Individual Time Trial Research Articles

The Effect of Cycling Exercises in Some Biochemical Elements and Achievement in Individual Time Trial for Elite Men Cyclist’s

The Effect of Cycling Exercises in Some Biochemical Elements and Achievement in Individual Time Trial for Elite Men Cyclist’s

How much can roof-mounted bicycles on a following team car reduce cyclist drag?

Earlier research demonstrated that a car following a cyclist can provide an aerodynamic benefit to this cyclist. This effect could be large enough to potentially influence the outcome of individual time trials. This incited the International Cycling Union (UCI) in 2023 to raise the minimum distance from 10 to 25 m. However, this previous research work did not consider the bicycles typically mounted on the roof of a team car. Indeed, some teams have mounted up to ten bicycles on the roof, possibly in an attempt to optimise the aerodynamic benefit by their team car, even in individual time trials. This study employs CFD simulations validated by wind tunnel measurements to assess the benefit provided by different rooftop bicycle configurations. It is shown that the extra benefits are substantial and extend up to a distance of at least 25 m between cyclist and car, which could trigger new rules by the UCI. This study also shows that the cyclist drag reduction by a following car and for any car-cyclist separation distance d, can be estimated by the static pressure coefficient at position d in front of the isolated car, which can be obtained by a single CFD simulation.

Performance and micro-pacing in sprint cross-country skiing: A comparison of individual time-trial and head-to-head race formats

ABSTRACT This study compared performance strategies and sub-technique selection in cross-country skate skiing sprint races, specifically individual time-trial (ITT) and head-to-head (H2H) formats. Fourteen male cross-country skiers from the Chinese national team participated in the FIS-sanctioned sprint race day. GNSS and heart rate sensors recorded positioning, skiing speeds, heart rate, sub-technique usage, and skiing kinematics. Statistical parametric mapping (SPM) was used to determine the course positions (clusters) where instantaneous skiing speed was significantly associated with section time. One-way analyses of variance were used to examine differences between the ITT and H2H. H2H race speeds were 2.4 ± 0.2% faster than the ITT race (p < 0.05).Variations in sub-technique and skiing kinematics were observed between race formats, indicating different strategies and tactics employed by athletes. SPM identified specific clusters (primarily uphill) where the fastest athlete gained significant time over the slowest. The greatest time gains were associated with higher G3 sub-technique usage and longer G3 cycle length on steep uphill terrain (9–13% gradients). Integrating SPM analyses and sub-technique assessments can help optimise performance and tactics in sprint races. This study enhances our understanding of cross-country skiing dynamics and performance variations among elite competitors.

Performance-Determining Variables of a Simulated Skimo Sprint Competition in Elite Junior Skimo Athletes

This study aimed to investigate the variables determining performance in a simulated on-snow Skimo sprint competition, and how their relationship with performance evolves from the individual time trial to the final. Fifteen national-level junior Skimo athletes (mean ± SD: age, 17.8 ± 2.5 years; maximal oxygen uptake, 66.8 mL·kg−1·min−1) underwent a comprehensive assessment, involving submaximal and maximal endurance tests, maximal strength assessments, and a maximal sprint to determine maximal glycolytic capacity. Subsequently, a simulated sprint competition, comprising an individual time-trial and three heats (quarterfinal, semifinal, final), was conducted. Whole-body and upper body aerobic power (r = 0.69–0.93), maximal speed and power (r = 0.82–0.85) during the maximal performance test, as well as fat-free mass (r = 0.62–0.77) and body fat (r = −0.67–−0.77), exhibited significant correlations with performance in the time-trial, quarterfinal and semifinal. Moreover, maximal strength (r = 0.39–0.95) and transition duration (r = 0.52–0.85) showed moderate to large correlations with sprint performance. Overall, aerobic power, maximal speed and power, as well as fat-free mass, and body fat emerged as crucial determinants of Skimo sprint performance, while dynamic strength and the ability to transition quickly between sections also proved to be relevant factors.

Performance-Determining Variables of a Simulated Sprint Cross-Country Skiing Competition.

