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23 June 2026
Professional road cycling is a sport shaped by performance data. Riders, coaches and performance staff rely on power output analysis daily to monitor progression, understand race demands and optimise preparation. Over the past two decades, power data has become one of the defining metrics of the sport, widely discussed within the peloton and increasingly analysed publicly by teams, experts, media and fans alike.
At the same time, anti-doping programs in cycling have continued to evolve towards increasingly data and intelligence-driven approaches. Biological monitoring through the Athlete Biological Passport, targeted testing strategies, long-term sample storage and advanced analytical techniques have progressively strengthened the ability to protect clean sport through longitudinal and contextual analysis rather than isolated testing alone.
It is within this broader evolution that the ITA has launched a two-year feasibility and pilot study exploring whether power data could contribute as a supplementary source of intelligence for anti-doping purposes in professional road cycling. The project, approved in March 2025 by the Funding Committee of the UCI anti-doping program, aims to assess whether longitudinal performance modelling based on riders’ power data can meaningfully support anti-doping strategies in a scientifically robust and operationally responsible manner.
Importantly, the initiative is a research and feasibility study. Its purpose is not to establish anti-doping rule violations through performance data, but to evaluate whether certain patterns or evolutions in performance may, in the future, help inform areas such as targeted testing strategies, sample retention decisions, additional laboratory analysis or investigations.
Understanding performance evolution over time
The two-year project focuses on the development of longitudinal performance profiles using riders’ race and, subject to scientific validation training data. A central objective of the research is to better understand typical variability in performance over time and across different rider profiles and age groups. Researchers are studying how performance evolves throughout a rider’s career, how race performances relate to training data and how repeated efforts can be analysed in a meaningful and reproducible way despite the many variables inherent to elite cycling.
The work particularly examines what researchers describe as “excess performances”, which represents individual performance trajectory of an athlete adjusted for the average performance of all athletes within the population at the same age as well as any confounders. The model therefore examines the change in an athlete’s performances over time rather than focusing solely on an isolated exceptional performance.
To achieve this, the study evaluates a wide range of factors that influence power data interpretation, including:
The researchers are also analysing how “normal” within-season and between-season performance variation can be characterised across different exercise durations and intensities.
While training data contributes important contextual information, the primary focus of the longitudinal monitoring model is race performance data. Racing provides the most relevant competitive context, while training data can support the interpretation of broader performance trajectories and help contextualise unusual developments when reviewed alongside other information.
The study also seeks to better understand how race performance can be interpreted in light of the many variables inherent to elite cycling, including pacing strategies, rider roles within teams, environmental conditions and the variability between power measuring devices. A key objective of the feasibility phase is to determine whether meaningful longitudinal analysis remains possible despite these influencing factors.
A phased scientific approach
The project is structured in incremental phases over two years. The first year focuses on retrospective analysis using historical rider data to determine whether a meaningful and sufficiently reliable longitudinal monitoring approach can be developed. If the feasibility phase demonstrates that the modelling principles are scientifically and operationally robust, the project would progress into a pilot implementation phase using current season data.
The study is being conducted with riders participating on a voluntary basis and in full compliance with applicable data protection regulations.
Around 60 riders have so far consented to participate in the project across the following teams:
Team Picnic PostNL (UWT)
Team Jayco AlUla (UWT)
Team Visma | Lease a Bike (UWT)
Decathlon AG2R La Mondiale Team (UWT)
Team Cofidis (PRT)
Additional teams, including Uno-X Mobility (UWT), Tudor Pro Cycling Team (PRT) and Team TotalEnergies (PRT), have also approved participation frameworks, with advanced discussions continuing with other teams.
Before participating, riders receive detailed information regarding the project’s objectives, legal basis, data collection and processing methods, data sharing protocols and their rights regarding personal data.
Scientific and ethical oversight
To support the development of the initiative, the ITA established a dedicated Power Data Advisory Panel bringing together expertise from sports science, athlete representation, cycling technology and integrity operations.
The project also benefits from broader expertise and collaboration across the scientific, technological and cycling communities. The project underwent ethical review through the partner university structures and incorporates dedicated data protection safeguards. Data shared with research partners is pseudo anonymised, partner universities access performance data without riders’ identities and the project operates under strict technical and organisational security measures.
Exploring new intelligence tools for clean sport
The project reflects the continued evolution of anti-doping programs towards more integrated and intelligence-led approaches. Cycling has historically played a leading role in the development of longitudinal anti-doping strategies and scientific innovation. The ITA’s power data project seeks to explore whether performance monitoring could, in the future, complement existing anti-doping tools in a sport where performance data already forms a central part of the competitive environment.
“We are constantly looking at how to make the cycling anti-doping program smarter and more effective”, says ITA Director General Benjamin Cohen. “Power data has been part of the conversation in cycling for many years. It is one of the sport’s most widely used performance tools, yet until now its potential contribution to anti-doping has remained largely unexplored. Thanks to the commitment of riders, teams and recognised experts, we now have the opportunity to assess its potential through a structured scientific process and determine whether it can meaningfully complement the anti-doping toolbox in the future.”
As part of the feasibility study, researchers are also taking into account existing scientific literature related to power meter validity, reliability and performance analysis methodologies in cycling. This includes research examining the accuracy and consistency of commercially used power meters, as well as broader methodological considerations surrounding the interpretation of cycling performance data.
The feasibility study aims to assess whether power monitoring can be implemented in a scientifically robust and operationally meaningful manner within the anti-doping framework of men’s professional road cycling.
If validated by the ITA and approved by both the UCI Funding Committee and the UCI Management Committee, the UCI regulations will be amended to require the mandatory sharing to the ITA of individual power data for all professional men’s road riders.
Building on the modelling principles developed through the project, the potential application of this approach could subsequently be considered for UCI Women’s WorldTour and UCI Continental level, as well as extended to other related sports, such as triathlon.
