Lead factor
Evidence strong
Fan-market fit
Campus relevance, sport calendar, and modeled fan-base overlap.
Fixture-derived; not live social scraping or guaranteed reach.
ProsMatch engine
The AI that scores athlete–brand fit.
Five domains, published weights, the reasoning written out, and a human reviewer who owns every call. Pick a matchup and run it live.
Real NIL data where available; some economics are modeled for the demo.
Try a matchup
The highest-trust proof case: existing reported Nike deal, signature product logic, and mainstream women’s basketball demand.
Live match run
Caitlin Clark × Nike
Run to score
Decision support only
A human reviewer owns the final call.
Formula: National consumer brand: 30% fan base + 25% social + 10% locality + 20% athletics + 15% brand fit
Fan-base alignment—
Social media and influence—
Locality and geography—
Athletic exposure—
Brand values and character—
ProsMatch read
Run the match to see ProsMatch explain the read across all five scoring domains.
Human reviewer owns eligibility, policy + disclosure.
Rules first, then the score
Inputs in, a score out, the reasoning shown.
Before it ever gets to an athlete, a campaign goes up against a set of rules in the matching engine. Athletes only see what they are actually eligible to apply for. Then the score: the same five domains every time, weights you can read, caveats spelled out.
- 01
Real signals, clearly sourced
Inputs
An athlete and a campaign: fan base, social reach, locality, athletic record, and brand fit, each drawn from NIL rows and labeled by source and confidence.
- 02
One weighted Match Score
Score
The five domains roll up through published weights into a single Match Score and tier, so the number is reproducible, not a black box.
- 03
The read, written out
Rationale
ProsMatch returns why the score landed where it did, the leading domain, the caveats, and the next human action, never a silent verdict.
How the score is built
The weights are published, not implied.
The match score is not a black box. Each of the five domains carries a fixed, visible weight and a stated measure, so a reviewer can see what moved a recommendation before trusting it.
A weighting framework can be audited; a black-box ranking cannot.
AASFan-base alignment
25%
Demographic, psychographic, category, and platform-behavior fit between the buyer persona and the athlete’s fan base.
SMISSocial media and influence
20%
Actual reach and quality of reach, prioritizing engagement over vanity follower counts.
LGRSLocality and geography
20%
Hometown, campus, follower concentration, and regional media relevance.
APESAthletic exposure
20%
School/conference level, sport visibility, performance, and media coverage.
BVCSBrand values and character
15%
Values fit, content tone, risk profile, and prior sponsorship performance.
Compatibility factors
Every factor carries evidence and a caveat.
Deliverable feasibility
Informational
Two short-form videos and affiliate link proof mapped to a 14-day window.
Final workload and availability require athlete/manager confirmation.
Brand-category safety
Needs review
Recovery-product category mapped against disclosure and associated-entity review.
No automatic compliance clearance; reviewer note required.
Proof readiness
Informational
Proof URL, screenshot, UTM receipt, and brand acceptance fields are modeled.
Demo data only; no live performance claim.
Data sources
- Demo campaign fixture
- Athlete packet fixture
- Comparable activation pattern
- NCAA Bylaw 22 source card
- Per-school policy source card (fixture)
- House v. NCAA settlement approved June 2025; forward revenue sharing in effect; back-damages appeals pending
Compliance posture
- ProsMatch suggests compatibility bands, not eligibility rulings.
- Every factor exposes evidence and caveat text.
- Compliance officers and AD office reviewers remain the decision owners.
- No NCAA, CSC, school, or conference affiliation is claimed.
- No public pricing or live customer-performance data is displayed.
ProsMatch never issues an eligibility ruling, every recommendation halts for a named human reviewer.
ProsMatch is decision support, not live AI decisioning. Every score halts for a named human reviewer who owns eligibility, school-policy, and disclosure calls.
House v. NCAA settlement approved June 2025; forward revenue sharing in effect; back-damages appeals pending. Proslync is independent of the NCAA, the CSC, and individual schools.