A new way to predict where top prospects will end up

Top running back Darrell Scott has narrowed his decision down to Texas, Colorado, Florida and LSU. John Albright / Icon SMI

Signing Day 2008   Latest Coverage SI.com/Rivals.com Top 25 Classes of '08 Mandel: Bama, ND reign; day's awards Staples: Analyzing the day's big decisions Rivals: Updates on who's going where Staples: Clemson lands impressive haul Mandel: Pryor officially delays decision Rivals: Team-by-team recruiting lists Takkle: Nation's top 100 prospects Takkle: Video highlights of top recruits Previous Coverage Rivals: Ranking top recruits' skill sets Staples: How Signing Day became so big Mandel: Pryor's recruitment one of a kind Staples: Wackiest recruiting story of year Mandel: SEC rules recruiting by numbers Staples: Recruiting and politics collide Tucker: Big factors in picking a school Staples: An economical look at recruiting Staples: Schools curb lavish official visits Armstrong: Recruits flock to Notre Dame Looking ahead Markazi: Barkley could be next big Trojan

Jeannette, Pa., quarterback Terrelle Pryor will sign with Ohio State, Foley, Ala., receiver Julio Jones will choose Alabama and Ventura, Calif., running back Darrell Scott will pick Texas. This isn't my opinion, nor do I have any inside information.

It's economics.

Using equations that contain more Greek letters than your favorite school's fraternity row, three economists have devised a way to predict the college choices of top football prospects. In two recruiting seasons (2005 and 2007), the College Football Recruiting Prediction model developed by Mike DuMond, Allen Lynch and Jennifer Platania has correctly predicted the college choice of the members of the Rivals 100 with 72.5 percent accuracy. The economists, who were published last week in the Journal Of Sports Economics, plan to predict the destinations of the nation's top 250 recruits on their Web site later this month, but DuMond ran the numbers of the three previously mentioned recruits to offer a taste of what to expect. According to the model, there is a 40.2 percent chance Pryor will choose Ohio State, compared to a 37.9 percent chance he will choose Michigan.

In addition to predicting the future, the model provided empirical evidence that BCS schools enjoy a prohibitive advantage over their non-BCS brethren in recruiting top talent. It also disproved several long-held beliefs about recruiting. For example, recruits don't seem to care how many players a school puts in the NFL, they aren't as interested in early playing time as they claim and scholarship reductions actually increase the likelihood that a top recruit will pick a particular school.

So what possessed three highly educated professionals to devote countless hours of their spare time to predicting the whims of 17- and 18-year-old football players? The easy answer is they live in the South. The trio met in the early '90s as doctoral candidates at Florida State. DuMond and Lynch, both Floridians, love the Seminoles. Platania, meanwhile, roots for her home-state West Virginia Mountaineers. And even though they had scattered -- DuMond works for a Tallahassee, Fla., consulting firm, Lynch teaches economics at Mercer in Macon, Ga., and Platania teaches at Elon in North Carolina -- they still yearned in 2004 to understand why certain prospects chose certain schools.

"You read interviews with some of these recruits ... and they say 'I felt more comfortable there' or something really vague like that," DuMond said. "We were just trying to figure out if we could put any science behind that sort of decision."

So DuMond, Lynch and Platania scoured the archived data on Rivals.com for the recruiting classes of 2002-04. During an 18-month span, they devised a set of more than two dozen variables (official visits, distance from the player's home, school recruiting budgets, age of each school's stadium, etc.) and built a model. They devised equations that told them what mattered most when a recruit made his decision. After plenty of heavy thinking and trial and error, they developed a statistical formula they believed would accurately predict a recruit's college choice.

Using a computer program called SAS (Statistical Analysis Software), the trio fed the pertinent data for the 2005 Rivals 100 into the model. They ignored whether players had already committed, instead using each player's final set of schools to see if the model would spit out a correct prediction. The model went 71 for 100, and it correctly guessed the destinations of the six highest-ranked players (Derrick Williams, Jerrell Powe, Eugene Monroe, Fred Rouse, Callahan Bright and Mark Sanchez).

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