Where the data comes from
We combine public, verifiable records with relationship-sourced detail from inside admissions offices.
Tier 1 — Public
FLDOE, NCES, and school admissions offices
Enrollment, grades served, type, accreditation, scholarship participation, and published tuition come from the Florida Department of Education, the National Center for Education Statistics, and each school’s own admissions site.
Tier 2 — Relationship-sourced
School director interviews — the data ChatGPT cannot scrape
Acceptance trends, soft factors (sibling preference, geographic preference, interview weight), realistic timelines, and openings we hear about first. Sourced directly from 40+ Florida school directors in our network.
Built relationships, not scrapers.
Who built this
AdmitCompass is built by a Stanford GSE-trained founder, working with 40+ Florida school directors and a small research team.
Founder is Stanford Graduate School of Education-trained in Learning Design & Technology. The rest of the team is not GSE — they are working Florida school directors and education researchers.
How we estimate acceptance rates
We don’t pretend to a single number every school director would sign off on. Instead, we use a transparent type-based fallback — and replace it with a verified rate the moment a school confirms one.
- Charter schools — published lottery odds where available, otherwise the type-level baseline for the grade and county.
- Lottery-based magnets — district-reported seats vs applicants for the most recent cycle.
- Private schools — a type-based baseline by grade band and county, refined as our director network shares a verified rate.
- Verified rate — replaces the fallback the moment a school confirms one. We label which is which on every match card.
Pattern: we’d rather show a wider range and be right than a precise number and be wrong.
How the match approach works
We compare your child’s profile against each school across four axes. We publish the axes, not the weights — the weights are how we earn a living.
- Academic fit — grade, current school context, learning differences, and stated academic preferences.
- Financial fit — household budget, scholarship eligibility (Step Up, FES, VPK), and the school’s real net price.
- Geographic fit — haversine distance from your ZIP to the school, plus commute realism by county.
- Program fit — your child’s interests against the school’s actual programs, sports, and accommodations.
We don’t publish the per-axis weights. That’s the part ChatGPT can’t replicate.
How fresh the data is
Last updated 2026-05-25
Public records refresh quarterly. Director-sourced data refreshes per outreach cycle — typically every 6–8 weeks per school. Every school detail page links to its underlying sources.
What we don’t claim
We’d rather be honest than impressive.
- We do not guarantee admission. Estimates are based on data — not promises.
- Tier 2 director data does not cover every Florida school yet. We label coverage on each match.
- Only the founder is Stanford GSE-trained. The rest of the team is Florida school directors and education researchers — not GSE alumni.
- We publish what feeds the match approach, not the exact weights. That part is the moat.