About AdmitBase

Who writes this

AdmitBase is written and maintained by Gerrit van Rensburg, its founder. There is no editorial team — it is one person, and you should read the site knowing that.

I build AdmitBase on my own. I read the ABA 509 disclosures, the ADEA, ASCO and AACP reports, and each school's own published class profile, and I write down what they say. Where a school publishes nothing, this site says so rather than filling the gap with an estimate dressed up as a source.

The voice is direct and grounded in evidence. No rankings hype, no motivational filler. Where the data is thin, the site says the data is thin.

How data is sourced

Admission statistics come from published institutional disclosures and from each school's own class profile. They are never taken from self-reported forum outcomes, and never from a rankings table or an admissions-consulting compilation — those publish numbers no school ever released.

• Law: ABA 509 Disclosure Reports (annual, every ABA-accredited US law school)
• Medical: each school's published entering-class profile. AAMC FACTS is used for national aggregates and application volume only — it does not publish per-school MCAT or GPA medians, so neither does this site until the school itself does
• Canadian medical: each school's own admissions-statistics release, including the in-province / out-of-province splits that a national rate hides
• Dental: ADEA Official Guide + ADEA Survey of U.S. Dental School Applicants and Enrollees
• MBA: published class profiles only, and GMAT figures are labelled by scale — classic and Focus are different tests with overlapping ranges
• Pharmacy: AACP Pharmacy School Admission Requirements (PSAR)
• Veterinary: AAVMC institutional data
• Optometry: ASCO institutional data

Each figure carries its own citation rather than the site's word for it: a source label naming the document it was read from, a link to that document where the school publishes one, and a confidence marker saying whether the number is the school's own published figure or an approximation. A figure with no citation gets a caveat on the page instead of a borrowed one. The working notes behind a row — what was checked, what was rejected, what is still open — live in a separate internal field that is never rendered to a reader; what you see beside a number is the public citation, and nothing else.

How the chance number is calculated

Your match score is a percentile. It asks where your GPA and test score fall against the 25th, 50th and 75th percentiles the school published for its own admitted class, then weights the two by programme — law counts the LSAT 60% and GPA 40%, medicine weights the MCAT and GPA equally, and every other programme has its own split, written out on the methodology page. Where a school publishes a median but no quartiles, the spread around it is a programme-typical estimate drawn from the schools that do publish quartiles — an estimate the site works out at read time rather than storing it in the school's row as though the school had reported it.

The chance percentage beside it is that percentile put through a logistic curve anchored on the school's own published acceptance rate. The ceiling rises with that rate and never reaches certainty, so strong numbers at a school that admits a small share of its applicants read as a real chance rather than a lock, and a floor leaves room for holistic review. For law both anchors come from the same document — the ABA 509 disclosure publishes the admitted-student quartiles and the acceptance rate together.

On calibration, plainly: that number is a model of published figures, not a count of what happened to applicants like you. The reference points for checking it are the national grids the profession itself publishes — the AAMC's MCAT/GPA acceptance grid for medicine, which this site carries, and the ABA's per-school disclosures for law. You will not find an accuracy percentage anywhere on this site, because none has been measured against reported outcomes yet. When there are enough of them to measure one, it gets published here whatever it says.

Where the data is weak

Coverage is uneven, and pretending otherwise would make the strong parts worth less. Of roughly 2,300 programme pages, about 940 carry admission statistics; the rest exist so the catalogue is complete and are marked as carrying no data. Pharmacy and MBA coverage is thin because most of those programmes publish nothing per school.

Where a median is an estimate rather than a school-reported figure, the school page says so in a notice beside the number — not in a footnote. Figures that were once presented under a source they did not come from have been removed rather than relabelled. If you find one that is wrong, the corrections policy explains how it gets fixed.

The full match algorithm and statistical methodology are on the methodology page.

Why I built AdmitBase

Admissions transparency is uneven. Some schools publish detailed disclosures; others bury the numbers. Applicants spend hours stitching together stats from a dozen sources, then make six-figure decisions based on incomplete information.

AdmitBase pulls what is published into one place, runs a percentile-based match against your numbers, and shows you where you stand at each school. No rankings spin, no motivational fluff — and no number presented as firmer than it is.

Editorial standards

I update articles when new disclosure data drops (typically annually) and when application cycles materially change. Every article carries a publication date and a last-updated date. If you find an error or have a question about methodology, write to support@admitbase.com — corrections get made, and the editorial policy says how.

Get in touch

Editorial questions, data corrections, or content suggestions: support@admitbase.com. Feature requests: /suggestions.