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zwiftdynamics.com

Introduction

The specific details of the underlying (differential) modeling equations used in Zwift's software are not publicly disclosed. However, we can make some general assumptions about the mathematical models that could be utilized to simulate the cycling dynamics in the virtual world. Please note that these assumptions are speculative and may not reflect the exact equations employed by Zwift.

Sticky draft in Zwift

The sticky draft effect in Zwift has been a subject of discussion and feedback from users. It often arises when drafting dynamics are influenced by the virtual environment and the limitations of the platform's physics modeling. Some riders have reported that they experience a stronger drafting effect or find it more challenging to break away from a group due to the sticky draft.
The precise mechanics behind the sticky draft in Zwift are not publicly disclosed by the company, so the specific factors that contribute to this phenomenon are not known. It could be a result of simplifications or limitations in the drafting algorithm or the modeling of air resistance and rider interactions within the virtual environment.

A possible way to determine the modelling approach of Zwift's draft model

Determining exactly how Zwift models the draft in a scientifically accurate way would require access to proprietary information and detailed insight into Zwift's software and algorithms, which are not publicly available. To gain scientific insights into Zwift's drafting model, it would typically need to conduct independent studies and experiments. Here's a general approach that I have taken to investigate and analyze the drafting mechanics in Zwift:

1. Literature Review: Conduct a comprehensive review of existing scientific literature on drafting in real-world cycling. This would involve studying research papers, journal articles, and books that discuss the aerodynamics, fluid dynamics, and physiological aspects of drafting.


2. Data Collection: Design and execute experiments in both real-world and Zwift environments to collect data on drafting dynamics. This could involve measuring variables such as velocity, power output, distance, and wind conditions. It's important to ensure that the experiments are conducted with a sufficiently large sample size and under known conditions.


3. Analysis and Comparison: Analyze the collected data and compare the results between measured and Zwift's virtual values. Assess whether Zwift's drafting model aligns with the expected real-world principles and quantify any discrepancies or variations.


4. Publication: Document the research findings, methodology, and analysis, which can be found on the next sites here.

Conducting scientific research on Zwift's drafting model would require expertise in the fields of aerodynamics, fluid dynamics, and data analysis.

Motivation

This analysis aimed to investigate and analyze Zwift's drafting mechanics by comparing the velocity outputs from Zwift activities to the predictions of established literature models. The study focused on adapting the draft coefficient and mass in the staandard literature models to achieve a better fit between the simulated velocity out of Zwift and the velocity derived from the literature models. Through iterative adjustments, the research findings revealed the necessity of modifying these parameters to align Zwift's result outputs more accurately with the predictions of the literature models.
To investigate Zwift's drafting mechanics, we conducted multiple Zwift activities and recorded relevant data, including velocity, power output, and distance. We then compared the observed velocity outputs from Zwift activities to the expected velocity outputs derived from established literature models that consider factors such as air density, frontal area, and drafting effects.

Results

The analysis demonstrated significant deviations between the observed velocity outputs in Zwift activities and the predicted velocity outputs from the literature models. To achieve a better fit, it was necessary to adapt the draft coefficient and mass parameters in the standard literature model. Through iterative adjustments, we found that the draft coefficient and the mass aren't constant and needs to be adaptes to achieve velocity outputs that were more consistent with the values of the Zwift acitivity. These adaptations allowed for a better alignment between the simulated velocity in Zwift and the expected velocity based on the established principles of drafting.

Conclusion

The investigation revealed the need of adapting the draft coefficient and mass in standard literature model to achieve better alignment with velocity outputs derived from Zwift. By iteratively adjusting these parameters, we were able to improve the accuracy of simulated velocity, bringing it closer to the values out of a Zwift acitivity. The investigation into Zwift's drafting mechanics has revealed that Zwift modifies the drag coefficient frequently during an activity.

Investigation results:

Click on an activity number to see the detailed results