Let G be your GPA and Gₛ the program benchmark. For the test equations, M is GMAT and V and Q are GRE verbal and quantitative scores; the subscript s marks the school benchmark.

Here p₀ is the program’s acceptance-rate baseline and logit(p)=ln[p/(1−p)]. The center estimate assumes average non-academic factors. The positive adjustment approaches ln(4), so academics can multiply baseline admission odds by at most four; this creates a different natural upper limit for each program. Negative adjustments are not artificially bounded, so a sufficiently weak academic profile can fall below 1%.

The median is calculated among enrolled students, not all applicants. It tells us nothing about how many rejected candidates also had above-median numbers. At a highly selective school, academic strength is common in the applicant pool, so it can improve your position without making admission more likely than rejection.

MBA admissions are holistic and schools publish enrolled-student summaries—not applicant-level acceptance data. The center assumes average non-academic factors. If p is the center estimate, the band halves or doubles its admission odds:

This is an odds-based scenario range, not a statistical confidence interval, prediction interval or guarantee.

The individual estimates pᵢ = P(Aᵢ) are marginal probabilities. They do not determine how two decisions move together. Independence would be an additional assumption requiring P(Aᵢ ∩ Aⱼ) = pᵢpⱼ. That is unlikely here because the same career impact, leadership, recommendations, essays and interview ability affect several applications.

Z is one shared, normally distributed application-strength factor; φ and Φ are the standard normal density and cumulative distribution. Conditional on a fixed Z=z, school decisions are treated as independent and the usual Poisson-binomial calculation is used. Integrating over Z makes the final outcomes positively related while preserving every school’s displayed probability. The 30% latent-correlation setting is provisional—not estimated from applicant-level admissions data. If it were set to zero, the model would reduce to independent coin flips; for example, P(at least one)=1−∏ᵢ(1−pᵢ).

Program inputs link to the latest available official profiles, primarily Class of 2027. For a consistent interface, every school-level comparison figure is labeled “median.” When a school publishes only an average, range or legacy GMAT score, that value is used as a median proxy; each result card links to the official profile and shows how the school reported it.