Recently, the National Collegiate Athletic Association (NCAA) released its first Academic Progress Rate (APR) scores for its football and basketball programs. The APR measures how well athletic programs educate student athletes and will be used to sanction programs that do not perform well academically. With these new academic reforms, the NCAA has taken the groundbreaking step of linking athletic success to academic success.
Proposed NCAA sanctions for collegiate athletic programs that fail to adequately educate student-athletes highlight the prevailing view that athletic success comes at the expense of academic progress. Some research, including research sponsored by the NCAA, has found that high-visibility athletic programs do not help to financially support the academic missions of universities (Litan, Orszag and Orszag 2003, Shulman and Bowen 2001). Research also has found no link between money spent on athletic programs and academic quality (Litan, Orszag and Orszag 2003). Yet, some clear links have been identified between athletic and academic success. Athletic success increases student applications to universities (Murphy and Trandel 1994, Zimbalist 1999). Theoretically at least, increased applications lead to more selective admissions and thus better students. Moreover, research by Lovaglia and Lucas (2005) suggested that high-visibility athletic programs increase the prestige of a public university’s academic degrees. The APR may be useful in promoting a positive association between academics and athletics in another way: Might providing better education for collegiate athletes now help athletic programs win?
The purpose of the proposed NCAA sanctions for programs with low APR scores is to motivate collegiate athletic programs to do a better job educating student athletes. In addition, the APR has the potential to motivate coaches in more powerful ways. First, it allows a direct test of the hypothesis that the athletic success of collegiate sports programs is negatively correlated with the academic success of their student athletes. If it can be demonstrated that no strong negative correlation exists between athletic and academic success, then coaches might be less ambivalent about insisting that athletes progress academically. Second, and most importantly, athletic recruits can use the APR to decide among competing athletic programs. While young athletes recruited to high profile athletic programs may be most concerned with pursuing a successful athletic career, they (and their parents) nonetheless realize the value of a college education. When deciding between two equally successful athletic programs, it would be in a student’s interest to pick the one with a higher APR. If student athletes begin to favor programs with higher APR scores, then the best athletes will go to schools that promote the academic progress of their athletes. Coaches would then have a powerful reason to promote the academic progress of their athletes. It would help them recruit better athletes and win. The perceived relationship between athletic and academic success would shift from negative to positive.
Comparing the academic and athletic success of collegiate programs, however, is not a simple calculation. If an accessible indicator existed that gave equal weight to academic and athletic success, then the best student athletes might well gravitate toward those programs that offered not only the best chance of athletic stardom but also the best opportunity for a solid education.
We develop a combined measure of athletic and academic success, the Student-Athlete Performance Rate (SAPR). The SAPR assigns programs a score based equally on athletic and academic success. To demonstrate its use, we compute SAPR scores for football programs in major conferences (ACC, Big East, Big 10, Big 12, PAC-10, and SEC plus Notre Dame).
On January 10th, 2005, the NCAA Division I Board of Directors approved measures to link athletic scholarships to academic success. In the words of Robert Hemenway, the Chair of the Board of Directors, “This action today is a critical step in our journey to establishing much stronger and significant academic standards for NCAA student-athletes. The ultimate goal is for our student-athletes to stay on track academically and graduate” (NCAA, 1/10/05).
Seven weeks later, on February 28th, the NCAA released its first APR numbers. The APR is based on the eligibility and retention of student-athletes (Brown 2005). Rates of eligibility and retention are exactly the indicators that recruits to a collegiate program would find important in deciding which program to join. Recruits would want to know whether a program is likely to keep them academically eligible to compete and retain them through to graduation.
Each Division I sports program received an APR score on a 1000 point scale. The NCAA set a score of 925, roughly equivalent to an expected 50% graduation rate, as a minimum acceptable standard. About 21% of all athletic teams have APR’s below the 925 cutoff. Perhaps by 2006, programs with subpar APR’s face losing up to 10% of their athletic scholarship allotments.
The number of high-visibility athletic programs that face potential sanctions is substantial. Although 21% of all athletic teams have APR’s below the 925 standard, the percentage is much higher for football and men’s basketball programs. For example, among the 63 football programs in the power conferences representing the Bowl Championship Series, 30 have APR’s below 925 (NCAA, 2/28/05).
