Mateo Ferreyra — Player report

Rankings / Mateo Ferreyra

Mateo Ferreyra ARArgentina · 20 · right-handed · Rank 147 · Potential 91

Ranking trajectory & 24-month forecast

Official ranking (actual) Forecast interval (80%) Dashed = Top 100 threshold

Key signals

True level ~69 places ahead of the official ranking. Opponent-adjusted strength (surface-split Elo) maps to roughly No. 78 — historically this signal leads the ranking by 6–12 months.
Age–ranking cohort: 61% historical breakout rate. Of players historically ranked 147 at age 20, 61% reached the Top 100 within 24 months.
Top 5% level-transition speed. 3 Challenger titles in the past 52 weeks; transition pace benchmarked against his cohort.
Form: 71% rolling 52-week win rate. 3–2 against Top 100 opponents.
Risk: Surface concentration. 82% of matches on clay; limited hard-court sample adds uncertainty to the North American swing.

Commercial profile

Argentina54%

Spain17%

Italy9%

Other20%

48k Instagram followers, +33% in 90 days. Spanish-speaking audience — a fit for brands entering LatAm and Spanish-language markets.

Suggested package (sample pricing)

Sleeve patch (year-round event exposure)	$12,000 / yr
Social bundle (2 posts + stories monthly)	$6,000 / yr
Gear branding (bag + cap)	$4,000 / yr

Package reference price $22,000 / yr — if he reaches the Top 100 within 24 months (model probability 61%), equivalent exposure typically resells at $150,000+ / yr.

Option-style terms Sign now at $22,000/yr for 2 years; the pre-agreed escalator renews at $66,000/yr if he enters the Top 100 (equivalent exposure resells at $150k+). The escalation odds are the model's own 61%. How these terms work →

Next step

Request brand access to open deal flow on this player, or email [email protected].

Methodology Track record Pricing For players Request access [email protected]

Methodology — Targets are calibrated probabilities of reaching the ATP Top 100 within 12/24 months. Training data: tour, Challenger and ITF results plus weekly rankings since 1990. Backtests are strictly time-sliced; training always ends before the prediction window opens.

Preview build — players, figures, probabilities and prices shown are illustrative sample data.