Article posted on September 13, 2011

Do men’s college basketball coaches perform better when coaching at their Alma Mater? Our study analyzed several variables that might help answer this question through exploring what, if any, influence they might have on a coach’s performance, with the goal being identifying specific variables that would aid ADs in assessing the winning potential of coaches they are considering employing.

To consider this question, we analyzed the final results of 629 coaching stints of coaches active in the last ten years – a stint being defined as one coach’s time as the head coach at a single school – with his time as head coach at a separate school being defined as a separate stint.

We focused on the alma mater variable to test whether coaches who work at a school that they attended (and thus a school where they should have a detailed working knowledge of the system, relationships with members of the program, and a deep emotional attachment to) will be more successful than coaches brought in from the outside. We also assessed six other variables related to coaching (years of assistant coach experience, years of head coaching experience, number of head coaching jobs held, age, whether or not a coach is a head coach at a school where he was an assistant, and whether or not a coach is employed by a BCS conference school).

Among these seven variables, three are significant: years of head coaching experience (which was a negative correlation), number of head coaching jobs held, and whether or not the coach is employed at a BCS conference school.

What did we find? In general terms, the data we analyzed suggests that when hiring coaches, ADs can and should consider coaches who are “hot,” (i.e., actively climbing the career ladder). ADs should also be wary of coaches with long tenures at one or two schools, and be careful to account for how much easier it is to win at a “power 6” conference school when evaluating a coach’s past performance. These quantitative factors are in addition to the usual qualitative considerations, as this study can not quantify player development, charisma, or recruiting in any way other than through actual game results.

Two key takeaways from our analysis:

1. Coaches who are switching jobs often, presumably moving up the career ladder, seem to coach teams that perform better. On the other hand, coaches with more experience entering a new job tend to perform worse. These apparently contradictory points can be reconciled by considering that coaches who are talented are going to find a good job (one where they are successful and thus remain employed) after a certain amount of years. Coaches who are at one place for a long time and then fired and/or switched jobs can often be less talented. It can be presumed that a certain amount of years of head coaching experience are needed to assure that a coach has talent, but after a certain number of years, a coach’s talent is clear and his performance will plateau. Thus, great coaches generally have found their final destination after a certain amount of years, although our study does not consider the optimum amount of years of experience. A practical implication for ADs could be to hire coaches who have been successful at multiple stops and hot coaches climbing the ladder, while avoiding coaches that have lingered at positions for a long time (maybe accumulating wins) but underperforming.

2. When hiring a coach, ADs should take into account that mediocre coaches can perform better at a BCS school than good coaches at a mid-major school. Though they may still be less talented coaches, the difference in their performances can partially be accounted for by the program at which they were coaching. Also worth noting are the variables that were not deemed significant by the regression: 1. There is nothing in the data set that suggests that coaches perform better coaching at their alma mater. Maybe this was once the case, but the games is becoming more and more hybrid, with coaches and administrators switching often between institutions, and the study backs up the fact that the best candidate should be hired, regardless of what school he attended. This was also the case for the variable expressing whether the head coach coached at a place where he was previously an assistant. This consistency factor appears to add little to a coach’s success.

Also worth noting are the variables that were not deemed significant by the regression:

1. There is nothing in the data set that suggests that coaches perform better coaching at their alma mater. Maybe this was once the case, but the games is becoming more and more hybrid, with coaches and administrators switching often between institutions, and the study backs up the fact that the best candidate should be hired, regardless of what school he attended. This was also the case for the variable expressing whether the head coach coached at a place where he was previously an assistant. This consistency factor appears to add little to a coach’s success.

2. Age is also not a significant variable in this regression, which is shown in reality by the vastly different ages of the coaches in this year’s final four, with the youthful Shaka Smart and Brad Stevens joining the middle aged John Calipari and the older Jim Calhoun.

3. Years of assistant coaching experience was not deemed significant. This is surprising for several reasons. One would think coaches that have very little experience would not perform as well, but there is nothing in the data to support this notion. Also, one would assume that coaches who have been assistants for an eternity, never being hired for a head coaching position, were not hired because of their inferior quality and thus a large number of assistant coaching years of experience would be negatively correlated to success as a head coach. This however was also not the case. It can be assumed that this variable acts something like the head coaching experience variable: some base level of experience is needed at the assistant level, but after a certain number of years, if a coach hasn’t been hired to a better position, it is less likely that he is a the best choice as for a coach job.

Besides what we did and did not find, let’s also spend a moment on potential weaknesses in this study.

1. There is a high correlation (.8344) between years as a head coach prior to being hired and number of previous head coaching jobs held. The reason these are kept as two separate variables instead of combining them into one is because this study felt that there was the possibility that the variables had different effects on head coaching success.

2. The lack of accounting for the impact of player talent on coaching success. For example, if there are two teams with identical schedules and one team is comprised of All-Americans that are the best players in college basketball and the other comprised of average basketball players the team with much more talent on its roster will perform much better than the average team. The head coach of a team cannot affect the level of talent that he has to work with (besides recruiting), he can only attempt to maximize the abilities of the team he has. The coach of the team with superior talent needs only to arrive at practice and roll out the balls for his superiorly talented players and then he will appear to be very successful in comparison to other coaches.

This will lead to the perception that he is a more talented coach when, in fact, it is impossible to tell how much the coach impacts his team’s success and how much impact the players have on team success. It would have been incredibly difficult for this study to create variables that accounted for the talent level of the players on the roster. Also, there is very little data out there that allows for successful quantification of recruiting or player development ability directly, two of the most important facets of coaching. The best that can be done is to evaluate a team’s final results and hope to glean some useful information for them.