TMDSAS Odds Calculator

TMDSAS Odds Calculator

Historical chances for TMDSAS medical applicants, estimated from the public TMDSAS Medical Report (EY2016–2025), with the real outcome data behind every estimate. Unofficial. Opens on an example profile. How it works

Entry yearsLast 3 · Last 5 · All
Residency
Gender
Application
513
1-point
3.90–3.99
0.1 bin
Interview
–
Chance of at least one interview
Acceptance
–
Chance of at least one acceptance
If interviewed
–
Acceptance among those interviewed

How the estimate moves with MCAT

Same profile and GPA, every MCAT score from 495 to 528. The dot marks your selection.

InterviewAcceptanceAccepted if interviewed

What actually happened

How this calculator works, and how we know it's accurate

Every number on this page traces back to the public TMDSAS Medical Report. This section shows where the data came from, how the estimates are built, and how closely they match what really happened.

1Where the data comes from

TMDSAS publishes a public dashboard of its medical applicants, the TMDSAS Medical Report. We downloaded its counts (not individual records) on 14 October 2026: how many applicants in each entry year, residency, gender, ethnicity, applicant type, MCAT score and GPA bin were interviewed, accepted and enrolled.

You can check these totals yourself: open the dashboard, pick one entry year, and the applicant count matches the row above.

2What each field means

MCAT
Total score from the applicant's most recent sitting (472–528).
GPA bin
Overall GPA rounded down to 0.1. "3.90–3.99" includes 3.90 through 3.99.
Interviewed
Received at least one interview at a TMDSAS medical school.
Accepted
Received at least one acceptance.
Matriculated
Enrolled in a TMDSAS medical school.
Reapplicant
Applied through TMDSAS in an earlier cycle.
Residency
Texas resident or non-resident, as TMDSAS recorded it.

3Who the model learned from

The model uses 57,256 of the 63,577 applicants. We left out the 6,321 who can't be scored on this page's inputs:

  • 6,041 with no current-format MCAT on file (most are EY2016 applicants who took the pre-2015 MCAT)
  • 199 with no GPA on file
  • 81 who declined to state a gender

The real-data grid above still includes everyone, with "None" columns and rows for missing scores.

4How the estimate is calculated

We fit three logistic regressions: a standard statistical method that learns, from past applicants, how each factor raises or lowers the odds of a yes/no outcome. One predicts an interview, one an acceptance, and one an acceptance among people who were interviewed.

  • MCAT and GPA enter as smooth curves, not straight lines. The curve can bend at 495, 500, 505, 510, 515 and 520 (MCAT) and at 3.3, 3.5, 3.7 and 3.9 (GPA), because a point matters more in some ranges than others.
  • MCAT and GPA work together: a high GPA helps more when the MCAT is also high.
  • Residency shifts the whole curve and changes how much MCAT and GPA matter.
  • Gender, ethnicity, applicant type and entry year each shift the odds up or down.

When you pick several years, the calculator scores your profile once per year and averages the results. "Any" gender averages men and women. "Any" ethnicity weights groups by their share of Texas applicants. "Any" applicant type weights first-time and reapplicants 78% to 22%, their share of applicants.

Evidence the estimates match reality

Texas residents by MCAT: real vs. model

Dots are the share of real applicants who got in. Lines are what the model predicted for those same applicants. EY2016–2025, 3-point MCAT groups.

Accepted, realAccepted, modelInterviewed, realInterviewed, model

Texas residents by GPA: real vs. model

Same comparison by overall GPA bin. EY2016–2025.

Accepted, realAccepted, modelInterviewed, realInterviewed, model

Test on years the model never saw

We refit the model on EY2016–2023 only, then asked it to predict EY2024–2025. Applicants are sorted into ten equal groups by predicted chance; bars compare predicted and real acceptance in each group (1 = lowest predicted chance, 10 = highest).

PredictedReal

Checks by group: Texas residents

Share accepted, real vs. model, for every gender and ethnicity group with 300+ Texas-resident applicants (EY2016–2025).

Non-residents by MCAT: real vs. model

Non-residents face much lower odds, and the model tracks that separately.

How much each factor moves the odds

Odds multipliers for an applicant with the same MCAT and GPA. 1.00 = no change; 2.00 = double the odds; 0.50 = half. These describe past outcomes, not why they happened. For example, they cannot see school missions, essays or experiences.

Limits to keep in mind

  • The model only knows MCAT, GPA, residency, gender, ethnicity, applicant type and year. Experiences, letters, essays, school list, MCAT section scores and application timing all matter and are not in the data.
  • Effects are added together, so combinations are not modeled separately. For example, Texas-resident Asian women were accepted slightly more often than the model predicts (49.6% vs 47.9%), more so at high scores.
  • Each cycle differs. In the test on unseen years, the model's ranking held up well, but it overestimated the overall acceptance rate by about 2 percentage points because 2024–25 were more competitive than earlier years. Choosing recent years in the calculator reduces this.
  • Unofficial analysis of public data. Not affiliated with or endorsed by TMDSAS.