Study: Perceptions of Cheating and Doping in E-Cycling

A study tries to answer the question of whether people care about cheating

From the abstract:



So the majority of those who were involved in the survey hadn’t experienced cheating, majority rules…

I think this could be an interesting thread :blush:

I’ve been racing on Zwift for nearly 7 years now, and presume that not all peoples results are accurate. I know mine weren’t for the first couple of years, as although I was using a trainer that was meant to be within 5% accuracy, in reality it was giving me a boost of nearer 10%. I wasn’t deliberately cheating, in fact I tried to make it more accurate, but I couldn’t. Eventually I found it too embarrassing and swapped to a direct drive trainer, and since then my Zwift power output has dropped to a more accurate reading, reflecting my outdoor performance.

Although I wouldn’t say that I do not care, I’ve just learned to take results with a pinch of salt. It would seem unlikely that the 60 year old who has a 20 minute pb of 7.5 w/kg while having an ave heart rate of under 100 bpm is an accurate reflection of their ability, but I have no idea whether they are deliberately cheating, or just totally unaware that their figures are inaccurate. I still enjoy racing on Zwift, and hopefully will continue to do so.


To me that is the least useful statistic since in many cases people don’t know if they’ve experienced cheating. But how they feel about the existence of cheating and what they want done about it, those are conclusions I find interesting. A lot of cheating that is not easy for a customer to detect would be easy for Zwift to detect, having full access to the data in real time.

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Could someone define what cheating is please?

Do I think people are using e-bikes or man in middle application - maybe the odd person, but incredibly small numbers.

Do I think there’s a grey area of inaccuracy (power, weight etc) & taking advantage of exploits - I’d say this is a much bigger number - but is it cheating?

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People manipulating their height or weight to gain a performance advantage or game the category system are intentionally cheating. People with shoddy equipment who don’t know about it or can’t afford proper equipment are not cheating, but race quality would improve if they were better detected and directed to support, excluded from results, or excluded from some races (some of this already happens but it could be improved). People who choose over-reporting equipment or manipulate their equipment to gain a performance advantage are intentionally cheating, and some of those manipulations are quite easy, not requiring advanced skills or major investment.


Monkeys and Zwift racers don’t like cheating :smile:

I’m just thinking, research is just as good as the study is executed (ChatGPT):

  1. Sampling Bias: The study recruited participants through social networking sites and online forums, which may have resulted in a biased sample of individuals who are more active and engaged in e-cycling. This could limit the generalizability of the findings to the broader e-cycling population.
  2. Self-Reporting Bias: The study relied on self-reported data, which is subject to biases such as social desirability bias and recall bias. Participants may have provided inaccurate or incomplete information, particularly when reporting their experiences of cheating or doping.
  3. Lack of Validated Questionnaire: The questionnaire used in the study was not based on a validated design. This may affect the reliability and validity of the data collected, as the questions may not have accurately captured the participants’ experiences and perceptions.
  4. Limited Scope of Questions: The study focused primarily on perceptions of cheating and doping in e-cycling, without exploring other factors that may contribute to these behaviors, such as motivations, social influences, or organizational factors. This narrow focus may limit the understanding of the complex dynamics surrounding cheating and doping in e-cycling.
  5. Lack of Control Group: The study did not include a control group of non-e-cyclists or traditional cyclists for comparison. This makes it difficult to determine if the prevalence and perceptions of cheating and doping in e-cycling differ significantly from other cycling disciplines.
  6. Potential Confounding Factors: The study did not account for potential confounding factors that may influence participants’ perceptions and behaviors, such as prior experiences in traditional cycling, competitive level, or cultural differences. These factors could impact the interpretation of the results.
  7. Limited Ethical Considerations: The study briefly mentions obtaining ethical approval from the university’s ethics committee, but it does not provide detailed information on informed consent procedures, participant confidentiality, or potential risks associated with participation.
  8. Lack of Longitudinal Design: The study employed a cross-sectional design, which only provides a snapshot of participants’ experiences and perceptions at a specific point in time. A longitudinal design would have allowed for a better understanding of changes in perceptions and behaviors over time.
  9. Limited Recommendations: While the study briefly mentions recommendations for improving anti-doping policies in e-cycling, it does not provide a comprehensive analysis or discussion of these recommendations. Further elaboration and justification for the proposed recommendations would strengthen the study’s conclusions.
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I consider 4th place a win on Zwift because the first 3 are probably cheating, not necessarily intentionally tho

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40 percent reported they didn’t experience cheating. The others were those that had not e-raced-4% and 11% picked “unaware or don’t know”. A slim majority experienced cheating.

