Each percent is your chance of an interview there, not a ranking of the program. Less competitive programs score higher because they are easier to land.
Where you’re most likely to land an interview
showing 50 of 698How these numbers are computed
Lift = P(invite | signaled in your stratum) − P(invite | unsignaled in your stratum). When the signaled rate is lower than unsignaled in the source (small-N sample noise), we floor the lift at 0 - signaling cannot credibly hurt your odds, and the UI shouldn’t lie.
Stratum = applicant type (US MD / DO / IMG) × Step 2 CK band (<240 / 240-249 / 250-259 / 260-269 / 270+). When n < 10 in your exact stratum, we fall back to the program’s overall rollup so you still get a number, just less personalized.
Gold vs silver: on two-tier specialties, each program’s own gold and silver invite rates are scaled onto your blended estimate, so the chip you pick re-prices the row. When a tier cell has fewer than 10 reports, or gold and silver land within sampling noise (gold not clearly above silver), the two pool back to the single blended estimate - the same n < 10 floor used for strata above.
Tier: Reach (matched-invitee mean is 8+ above your Step 2, or signal can’t rescue), Target (closer fit), Safety (baseline P(invite) > 50% - you’ll interview without a signal). The signal slider hides on Safety and on unrescuable Reach rows where worthSignaling is false.
Refine your estimate: each credential you set shifts P(invite) by its modeled effect for this specialty, from a ridge logistic regression on real applicant data. Credentials with no statistically measurable effect leave the number unchanged.
Caveats: lift is observational (signaled applicants may differ in unmeasured ways like geographic ties, mentorship, prior aways); programs with fewer than ~30 reports have wide CIs.
/match-plan takes your saved programs and computes P(invite), P(match), and tier per program for your specific stats - with primary + backup specialty support and signal-budget allocation.