Data Sources & Methodology
Version 1.0 · Last Updated: June 24, 2026
1. Overview
MedTrack helps premed students track their progress toward medical school by combining their self-reported study and experience data with public school-level data. This page explains the calculations behind the metrics in the app, the sources behind our school dataset, and the limitations of what those numbers mean.
We publish this page so users — and admissions counselors, advisors, and researchers — can understand exactly what MedTrack measures and how. None of the figures below are admissions predictions. They are tracking aids and self-assessment tools.
2. What MedTrack Score Measures
MedTrack Score is a 0–100 composite that summarizes your overall premed readiness across multiple pillars:
- MCAT performance and practice accuracy
- AMCAS-style experience hours (clinical, volunteer, shadowing, research)
- GPA (both cumulative and BCPM "science" GPA)
- School list balance (reach / target / safety distribution)
Each pillar is weighted based on its typical importance in medical school admissions. The score updates as you log new data.
Pillar weights (current version)
The Score draws on four pillars:
- GPA pillar — 30%. Cumulative and science GPA, weighted against AAMC-published applicant percentile data.
- MCAT pillar — 30%. Projected MCAT range from your practice block data plus any official MCAT score you have entered.
- Experience pillar — 25%. Total clinical, volunteer, shadowing, and research hours, weighted against typical accepted-applicant hour distributions.
- School list balance pillar — 15%. Distribution of your target list across reach, target, and safety tiers based on your stats.
These weights reflect the relative emphasis admissions committees typically place on each category at MD programs. The weights are tuned for a US MD-track applicant; DO and international tracks use modified weights documented in-app.
3. How Projected MCAT Is Calculated
The Projected MCAT range is an estimate of the scaled MCAT score you would likely earn based on your logged practice data. We display a range (e.g., 508 — 514) rather than a single number because limited practice data has inherent uncertainty.
The estimate is based on:
- Your logged practice block scores
- Performance trends over time
- Section-level accuracy where available (Chem/Phys, CARS, Bio/Biochem, Psych/Soc)
We use a statistical model that converts your practice accuracy to an estimated scaled MCAT score range. The range widens when you have limited practice data and narrows as you log more blocks. As you get closer to the AAMC-published official practice test range, the projection converges toward what real test-takers with similar practice accuracy have scored on the actual MCAT.
Disclaimer: Projected MCAT is an estimate based on self-reported practice data, not a prediction of actual MCAT performance. Real MCAT scores depend on many factors not captured in practice data — test-day conditions, stamina, content gaps that practice didn't surface, anxiety, and timing. Treat the projected range as a directional signal, not a forecast.
4. How Practice Accuracy Is Calculated
Practice Accuracy = total correct answers ÷ total questions answered, across all logged practice blocks.
It updates whenever you log a new block. Section-level accuracy (when shown in-app) uses the same formula scoped to a single MCAT section's blocks.
We do not weight more recent blocks more heavily than older ones in the headline accuracy figure. If you want to see your trajectory over time, the in-app Performance screen shows a rolling accuracy line by week.
5. School Data Sources
MedTrack pulls school data from public, primary sources where available. We prefer official sources over aggregators, and we mark on each school's page where a given figure came from.
Sources we use:
- AAMC-published statistics (for MD programs)
- AACOM-published statistics (for DO programs)
- Official medical school websites (linked tuition, admissions statistics, class profiles)
- U.S. Department of Education public datasets (for tuition figures where the school does not publish a current number)
- Third-party aggregators (used as a fallback when primary sources are not publicly accessible — these are marked on individual school pages)
Data is refreshed periodically. Some figures may lag behind the most recent admissions cycle, because many schools publish their stats only after the matriculating class has enrolled.
6. Acceptance Rate Methodology
We display acceptance rate as:
(matriculants ÷ total applicants) for the most recent published admissions cycle
This is the convention used by the AAMC's Medical School Admission Requirements dataset.
A few notes:
- Acceptance rates marked "Not disclosed" reflect schools that do not publicly publish this figure.
- For DO schools, application volumes are typically smaller than MD schools, which can make a single year's rate look more volatile.
- Schools that are very selective (sub-5% acceptance rate) and schools that are very open (over 25% acceptance rate) are both meaningful signals — we do not hide either category.
- Acceptance rate is not the same as admit rate. Some schools report different numerators (offered admission vs. accepted offer vs. enrolled). We standardize on matriculants where possible.
7. Tuition Data
Tuition figures are pulled from official school sources where available, and from aggregated public datasets where not. Figures represent estimated annual tuition for the most recent academic year published.
- In-state tuition rates apply only where a school participates in a state university system with differential tuition. We display in-state rates if your residency matches.
- Private schools typically have a single tuition figure.
- Special cases — full scholarships (e.g., NYU Grossman), military-funded programs (HPSP/USUHS), or income-based reduced tuition — are noted on the individual school's page.
Tuition figures do NOT include fees, housing, meals, transportation, books, board exam costs, or other cost-of-attendance components. For total expenses, refer to the school's published cost of attendance.
8. What MedTrack Score Is NOT
This section is important. We want users to understand the limits of what the Score is for.
MedTrack Score is NOT:
- NOT an admissions prediction. A high Score does not guarantee acceptance. A low Score does not mean you will not be admitted.
- NOT endorsed by the AAMC, AACOM, or any medical school. MedTrack is independently developed and operated by MedTrack LLC.
- NOT a substitute for advice from premed advisors, admissions counselors, or other qualified human professionals.
- NOT a guaranteed indicator of admission outcomes — admissions committees evaluate many qualitative factors (personal statement, letters of recommendation, interview performance, fit) that no automated scoring can capture.
Use the Score the way it is intended: as a tracking tool that helps you see where you stand on the measurable dimensions of a premed application. Pair it with human guidance from your advisors.
9. Updates & Versioning
This methodology document is versioned. Material changes to the scoring algorithm or to which data sources we use will be noted here so you can see what changed and when.
- Current methodology version: 1.0
- Last updated: June 24, 2026
Past versions of this document will be archived as we publish new ones.
10. Questions
For methodology questions, including how a specific number was computed or why a particular school's data looks the way it does:
Email: medtrackinfo@gmail.com