Christopher, when I was at school 100-40=60 and 60 is is larger than 40 and therefore the majority

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I can’t argue with that logic, Martin. However, all of the respondents didn’t answer the question yes or no, some picked other choices. Of the individuals that responded yes or no, 44% said they experienced cheating in ecycling and 40 percent said they didn’t.

1 in 20 purposefully mis represent their height or weight to gain an advantage. Basically someone in every race is trying to cheat at those numbers

I take purposefully misrepresenting as more than just didnt update it as it is regularly within the same ball park figure.

There is a probably a can of worms that esports will likely never get on top of and that is things like testosterone replacement & boosting prescriptions etc From all accounts, its becoming quite a challenge in the elite end of age group triathlon and other sports within limited testing.

@Christopher_Schwenke , this is the trouble with statistics, I was once told that statistics is the art of making figures say what you want them to

To me the important questions are whether the current level of cheating is significant, whether more should be done about it, and what can be done at reasonable expense to improve the integrity of races.

We don’t need to reach a majority of racers experiencing cheating in order to say that the current level of cheating is significant, just like you would not want to reach a point where a majority of people in your town have experienced robbery before deciding to take more actions to prevent or detect it, as well as engaging with the community to talk about how to respond.



I is like saying only 40% of people that got sick from the food at the restaurant so the restaurant is good to go to, don’t worry it is save, most people don’t get sick.

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Since I don’t participate in races it’s impossible for me to say whether cheating is too much on Zwift.

However on a more general note, having a game where the equipment can easily be off by +/- 50% (or more), where you can cheat in races by simply setting a number in a menu (your weight) and where both your HR and power numbers can be altered by downloading a mod on the dark (or light) web, will surely attract the types who wants to do that.

God (or Allah or Jahve or whatever) knows why people wants to cheat, but all competitive games have cheaters and the easier it is to cheat, the more cheaters there will be.

From all other competitive games it can also be seen that the amount of cheaters greatly affects how people see the relevance of the competitive part of the game.

For me I have to be completely honest and say that racing simply does not make sense. I don’t get the urge to win a random race where someone has picked a random cutoff (W/kg) for who can participate; especially when that cutoff can be so easily changed. Someone is always better than you, so if you get on the podium it’s just because these other people were not in the race… It would be interesting to get stats from Zwift to see how many are just at the border of the cut-off for the different races.

I guess I could see one reason for races, to get all-out numbers for your current form.

Can Zwift do anything about cheating? I highly doubt it… I guess you could limit the amount of change per week on your weight. That however has a lot of issues.

Other games have various forms of cheat-detection. Some of these could be employed on Zwift as well (such as detecting known cheat programs running on the same hardware as the game client), but since the actual power and HR numbers are typically transmitted over BT it is impossible to detect cheaters who really wants. And weight cheating is in any case also completely impossible to detect (unless it is severe of course).

This it what people who don’t know statistics tell others, yes…

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They absolutely can do “anything” about cheating. They can’t solve every problem, and some would be expensive to solve, but many trivial exploits are known and there are reasonable solutions for some of them. Currently the discussion of those details is largely pointless due to the lack of engagement.

Maybe, I don’t know any trivial exploits, except weight manipulation, which is easy to do but impossible to do anything about (again: except in severe cases). That alone means all other complex exploits are not really that relevant.

It would take me a day or two to write a program which could simulate a trainer and a HR over bluetooth; maybe a day more to add realistic data for power/cadence/HR. Compared to other cheats in other games that rely on artifical intelligence and fast image detection, this is nothing. And again: Zwift can’t do anything (read: much) about it.