THE APR AND ATHLETIC RECRUITS
Aside from its use as a punitive tool, the APR can provide student-athletes recruited to universities a tool to use when deciding among various programs. Talented young athletes recruited by major collegiate sports programs must weigh a dizzying array of information before deciding on a school. Sometimes that information can be contradictory. To make an informed decision, a recruit should be able to answer at least two questions. First, which program will provide the best athletic experience, including the most visibility and the best opportunity for a professional career? Second, which program will provide the best education and opportunities if a pro career doesn’t materialize?
The APR gives student-athletes a way to measure the academic success of athletic programs. From the standpoint of recruits, however, the APR neglects the athletic half of the equation to focus exclusively on the academic side. The most successful sports programs in athletics may not be the ones that do a good job of educating their student athletes. Similarly, the programs that provide the best educational opportunities for student athletes may not provide the best athletic opportunities. There is no clear way to judge how well a program both educates its players and gives them a chance for success in athletics.
We propose an indicator that combines academic and athletic success. The Student-Athlete Performance Rate (SAPR) described below gives equal weight to the athletic and academic success of sports programs.
COMPUTING THE SAPR
We constructed a method for computing SAPR scores and applied it to Division I-A football programs. The SAPR is calculated on a 2000 point scale, half reflecting athletic success and half academic success. 1000 possible points of each program’s SAPR score is its Academic Progress Rate (APR). The other 1000 points of the SAPR is determined by a program’s Athletic Success Rate (ASR). Table 1 displays the factors used to calculate the ASR and their weightings.
Table 1: Factors in ASR (and weightings)
All-time winning % (.10)
Conference championships in last 5 years (.10)
Attendance average (2003) (.15)
Bowl games in last 5 years (.15)
National rankings in last 5 years (.15)
Players in the National Football League (.15)
Wins in the last 5 years (.20)
A number of factors reflect the current status of a football program, including conference championships in the last 5 years, bowl games in the last 5 years, national rankings in the last 5 years, and wins in the last 5 years. All-time winning percentage is included to reflect the tradition of a program. Attendance and professional players from a program are included because we believe they are factors that reflect the potential visibility and chance for professional success of athletes associated with a collegiate program. Similarly, the weightings reflect the factors that we believe recruits would consider most seriously. For example, an important athletic factor for new recruits would be how much a program wins.
For each of the seven factors in the ASR, we gave each program a score reflecting its percentage of the highest possible value for that factor. For example, the University of Michigan had the highest attendance average at about 111,000 fans per game and received a 1.0 for the attendance factor. A program with an average attendance of 55,500 fans per game would receive a score of .5 for the attendance factor. In the same way, a program that has participated in 3 bowl games in the past 5 years receives a score of .6 for the bowl game factor.
We multiplied each school’s score for each factor by its weighting. We then added the weighted factor scores. The factor weightings add to 1.0 and thus adding each school’s weighted scores for each factor produced a total score with a maximum possible value of 1.0. We then multiplied these values by 1000 to put ASR scores on the same scale as the APR.
Our initial ASR calculations produced a range of scores among football programs in power conferences between 148 and 856. We then standardized the scores to produce a range comparable to that of the APR. We then added ASR and APR scores to produce for each program an SAPR score with a maximum possible value of 2000. Table 2 displays SAPR scores for football programs in conferences represented in the Bowl Championship Series.
