The Season of Recruiting Rankings: 24/7
By Michael Chung
In my prideful trust of advanced education, I felt it would be a cinch to write up the major recruiting services’ methodologies. The big boys—Scout and Rivals—were relatively simple and my numbers turned out correct, and then came 247. While looking at their numbers, I worked hard on trying to figure it out for myself as well as searched for their explanations. The first aspect of their player rankings is very straight forward:
At 247Sports, each recruit that we evaluate will be assigned a numerical rating as well as a star rating. The rankings are determined by our recruiting analysts after countless hours of personal observations, film evaluation and input from our network of scouts.
Players are ranked by position, grouped qualitatively with a star ranking and given a numerical ranking based on their future potential. The explanation for the numerical rankings is below.
110-101 = A player ranked in this range is a "franchise player." He is one of the best to come along in years - if not decades (LeBron James, Adrian Peterson). Odds of having a player in this category every year is slim. This prospect has “can’t miss” talent.
100-98 = Five-star prospect. One of the top 25 or so prospects in the nation. Player has excellent pro potential, and should emerge as one of the best players in the country before his college career ends.
97-90 = Four-star prospect. Prospect will be an impact-player for his college team. All-America candidate who displays pro potential. Typically one of the top 300 players in the nation.
89-80 = Three-star prospect. These are the players who will develop into reliable starters for the college teams. They are among the best players in their region of the country, and are generally among the top 750 players in the nation.
79-below = Two-star prospect. These players make up the bulk of Division I rosters. They may have little pro potential, are likely to become role players for their respective schools or not enough is known about the prospect to rank them accurately.
No sweat like all the other services, but then came trying to figure out their team rankings system, here is where the difficulty begins. 247 writes:
Powered by the industry-generated 247Composite, the 247Sports Team Recruiting Ranking is a proprietary formula based off the Gaussian distribution formula. Updated in real-time after each commitment, the 247Sports Team Ranking is widely respected as the industry's most comprehensive and unbiased team recruiting ranking.
Here is “The Formula“ they use:
where c is a specific team's total number of commits and Rn is the 247Composite Rating of the nth-best commit times 100.
In order to create the most comprehensive Team Recruiting Ranking without any notion of bias, 247Sports Team Recruiting Ranking is solely based on the 247Composite Rating.
Each recruit is weighted in the rankings according to a Gaussian distribution formula (a bell curve), where a team's best recruit is worth the most points. You can think of a team's point score as being the sum of ratings of all the team's commits where the best recruit is worth 100% of his rating value, the second best recruit is worth nearly 100% of his rating value, down to the last recruit who is worth a small fraction of his rating value. This formula ensures that all commits contribute at least some value to the team's score without heavily rewarding teams that have several more commitments than others.
Readers familiar with the Gaussian distribution formula will note that we use a varying value for σ based on the standard deviation for the total number of commits between schools for the given sport. This standard deviation creates a bell curve with an inflection point near the average number of players recruited per team.
The site gives a very nice graph to illustrate that OSU’s best player will have the highest value, equal to his composite score, and each player afterwards will have a lower value. At the time of the writing of this article (before Lonnie Johnson de-committed), Ohio State had a mean of 91.67 (but they are now at 91.91 due to Lonnie Johnson’s numbers being low) and an overall score of 264.96 (but now at 261.66 as Johnson’s numbers were removed from the final tally). We will mainly use the numbers prior to Lonnie Johnson’s de-commitment and have in brackets the current value.
To calculate OSU’s total team score, I need to figure out the standard deviation, which “shows how much variation or dispersion from the average exists (Taken Wikipedia, same link as above).” To do this is a bit tedious. I must take every player’s composite score (CS), e.g. Damon Webb is the top player with a CS of 98.03, subtract it from the average of 91.67, then take the product and square it. I must do this for all 18 players then divide by 18 and take the final square root to obtain the std. deviation. So with Damon Webb would be 98.03-91.67= 6.36, then 6.36 squared equals 40.45. I would do this for every player, then add up the numbers, divide by 18 (but now 17), and then take the square root of the quotient for the standard deviation, which I would then plug into the formula, and get 18 (17) different values.
For the standard deviation, I came up with 4.43 (but this will change since Johnson’s de-commitment). Now I plug this and each player’s number into the equation. The best player is Damon Webb, so his score will be 98.03 because his n score =1 which means we would take 98.03 times e to the zero power or 98.03 times 1. Each player afterwards should have a lower number than Damon. Jamarco Jones has the second highest composite at 97.33, and his n=2, plugging it into the equation would yield a number lower than 97.33. You do this for every player and come up with the total, which should equal around 264.96 (but now would equal 261.66).
I tried for a while to plug in the numbers and came to the conclusion that the average fan would not take so much time to do it, so I decided only to explain how to do it in hopes that those who were truly interested and wanted their math brushed up would have the means to work on 247’s formula.
What I do think the average Recruitnik would be interested in is how much of a predictor is 247. We saw in an earlier article, that Alabama has won the Rivals recruiting challenge five of the last six years and has won three of the last four BCS national titles and is knocking on the door for another. There does appear to be a correlation between Rivals and BCS national championships; does 247 offer the same?
In 2008, 247 had Alabama 3rd behind Notre Dame and Georgia while OSU finished 6th. In 2009 Alabama finished 2nd behind LSU while the Buckeyes finished 4th, 2010 Alabama finished 5th while OSU finished 20th. In 2011 Alabama was #1 and the Buckeyes 6th. In 2012 Alabama was #1 and OSU 5th, and in 2013, Bama again was #1 and the Buckeyes were #2. Judging by the numbers in this very unscientific brief study, 24/7 has done a fairly decent job of predicting the future success of college football teams based on recruiting.
Our next article will look at ESPN.