Applied Race Intelligence
From observed behaviour to insight
Real race analysis designed to understand product adoption, athlete behaviour and the commercial dynamics of an event. The data is real; the event is published anonymised.
On this page
- What competition reveals about product adoption
- From race-day presence to commercial opportunity
- Participant profile at a multi-format event
The brands shown form part of the data observed in competition. Observed in competition · Event anonymised · 2026
Brand Intelligence
What competition reveals about product adoption
European half marathon · 2026 · Event anonymised
Across 28,875 analysed participants, the analysis works through four questions: where each brand stands on race day, who uses it, which products explain that presence and which product connects with which consumer.
Question
Where does the brand stand on race day?
Competition Share across 28,875 analysed participants — usage observed on race day, not national market share or retail sell-through.
No brand holds more than a quarter of the field: real competition is more evenly split than brand perception suggests.
Question
Who is using the brand?
Observed share of the leading brand by age band, calculated on the same analysed base.
Ten percentage points separate the youngest segment from the oldest. The headline share of 23.1% hides that difference entirely.
Question
Which products drive its presence?
Distribution of observed usage within the leading brand's portfolio.
Two models account for 62% of the brand's observed usage. The performance range dominates daily training, which reaches only 6%.
Question
Which product connects with which consumer?
The Affinity Index compares a product's representation within a segment against the event's own benchmark. Above 1.0x, the product is over-represented in that segment.
Product
Supernova Rise 2
Consumer
57% women
Event benchmark
40% women
Female Affinity Index
1.43x
A portfolio that looks uniform at headline-share level contains one product clearly oriented towards the female consumer.
Question
How does product usage change with performance?
Median finish time among the runners observed in each model.
Adizero Adios Pro 4 shows the highest performance profile in the portfolio analysed, with a median of 1h32. There are 44 minutes between that model and Ultraboost Light: one catalogue covers very different competitive levels.
Decision
From data to decision
Analytical implications supported by the data. We make no claim that the brand has acted on any of them.
Performance positioning
Two high-end models account for 62% of observed usage: race-day presence rests on performance product, not on daily training product.
Portfolio strategy
The daily training model reaches only 6% of observed usage within the brand itself.
Female consumer opportunity
An Affinity Index of 1.43x marks a product with measurable female connection above the event benchmark.
Penetration in the 45+ segment
Share falls from 27.2% to 16.8% between the youngest and the oldest segment.
Methodology
How this analysis was built
Footwear detection by computer vision at several control points, connected with the authorised race record (age, sex, finish time). The brands and models shown form part of the data observed in competition. The event is published anonymised, with every figure calculated on a stated base.
Event Intelligence
From race-day presence to commercial opportunity
European half marathon · 2026 · Event anonymised
The same race-day observation, read from the organiser's perspective: who competes, which products are used, how much real adoption the sponsor asset has and which brands already hold a community inside the event.
Event Profile
Who actually competes at the event?
Observed profile built on the authorised race record, rather than generic audience estimates.
31,045
Finishers
28,875
Participants analysed
93%
Detection coverage
40%
Women
93
Nationalities
40%
International participation
28,875 of 31,045 finishers analysed: a large-scale event with substantial international participation, described through a specific, verifiable profile instead of generic audience estimates.
Product Landscape
Which products are used inside the event?
Observed product presence across the footwear identified on race day.
39.2%
The ten most present models account for 39.2% of all observed product
The remainder spreads across a long tail of minority models: the race concentrates demand in very few products. This is observed product usage, not advertising visibility.
Sponsor Asset Adoption
How much real adoption does the sponsor asset have?
Sponsor Asset Adoption: observed use of the official shirt carrying the sponsor logo. It is not advertising reach, impressions or audience exposure.
38%
of finishers
11,797
Identified wearers
37
Median age, wearers
60%
Wearers aged 25 to 44
The organiser can document not only how many runners wore the official asset, but also the profile of those wearers.
Organic Brand Demand
Which brands already hold a community inside the event?
Organic Brand Demand identifies which brands already hold a meaningful community inside the event, before any commercial conversation begins.
65.9%
of the analysed field — 19,029 runners — sits with four high-presence brands identified as commercially relevant
The analysis shows which brands hold a meaningful community inside the event, and turns that evidence into a way to prioritise commercial conversations — measured before any agreement exists.
The contractual status between any observed brand and the organiser is not published without explicit authorisation.
Commercial Application
From observation to commercial conversation
The organiser receives an aggregated report covering the participant profile, the product landscape, real sponsor asset adoption and the brands with organic demand already present — the evidence on which to build or renew agreements, without estimating their financial value.
Event Intelligence
Participant profile at a multi-format event
Multi-format city event · Spain · 2026 · Event anonymised
A separate real analysis, completed earlier by Eyerace, at the same level of detail every organiser receives. It stands as an independent case — it is not combined with the anonymised European event above.
01 · Context
Multi-format city event · Spain · 2026
Marathon, half marathon, 10K and relay on the same day. 3,500 registered runners and 3,180 finishers, with 5 control points along the course.
02 · Business question
Who are the participants and what do they use?
The organiser needed to describe its participants with observed data — not only with registration volume — and to document the presence of its main sponsor to support the renewal conversation.
03 · Deployment
5 camera control points
Industrial IP cameras rented for this edition, placed at the start, at intermediate sections and at the finish line, without altering the course or the runner experience.
04 · Methodology
Race record plus bib and footwear detection
Every detection is connected with the authorised race record (bib, age, sex, category and time). Detected product is classified by brand and model using computer vision, with a confidence review at each control point.
05 · Coverage
94% detection coverage
2,989 participants analysed out of 3,180 finishers (94% detection coverage). The remaining 6% covers bibs that were not legible or camera angles with no valid detection.
06 · Insights
Competition Share and participant profile
The leading brand holds 24.6% of footwear Competition Share, with the top five brands together reaching 80.9% of the analysed sample. The single most present model accounts for 5.9% of the whole race. Women make up 36% of the analysed finishers, with a median age of 37.
07 · Deliverables
Aggregated report for the organiser
Real Participant Profile, Competition Share by brand and model, and observed presence of the main sponsor, delivered in a single aggregated and documented report.
08 · Commercial use
Sponsor Asset Adoption
The organiser used the report to document real adoption of the official shirt to its main sponsor: 44% of finishers, 1,400 identified runners.
09 · Measurement scope and limits
What this analysis measures and what it does not
Every metric states its calculation base. Detection coverage (94%) and official shirt adoption (44%) are expressed against total finishers — 2,989 and 1,400 out of 3,180 respectively. Competition Share by brand and model is calculated only among participants with identified product, not against total finishers.
Eyerace does not estimate the financial return of sponsorship, nor project national market share from a single event.
10 · Confidentiality
How we handle confidentiality
Every analysis goes to the organiser first. We publish the name of the event and of the sponsoring brand on the site only when both authorise it in writing — the same standard we apply to your own participant data. That is why this case is shown anonymised.
Next step
Join the next analysis cycle
We work with a limited number of events each season so every analysis is documented in detail.