To investigate performance-determining variables of an on-snow sprint cross-country skiing competition and the evolvement in their relationship with performance as the competition progresses from the individual time trial (TT) to the final. Sixteen national-level male junior skiers (mean [SD] age, 18.6 [0.8]y; peak oxygen uptake [VO2peak], 67.6 [5.5]mL·min-1·kg-1) performed a simulated sprint competition (1.3km) in the skating style, comprising a TT followed by 3 finals (quarterfinals, semifinals, and final) completed by all skiers. In addition, submaximal and incremental roller-ski treadmill tests, on-snow maximal speed tests, and strength/power tests were performed. VO2peak and peak treadmill speed during incremental testing and relative heart rate, rating of perceived exertion, blood lactate concentrations, and gross efficiency during submaximal testing were all significantly correlated with performance in the TT and subsequent finals (mean [range] r values: .67 [.53-.86], all P < .05). Relative VO2peak and submaximal relative heart rate and blood lactate concentration were more strongly correlated with performance in the semifinals and final compared with the TT (r values: .74 [.60-.83] vs 0.55 [.51-.60], all P < .05). Maximal speed in uphill and flat terrain was significantly correlated with performance in the TT and subsequent finals (r values: .63 [.38-.70], all P < .05), while strength/power tests did not correlate significantly with sprint performance. VO2peak and high-speed abilities were the most important determinants of sprint cross-country skiing performance, with an increased importance of VO2peak as the competition format progressed toward the final.

The effect of normobaric hypoxia on acute exercise-induced changes in blood sphingoid base-1-phosphates metabolism in cyclists.

Extracellular sphingosine-1-phosphate (S1P) emerged as an important regulator of muscle function. We previously found that plasma S1P concentration is elevated in response to acute exercise and training. Interestingly, hypoxia, which is commonly utilized in training programs, induces a similar effect. Therefore, the aim of the current study was to determine the effect of normobaric hypoxia on exercise-induced changes in blood sphingolipid metabolism. Fifteen male competitive cyclists performed a graded cycling exercise until exhaustion (GE) and a simulated 30 km individual time trial (TT) in either normoxic or hypoxic (FiO2 = 16.5%) conditions. Blood samples were taken before the exercise, following its cessation, and after 30 min of recovery. We found that TT increased dihydrosphingosine-1-phosphate (dhS1P) concentration in plasma (both HDL- and albumin-bound) and blood cells, as well as the rate of dhS1P release from erythrocytes, regardless of oxygen availability. Plasma concentration of S1P was, however, reduced during the recovery phase, and this trend was augmented by hypoxia. On the other hand, GE in normoxia induced a selective increase in HDL-bound S1P. This effect disappeared when the exercise was performed in hypoxia, and it was associated with reduced S1P level in platelets and erythrocytes. We conclude that submaximal exercise elevates total plasma dhS1P concentration via increased availability of dihydrosphingosine resulting in enhanced dhS1P synthesis and release by blood cells. Maximal exercise, on the other hand, induces a selective increase in HDL-bound S1P, which is a consequence of mechanisms not related to blood cells. We also conclude that hypoxia reduces post-exercise plasma S1P concentration.

Comprehensive analysis of performance, physiological, and perceptual responses during an entire sprint cross-country skiingcompetition.

To investigate performance, physiological, and perceptual responses of an entire sprint cross-country skiing competition in the skating style. Eighteen national-level male junior skiers participated in a simulated competition comprising an individual time trial (TT), followed by three heats (quarterfinals [QF], semifinals [SF], and final [F]). Participants' heart rate (HR) was continuously monitored while perceived readiness (RED, 1-10), rating of perceived exertion (RPE, 6-20), and blood lactate [La-] were assessed at standardized time points. The total duration and distance covered were 03:30 ± 00:06h and 25.2 ± 2.9km, respectively. The participants spent 02:19 ± 00:27h > 60% of their maximal HR (HRmax) and 00:16 ± 00:04h > 85% of HRmax. Average HR decreased from TT to F (89.3 ± 2.0% vs. 86.9 ± 3.0% of HRmax, P < 0.01). [La-] levels were highest before (4.6 ± 2.0 vs. 2.9 ± 1.2, 3.2 ± 2.0 and 2.5 ± 1.3mmol·L-1, all P < 0.01) and after (10.8 ± 1.4 vs. 9.8 ± 1.6, 9.1 ± 1.8 and 8.7 ± 1.7mmol·L-1, all P < 0.05) F compared to TT, QF, and SF, respectively. RED was lowest before F compared to TT, QF, and SF (6.6 ± 1.4 vs. 7.9 ± 1.1, 7.6 ± 1.1, and 7.4 ± 1.4, respectively, all P < 0.05) while RPE was highest after TT compared to QF, SF, and F (17.8 ± 0.9 vs. 15.1 ± 2.0, 16.5 ± 1.2 and 16.6 ± 1.8, respectively, all P < 0.01). The six best-performing skiers demonstrated higher RED before F (7.2 ± 0.9 vs. 5.3 ± 1.2, P < 0.05) and higher [La-] after F (11.2 ± 0.2 vs. 10.2 ± 0.3, mmol·L-1, P < 0.05) than lower-performing competitors. This study provides novel insights into physiological demands of an entire sprint cross-country skiing competition, which involves repeated 3-min high-intensity efforts interspersed with > 2h (25 km) of low- to moderate-intensity exercise.

