CRI Plus

Who the accepted applicants were. Academics, backgrounds, and timing for everyone in the dataset who was admitted, grouped into three sections.

Academic Profile

Overview: Average cGPA, sGPA, MCAT, and GRE with the response count behind each, plus the distribution of accepted applicants across score ranges.
Trends: How those averages have moved from one admissions cycle to the next.
Score Combinations: Which pairings of GPA and test score actually appear among accepted applicants, rather than each metric read on its own.
GPA Band Analysis: Accepted applicants grouped into GPA bands, so you can see the shape of the pool around your own.

Who the accepted applicants were before they applied.

Major: The degrees accepted applicants came in with.
Experience: The shadowing, work, and volunteering hours they reported.
Employment: What share held a healthcare role, a non-healthcare role, both, or neither.
Residence: Where they applied from, and which schools took them, in state and out.
Undergraduate: The institutions they came from, and where those institutions send people.
Trends: How the background mix has shifted across cycles.

When the accepted applicants applied, where they ended up, and how long each step of the wait ran.

Timing: The month accepted applicants sent their cycle-wide CASAA application in, each person counted once.
Schools: Which CAA programs accepted applicants ended up attending.
Pathways: Those same program choices grouped by home state or undergraduate institution.
Response Time: The wait broken into five separate measures rather than one number: submission to verification, to an interview invitation, to the interview itself, interview to decision, and submission to acceptance end to end.

Every view can be read across all cycles at once or narrowed to a single cycle, which is how you tell a durable pattern from one unusual year.