February 1, 2011

Recruiting vs. results: The cycle in action

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Dallas Jackson is the Senior Analyst for RivalsHigh. Email him your question, comment or story ideas to DallasJ@Yahoo-Inc.com and follow him on Twitter.

Last week, RivalsHigh did a simple analytic to see which college football programs are doing more-with-less, or less-with-more, when it comes to recruiting classes and winning on the field.

Basing on an analysis of the 29 NCAA FBS teams to finish inside the Rivals.com Top 50 recruiting classes since 2002, it drew that the Virginia Tech, Missouri and Ohio State were the three teams getting the most out of the recruits that the team brings in - while Texas A&M, South Carolina, and Ole Miss were on the flip-side of that.

As you can imagine, numbers folks who also are sports nuts, took the idea and ran with it.

Cary A. Caro, Ph.D (LSU) is just that.

"Data collection and analysis is a big part of our curriculum here and was very intense in our graduate program," he said. "I just really enjoyed the stats part of it because it's very objective and gives you an understanding of relationships from a mathematical perspective. That and I'm a football junkie."

Caro created a regression analysis that was formulated to show what the correlation between the offseason success and on-field winning is. He expanded the scope to recruiting points, as opposed to simple class rank, coaching changes, bowl wins and bowl losses to try to explain what impact other outside forces could have in recruiting as well as the potential impact recruiting could have on the cycle.

"I began the analysis with simple correlation statistics using the variables discussed," Caro said. "Winning percentage over the time period was correlated to recruiting point average by a coefficient of .684. There is a very strong positive correlation between a team's winning percentage and the average class recruiting points scored."

But what factors are the biggest?

The study showed that winning a bowl game has a strong correlation in recruiting success, while losing a bowl game barely has any negative impact.

"Winning your bowl game has a .623 correlation to recruiting points gained, a very strong correlation," Caro said. "However losing a bowl game only has a negative-.091 impact, which means that losing your bowl game has nearly no effect in winning a recruiting battle."

Surprisingly, coaching changes nearly had no impact on long term success on the field or off.

Naturally, there are cases where the impact is dramatically good - Nick Saban at Alabama for example. However, his positive impact is offset by the negative impact that can be done by Rich Rodriguez at Michigan or Rick Neuheisel at UCLA.

The overall impact shows that stability in a program is dramatically more important than coaching changes.

"A coaching change can drop your winning percentage over the course of the 10 years by 0.063," Caro said. "Which is almost nothing but it is interesting, as you would expect this number to be positive, but statistically, that is not the case. While is it a marginal effect, it's still a negative effect. This model shows that winning in the recruiting arena and keeping your coaches really helps to bolster your winning percentage in the course of 10 years."

This could be a proof positive as to why teams such as Ohio State, Oklahoma, and Virginia Tech - which have had no coaching changes since 2002 - are steady in both recruiting and on-field success while UCLA, Tennessee, Notre Dame and Nebraska have fluctuated in both categories and had three different coaches in the same time period.

BY THE NUMBERS
There are 29 schools to have its recruiting classes ranked inside the Top 50 each year since 2002. Here's the average recruiting points, bowl record and coaches in that time span.
TeamAvg. PointsBowl RecordCoaches
Alabama1900.35-33
Arizona1103.81-23
Arizona State1166.62-32
Arkansas1207.62-42
Auburn1799.66-22
Florida2330.85-42
Florida State2160.76-32
Georgia2077.17-21
LSU2245.36-32
Maryland12055-11
Miami1952.43-52
Michigan1904.92-52
Mississippi1296.14-03
Missouri1061.63-31
Nebraska1385.84-33
North Carolina12621-32
Notre Dame1650.41-43
Ohio State1893.26-31
Oklahoma2134.44-51
Oklahoma State1159.34-42
Oregon1319.92-62
Pittsburgh1053.82-52
South Carolina1550.41-42
Tennessee1933.62-53
Texas2178.86-21
Texas A&M1463.10-53
UCLA1510.43-43
USC2589.97-12
Virginia Tech1245.74-51
The next step in the process is to draw the direct correlation to top classes and winning.

Caro finds that there is a stunningly strong percentage tied to recruiting.

"I moved on to try to predict winning percentage over the course of the time period by recruiting points averaged in the same period.," he said. "Interestingly, recruiting points accounted for 45 percent of the variance in winning percentage in that time period. So, we can say that 45 percent of a team's success is attributable to how many points they score in the recruiting cycle in that time period."

Caro developed a prediction model based on recruiting points and its correlation to winning.

"If we wanted to try to predict a team's winning percentage we would apply the formula of (Winning percentage = .343 + .00018) where X is the points the team scores in the recruiting cycle in that period of time," he explained. "So, for every 500 points the team scores in recruiting, the winning percentage will rise by about .09 points (.433 for 500 points, .523 for 1000 points, .613 for 1500 points, etc.). You can extrapolate the data accordingly by putting in the team value in recruiting points and know that about 45 percent of your success is already taken care of by this factor but you still have to develop, schedule, play, etc."

Other factors get thrown into an additional model which indicates that 76 percent of a team's winning percentage can be factored by recruiting, coaching and bowl wins.

"These were the only significant predictors in the 10 year span for team winning percentage. These factors accounted for 76 percent of the variance in the percentages over that period of time," Caro said. "This model was as follows: Winning Percentage = .511 + .0001 (Recruiting Points) - .063 (coaches) + .019 (bowl wins)."

The last factor looked at was early impact versus long-term effect of a class.

By looking at what the class did in its first year versus the length of time a class remains in the program showed that, while a great class can impact the team immediately, recruiting is a long-term process.

"I ran a regression model where each of the points earned in recruiting was run against winning percentages in that same year," Caro said. "This model showed that recruiting points only accounted for 11 percent of the variance in the winning percentage on a yearly basis.

"So what does this all tell us? In essence, recruiting is indeed a long-term process that leads to success in the long term, not the short term. This is evidenced in the difference between the yearly model, and 11 percent variance, and the long term model (45 percent)."

What this shows us may be what recruiting experts already knew: College football is not a chicken-or-egg problem. It is a cyclical, living example of how recruiting and winning goes hand in hand.

Mathematically, it shows that recruiting is a long-term practice, letting a coach see the term through is important and being a great recruiter is very much tied to winning.

"Essentially, from a statistical stand point, if you can account for nearly half of your winning percentage through recruiting, then you can see how essential it is to bring in top talent each year," Caro said.

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