Riding Scheme Based on Fraction-weight Model

The difference of 0.01s is enough to decide the winner of a race. To push oneself to the limit through training is the meaning of sports, and to seize every second by helping athletes polish details and optimize tactics is the meaning of modern sports technology. This is evident in the Individual Time Trial (ITT), a race that focuses on tactics and details. In order to help riders achieve better results, it have created optimization methods for each type of rider and course, taking into account energy reserves (stamina), rider power and course conditions. So, several models are developed in this paper: scoring weighted regression model and energy-power model based on Skiba model.

Power Diagrams and Rules of Cyclists in Road Cycling

Road cycling time trials have a long history in all sports, and the individual time trial is one of the most important events in road cycling time trials. Due to the long distance, complex sections, and uncertain natural environment of road cycling individual time trials, in addition to the performance of the bicycle itself, the rider’s ability and physical ability, the athlete’s planning of the ride during the distance is also an important factor affecting the performance of this sport. Therefore, it is important to create a model that can facilitate cyclists’ planning decisions for cy- cling. In constructing the initial model, we compared the training and competition data of cyclists with other types of athletes by referring to various literature to find commonalities and individ- ualities between road cycling time trials and other sports, thereby refining the data, and finally determined a power curve model related to power functions using knowledge of ordinary differ- ential equations and fitting.The model can infer the instantaneous power from the rider’s riding time, and when combined with the external force data such as wind and gravity, the rider’s kinetic energy can be derived. The model also incorporates the fact that the total energy of the rider is limited, which guarantees the feasibility and reasonableness of the model

Interchangeability between the Data Obtained by Two Powermeters during Road Cycling Competitions: A Case Study

Various power meters are used to assess road-cycling performance in training and competition, but no previous study has analyzed their interchangeability in these conditions. Therefore, the purpose was to compare the data obtained from two different power meters (PowerTap vs. Power2Max) during cycling road races. A national-level under-23 male competitive cyclist completed six road-cycling official competitions (five road races and one individual time trial), in which power output was simultaneously registered with the two power meters. After this, the main power output variables were analyzed with the same software. The average and critical power obtained from the PowerTap power meter were slightly lower than from the Power2Max power meter (3.56 ± 0.68 and 3.62 ± 0.74 W·kg-1, 5.06 and 5.11 W·kg-1, respectively), and the correlations between both devices were very high (r ≥ 0.996 and p < 0.001). In contrast, the PowerTap power meter registered a significantly higher (p < 0.05) percentage of time at <0.75 and >7.50 W·kg-1 and power profile at 1, 5 and 10 s. In conclusion, the data obtained in competitions by the two power meters were interchangeable. Nevertheless, the Power2Max power meter underestimated the pedaling power during short and high-intensity intervals (≤10.0 s and >7.50 W·kg-1) compared to the PowerTap power meter. Therefore, the analysis of these efforts should be treated with caution.

Research on the Optimal Strength Curve of Athletes Based on EVP Model

As one of the world's favorite extreme sports, bicycle racing gives people a physical workout and is in line with today's global community's advocacy of low carbon. The individual time trial and team time trial in bicycle racing is a great challenge for athletes. In this sport, different athletes have different power curves, and athletes have to adjust their power curves according to the actual situation during the ride. And when and where athletes adjust their power usually determines whether they can win the race or not. Therefore, in order to find the best power adjustment strategy, we build a mathematical model for determining the relationship between rider's position on the track and rider's power, as well as the power profiles of athletes on specific tracks, and try to apply it on any type of riders.

Research on Bicycle Road Time Trial Based on Differential Equation

Bicycle road time trial is a kind of bicycle road race, including individual time trial and team time trial. The purpose of this paper is to build a power prediction model to provide the rider with an optimal power distribution strategy according to the characteristics of the track and the rider's abilities. We first analyze the energy conversion problem in the speed direction of the system composed of bicycles and people. In order to extend our model, we get the distance as a function of time. Calculate the performance of each type of rider on the two tracks, and find that the relative error of the results is about 10%, which proves that the establishment of our model is effective. Afterwards the model was applied to the track we designed, and the results were reasonable by comparing the data. Further, we consider the influence of wind speed in combination with the actual situation, to optimize our model so that the results are more accurate, and the relative error is within 5%.