Table 2: SAPR scores for football programs in conferences represented in the Bowl Championship Series-ACC, Big East, Big 10, Big 12, PAC-10, and SEC (as well as Notre Dame)
|1) Michigan||1920||33) Iowa State||1822|
|2) Miami||1917||t34) Ohio State||1820|
|3) Florida State||1911||t34) Rutgers||1820|
|4) Auburn||1903||t34) Washington St.||1820|
|5) Oklahoma||1897||t37) Arkansas||1818|
|6) Georgia||1894||t37) Illinois||1818|
|7) Florida||1891||t39) South Carolina||1817|
|8) Boston College||1890||t39) Wake Forest||1817|
|9) Texas||1882||t41) Duke||1816|
|10) LSU||1880||t41) Northwestern||1816|
|11) Virginia Tech||1879||t41) Texas Tech||1816|
|12) Iowa||1876||44) Minnesota||1812|
|13) Virginia||1870||45) Cal||1808|
|14) Mississippi||1867||46) Purdue||1806|
|15) Stanford||1865||t47) Oregon State||1800|
|16) Maryland||1864||t47) Washington||1800|
|17) Nebraska||1863||49) Baylor||1798|
|18) USC||1860||50) Vanderbilt||1792|
|19) Notre Dame||1854||t51) Kentucky||1790|
|20) Tennessee||1853||t51) Michigan St.||1790|
|21) Clemson||1848||53) Oklahoma St.||1789|
|22) Georgia Tech||1847||54) Indiana||1788|
|23) North Carolina||1846||t55) Oregon||1787|
|24) West Virginia||1845||t55) Texas A&M||1787|
|25) Pittsburgh||1845||57) Alabama||1785|
|26) Colorado||1841||58) Arizona St.||1784|
|27) Kansas State||1838||59) Mississippi St.||1768|
|28) Syracuse||1833||60) Missouri||1767|
|29) N. Carolina St.||1828||61) UCLA||1765|
|t30) Penn State||1826||62) Kansas||1749|
|t30) Wisconsin||1826||63) Arizona||1722|
|32) Connecticut||1824||64) Temple||1697|
Comparing the APR and ASR components of the SAPR allow a test of the hypothesis that athletic success is negatively correlated with academic success of major collegiate football programs. If athletic success is antithetical to academic success, then we would expect a strong negative correlation between scores on our ASR scale and on the APR scale. Instead, we found only a slight (Pearson’s r = -..122, two-tailed p = .335) and non-significant negative correlation between the ASR and the APR. Statistically, major collegiate football programs whose athletes make good academic progress are just as successful as those programs whose athletes make little progress.
The SAPR has a number of potential uses. One is to give student-athlete recruits a measure of combined athletic and academic success to consider when choosing among various collegiate programs. Some football programs that have been very successful on the football field-Michigan, Miami, and Florida State, for example-also have very high SAPR scores. Others fare less well. Recruits considering alternative programs can use the SAPR as a tool when making their decisions. If use of the SAPR for this purpose becomes widespread, then we can expect the correlation between the athletic and academic success of collegiate programs to shift from neutral to positive. If coaches are able to use high SAPR scores to recruit better athletes, then their success in promoting the academic progress of their student athletes will lead to greater athletic success as well.
Another potential use of the SAPR is to determine the likelihood of programs changing coaches. 10 of the schools with the lowest 15 rankings in our SAPR scores for football programs from major conferences have changed coaches since the end of the 2002 football season. Only 3 of the top 15 programs did so. Some of the changes at both ends of the spectrum reflected coaches being fired, and some reflected coaches moving on to new positions. In a logistic regression analysis with any coaching change as the dependent variable, the coefficient for SAPR approaches significance (B = -.012, SE = .006, two-tailed p = .056) in the direction of schools higher in SAPR scores being less likely to change coaches. More research and a larger sample are necessary to determine the relationship between SAPR scores and coaching changes.
A question for future research is whether the coach or the institutional climate is the primary determining factor in a program’s SAPR score. We can gather more data to test this prediction. We will compute SAPR scores for men’s and women’s basketball programs (which will entail using some different factors in the ASR formula) in power conferences. We will then compare SAPR scores for football and basketball programs at the same institution. If scores for football and basketball are highly positively correlated, then the institution is likely the more important factor. If the correlation is weak or negative, then the coach is probably the driving force.
Brown, G. T. (2005). “APR 101.” NCAA News Online, February 14.
Litan, R. E., J. M. Orszag and P. R. Orszag (2003). The Empirical effects of collegiate athletics: An interim report. National Collegiate Athletic Association.
Lovaglia, M. J. and J. W. Lucas (2005). “High visibility athletic programs and the prestige of public universities.” The Sport Journal 8(2):1-5.
Murphy, R. G. and G. T. Trandel (1994). “The relation between a university’s football record and the size of its applicant pool.” Economics of Education Review, 13, 383-387.
NCAA. 1/10/2005. “NCAA Division I Board of Directors sets cutlines for academic reform standards.” NCAA Press release.
NCAA. 2/28/05. “Academic Progress Rate data for NCAA schools.” http://www2.ncaa.org/academics_and_athletes/education_and_research/academic_reform/school_apr_data.html
Shulman, J. L. and W. G. Bowen (2001). The Game of Life: College Sports and Educational Values. Princeton, NJ: Princeton University Press.
Zimbalist, A. (1999). Unpaid Professionals: Commercialism and Conflict in Big-Time College Sports. Princeton, NJ: Princeton University Press.