantification of brake data acquired with a brake power meter during simulated cross-country mountain bike racing

There is currently a dearth of information describing cycling performance outside of propulsive and physiological variables. The aim of the present study was to utilise a brake power meter to quantify braking during a multi-lap cross-country mountain bike time trial and to determine how braking affects performance. A significant negative association was determined between lap time and brake power (800.8 ± 216.4 W, mean ± SD; r = -0.446; p < 0.05), while the time spent braking (28.0 ± 6.4 s) was positively associated with lap time (314.3 ± 37.9 s; r = 0.477; p < 0.05). Despite propulsive power decreasing after the first lap (p < 0.05), lap time remained unchanged (p > 0.05) which was attributed to decreased brake work (p < 0.05) and brake time (p < 0.05) in both the front and rear brakes by the final lap. A multiple regression model incorporating braking and propulsion was able to explain more of the variance in lap time (r² = 0.935) than propulsion alone (r² = 0.826). The present study highlights that riders' braking contributes to mountain bike performance. As riders repeat a cross-country mountain bike track, they are able to change braking, which in turn can counterbalance a reduction in power output. Further research is required to understand braking better.

A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers

This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO₂max 60.8 ± 6.7 ml · kg^-1 · min^-1) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6-600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R² = 0.92; P < 0.01). This model included VO₂max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R²: 0.62-0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.

The influence of tyre characteristics on measures of rolling performance during cross-country mountain biking

This investigation sets out to assess the effect of five different models of mountain bike tyre on rolling performance over hard-pack mud. Independent characteristics included total weight, volume, tread surface area and tread depth. One male cyclist performed multiple (30) trials of a deceleration field test to assess reliability. Further tests performed on a separate occasion included multiple (15) trials of the deceleration test and six fixed power output hill climb tests for each tyre. The deceleration test proved to be reliable as a means of assessing rolling performance via differences in initial and final speed (coefficient of variation (CV) = 4.52%). Overall differences between tyre performance for both deceleration test (P = 0.014) and hill climb (P = 0.032) were found, enabling significant (P < 0.0001 and P = 0.049) models to be generated, allowing tyre performance prediction based on tyre characteristics. The ideal tyre for rolling and climbing performance on hard-pack surfaces would be to decrease tyre weight by way of reductions in tread surface area and tread depth while keeping volume high.

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.

Mechanical work and physiological responses to simulated cross country mountain bike racing

The purpose was to assess the mechanical work and physiological responses to cross country mountain bike racing. Participants (n = 7) cycled on a cross country track at race speed whilst VO2, power, cadence, speed, and geographical position were recorded. Mean power during the designated start section (68.5 ± 5.5 s) was 481 ± 122 W, incurring an O2 deficit of 1.58 ± 0.67 L - min(-1) highlighting a significant initial anaerobic (32.4 ± 10.2%) contribution. Complete lap data produced mean (243 ± 12 W) and normalised (279 ± 15 W) power outputs with 13.3 ± 6.1 and 20.7 ± 8.3% of time spent in high force-high velocity and high force-low velocity, respectively. This equated to, physiological measures for %VO(2max) (77 ± 5%) and % HR(max) (93 ± 2%). Terrain (uphill vs downhill) significantly (P < 0.05) influenced power output (70.9 ± 7.5 vs. 41.0 ± 9.2% W(max)),the distribution of low velocity force production, VO2 (80 ± 1.7 vs. 72 ± 3.7%) and cadence (76 + 2 vs. 55 ± 4 rpm) but not heart rate (93.8 ± 2.3 vs. 91.3 ± 0.6% HR(max)) and led to a significant difference between anaerobic contribution and terrain (uphill, 6.4 ± 3.0 vs. downhill, 3.2 ± 1.8%, respectively) but not aerobic energy contribution. Both power and cadence were highly variable through all sections resulting in one power surge every 32 s and a supra-maximal effort every 106 s. The results show that cross country mountain bike racing consists of predominantly low velocity pedalling with a large high force component and when combined with a high oscillating work rate, necessitates high aerobic energy provision, with intermittent anaerobic contribution. Additional physical stress during downhill sections affords less recovery emphasised by physiological variables remaining high throughout.