Research on the Factors Influencing the Strength of Cyclists

Individual Time Trial (ITT) is a road bicycle race where cyclists race alone against the clock. To minimize the total time cost, cyclists need to focus on the output power. In this paper, we develop models to analyze the output power of cyclists determine how to adjust the output power at every position of the course. Firstly, this article collects the real data of cyclists, which is used to find the power profile related to power and duration. Reasonable expressions of different types of cyclists of different gender are also concluded. Secondly, this article considers the cyclists in competition as a constantly charged battery and discharged. FTP is the power at which cyclists can work steadily for a long time. Therefore, this article uses FTP to represent the recovery rate of cyclists approximately. There is two basis of our model. First, maintaining a steady speed is the key to reducing the total time loss in the time trial. The next basis of our model is to divide the course into three types: uphill, downhill, and sharp turn and do the force analysis. Then, this article builds up a model which tells the cyclists how to adjust output power in the whole time trial. Fatigue is also considered in our model. the model applies to two real Individual Time Trials and one course designed by us and draws the power-distance curve correspondingly. Finally, this article analyzes the potential impact of the wind. The wind will affect the cyclists' air resistance fA. The time cost at every part is calculated to determine the proposed model's accuracy. This article also analyzes the impact of improper power adjustment.

Optimal pacing strategy modeling of cycling individual time trials

Improving the performance of professional cyclists during individual time trials has been a challenge for several decades. In this study, the fatigue power profiles of male and female professional cyclists were characterized and a novel optimal pacing strategy model was established to determine the output power distribution based on the simulated annealing algorithm. Moreover, the model was implemented on the male 2021 UCI ITT course and the female 2021 Olympic ITT course. Compared with the actual performance of the professional cyclists, the race scores predicted by this model are among the best, which indicates that the model is highly practical and instructive. Considering riders are unlikely to follow the detailed plan exactly and their output power can deviate from the optimal power, a sensitivity analysis was conducted and the results demonstrated the high stability and reliability of the model.

Characteristics of Pacing Strategies among Elite Cross-Country Skiers According to Final Rank.

The purpose of this study is to explore differences in pacing strategies between successful and less successful male elite cross-country skiers during a 15 km interval-start race involving different techniques. The final rank, split times and final times were extracted individually for the top 100 finishers in the 15 km individual time trial races from the Norwegian national season opener races over two years. The same course was used in all the competitions. The athletes were divided into four groups according to final rank: Q1: 1st–25th; Q2: 26th–50th; Q3: 51st–75th; Q4: 76th–100th. The relative change in speed was used for the time spent on lap 1, to an average for laps 2 and 3. Significant correlation between placement and speed reduction after the first lap was found in three out of four races. In Race 2 (skating), both Q1 and Q2 had lower speed decreases between laps than Q4 did. In year 2, both races (classical and skating) had lower speed reduction between laps for the first quartile compared to that of the last. Overall, this study shows that lower-level cross-country skiers started out relatively faster in the first lap and achieved a greater reduction in speed in the subsequent laps when compared to their faster opponents.

Effect of Normobaric Hypoxia on Alterations in Redox Homeostasis, Nitrosative Stress, Inflammation, and Lysosomal Function following Acute Physical Exercise.

Hypoxia is a recognized inducer of oxidative stress during prolonged physical activity. Nevertheless, previous studies have not systematically examined the effects of normoxia and hypoxia during acute physical exercise. The study is aimed at evaluating the relationship between enzymatic and nonenzymatic antioxidant barrier, total antioxidant/oxidant status, oxidative and nitrosative damage, inflammation, and lysosomal function in different acute exercise protocols under normoxia and hypoxia. Fifteen competitive athletes were recruited for the study. They were subjected to two types of acute cycling exercise with different intensities and durations: graded exercise until exhaustion (GE) and simulated 30 km individual time trial (TT). Both exercise protocols were performed under normoxic and hypoxic (FiO2 = 16.5%) conditions. The number of subjects was determined based on our previous experiment, assuming the test power = 0.8 and α = 0.05. We demonstrated enhanced enzymatic antioxidant systems during hypoxic exercise (GE: ↑ catalase (CAT), ↑ superoxide dismutase; TT: ↑ CAT) with a concomitant decrease in plasma reduced glutathione. In athletes exercising in hypoxia, redox status was shifted in favor of oxidation reactions (GE: ↑ total oxidant status, ↓ redox ratio), leading to increased oxidation/nitration of proteins (GE: ↑ advanced oxidation protein products (AOPP), ↑ ischemia-modified albumin, ↑ 3-nitrotyrosine, ↑ S-nitrosothiols; TT: ↑ AOPP) and lipids (GE: ↑ malondialdehyde). Concentrations of nitric oxide and its metabolites (peroxynitrite) were significantly higher in the plasma of hypoxic exercisers with an associated increase in inflammatory mediators (GE: ↑ myeloperoxidase, ↑ tumor necrosis factor-alpha) and lysosomal exoglycosidase activity (GE: ↑ N-acetyl-β-hexosaminidase, ↑ β-glucuronidase). Our study indicates that even a single intensive exercise session disrupts the antioxidant barrier and leads to increased oxidative and nitrosative damage at the systemic level. High-intensity exercise until exhaustion (GE) alters redox homeostasis more than the less intense exercise (TT, near the anaerobic threshold) of longer duration (20.2 ± 1.9 min vs. 61.1 ± 5.4 min—normoxia; 18.0 ± 1.9 min vs. 63.7 ± 3.0 min—hypoxia), while hypoxia significantly exacerbates oxidative stress, inflammation, and lysosomal dysfunction in athletic subjects.

