For high school graduates, choosing the right college depends on many different factors. Academics, cost, distance from home, athletics, and social factors all play a role in choosing which schools to send applications. But students and their families often have incomplete information about the colleges they are qualified academically to attend or those that will provide the necessary financial aid. When a student settles for a college beneath their qualifications, the phenomenon is called "under-matching." The 2013 Data Science For Social Good team of Min Xu, Edward Su, Nihar Shah, and mentor Michelangelo D'Agostino used data analytics to tackle this educational problem.