Association of Heart Rate Variability and Simulated Cycling Time Trial Performance

The aim of this study was to determine if an abnormal HRV status would have negative effects on simulated individual time trial (ITT) performance in recreational cyclists. Recreational male (n=23, 42.8±8.3 years, 78.0±11.0 kg) and female (n=2, 37.0±6.8 years, 68.0±4.4 kg) cyclists completed simulated indoor 40-minute ITTs (40TT) over ten weeks. Participants were asked to complete simulated 40TTs under two HRV conditions: HRV normal values and HRV abnormal values. Participants recorded daily morning HRV readings to determine HRV status. Each participant performed all 40TTs on their personal indoor bike trainer and bike without external race simulation (e.g., Zwift). All cycling performance data were recorded on personal bike computers and submitted via a Qualtrics survey. A total of 138 ITTs (Normal = 75; Abnormal = 63) were assessed for relationships between HRV status and performance outcomes using a linear mixed-effects model with Cohen’s D for effect sizes (ES). A significant main effect of HRV status was found for peak power (F = 6.61; Normal: 372 ± 121.5 watts; Abnormal: 349 ± 105.9 watts; 380; p = 0.01; ES = 0.20) and peak speed (F = 6.12; Normal = 10.8 ± 1.2 m/s; Abnormal: 10.4 ± 1.2 m/s; p = 0.02; ES = 0.33). No significant main effect or effect sizes exceeding 0.20 were observed for all other performance variables. Daily HRV monitoring provides valuable insight that an individual’s peak power and speed may be compromised during cycling performance despite no changes in physiological or psychological indicators of effort. Coaches and cyclists can use morning HRV to inform race strategy ensuring desired performance outcomes, especially for those who rely on high power outputs

Solution of Speed Policy Model Based on Genetic Algorithm

Cycling Road races are divided into standard time trials, team time trials and individual time trials, which pose a great challenge to the physical fitness of cyclists. In this paper, the power curve model and speed adjustment strategy model are established, and the genetic algorithm method is used to formulate competition strategies for different tracks and different players. The research on this issue can provide guidance for cyclists and help them achieve better results.In order to determine the relationship between the driver’s position on the track and the driver’s strength, this paper establishes a speed adjustment strategy model according to the force analysis. It is essentially a single-objective optimization model. Combining these two models provides runners with instruction in road cycling competitions.In this paper, the genetic algorithm is used to solve the model, and comprehensively considers other factors such as weather and player psychology.

Simulation and Optimization Model of Bicycle Time Trial Based on Genetic Algorithm

We have established a simulation optimization model of bicycle time trial based on genetic algorithm. By using the algorithm, we can not only get the best force of different sections, but also get personalized analysis of different players. These two sets of data can directly help us find the shortest time for a particular rider to finish a particular race. In this paper, we expanded the model biased towards the six-person team time trial, and successfully combined the genetic algorithm to find out the best time duration and the best order for everyone in the team to break the wind. First of all, we built a basic physical simulation model of bicycle individual time trial. The two resistances can be obtained by the basic laws of physics. Then we consider different terrain factors. Based on this, we also built the corresponding topographic map in combination with the actual road conditions. Finally, we consider the physical strength change of the players, and establish a dynamic physical strength change model combined with related papers. After building the basic physical model, we first need to consider the riding ability of a rider. In order to quantitatively describe how much power players should use in different places, we introduce the road cognition coefficient and terrain difficulty degree. Therefore, an optimal power table of a specific rider for a specific track is obtained.

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

ABSTRACT 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 hypothesised that a larger area was associated with 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.