The Future of NCAA Pods that Almost Happened

Remember the plans to expand the NCAA field to 96 teams? While everyone was predicting doom and gloom, there was one benefit to the scrapped proposal. The new plan would have meant easier travel.

Right now the west coast is usually the land of misfit toys, the place where all the four and five seeds get sent. Consider the placement of the top seeds this year:

Spokane
4 Maryland
5 Michigan St.
4 Purdue
5 Texas A&M

San Jose
4 Vanderbilt
5 Butler
3 New Mexico
6 Marquette

Oklahoma City
1 Kansas
8 UNLV
2 Kansas St.
7 BYU

Milwaukee
3 Pittsburgh
6 Xavier
2 Ohio St.
7 Oklahoma St.

New Orleans
3 Baylor
6 Notre Dame
1 Kentucky
8 Texas

Buffalo
1 Syracuse
8 Gonzaga
2 West Virginia
7 Clemson

Providence
3 Georgetown
6 Tennessee
2 Villanova
7 Richmond

Jacksonville
1 Duke
8 California
4 Wisconsin
5 Temple

And this is not a one year trend. The Pac-10 was weaker last season, but if you look historically, the 4/5 seeds are much more likely to get shipped out west. The problem is that the best seeds get the spots closest to home, and in recent years teams in the East and Midwest have been more likely to get seeds 1-4. Meanwhile, while the WAC, MWC, and WCC have had some of the best teams in the country, those teams tend to be seeded 5-8.

But now consider one of the primary proposals for a 96 team tournament. The idea was to play the extra game on the Tuesday/Wednesday of the 2nd week. In other words, after the first weekend there would still be 32 teams left. And in the first week, instead of 16 four team pods, there would be 32 three team pods. The huge advantage of this is that more teams could be rewarded with shorter early round travel. Consider how this year’s field might have looked:

1 seeds – No change
2 seeds – 35 miles closer
3 seeds – 773 miles closer
4 seeds – 5550 miles closer
5 seeds – 4894 miles closer
6 seeds – 1042 miles closer
7 seeds – 3500 miles further
8 seeds – 3789 miles closer
Total - 12,583 miles closer

Spokane
8 Gonzaga – 1894 miles closer
7 BYU – 252 miles closer
7 Clemson – 1425 miles further
7 Richmond – 1707 miles further

San Jose
8 California – 2324 miles closer
8 UNLV – 600 miles closer
8 Texas – 1029 miles further
7 Oklahoma St. – 620 miles further

Oklahoma City
1 Kansas – No change
2 Kansas St. – No change
3 Baylor – 168 miles closer
3 New Mexico – 359 miles closer

Milwaukee
4 Purdue – 1404 miles closer
4 Wisconsin – 896 miles closer
5 Michigan St. – 1458 miles closer
5 Butler – 1682 miles closer

New Orleans
1 Kentucky – No change
4 Vanderbilt – 1471 miles closer
5 Texas A&M – 1258 miles closer
6 Marquette – 919 miles closer

Buffalo
1 Syracuse – No change
2 West Virginia – No change
2 Ohio St. – 35 miles closer
3 Pittsburgh – 246 miles closer

Providence
2 Villanova – No change
3 Georgetown – No change
4 Maryland – 1779 miles closer
5 Temple – 496 miles closer

Jacksonville
1 Duke – No change
6 Tennessee – 397 miles closer
6 Xavier – 296 miles further
6 Notre Dame – 22 miles closer

First, the top lines are barely impacted because they get their first choice of location in the current system. Now Ohio St. and Pittsburgh can join Syracuse and West Virginia in Buffalo, but there are few changes overall. But then the big gain comes for the teams given 4 and 5 seeds. Now virtually every one of these teams is 1000 miles closer to home, with virtually no negative consequence. A few of the seven seeds now get shipped out west to fill in the final slots. But there is a net gain for the NCAA because more of the quality west coast teams get to stay close to home such as California and Gonzaga.

For the first time in the pod system, the west coast pods would finally have decent representation from the Pac-10, MWC, WAC, and WCC. These regions typically only have a couple of local teams and now they would have several. In fact, these west coast conferences would be 5429 miles closer to home, almost half of the overall gain. Instead of the Pacific Northwest being the toughest ticket to sell out, Gonzaga would have owned the region for the last decade.

But more importantly, more teams would get to play close to home in all parts of the country. With the top 8 seeds slotted 12,583 miles closer to home, many more fans could drive to see their team play. Right now, fans that want to travel to see their team have to make reservations to fly across the country on very shot notice. And that can be very expensive if you do not have a ton of frequent flyer miles.

Of course the disadvantage is that fans traveling to see the protected seeds would only get to see one game. But for many fans, one near-to-home, weekend game would be the perfect cap to the season.

And for fans that want to see multiple rounds, it gives them more time to make their reservations for the round of 32. The round of 32 would have been at least 9 days after the brackets were announced giving people enough time to make plans to fly to a now 8-team regional final.

I know this advantage was not going to convince anyone that a 96 team tournament was a good thing. But if you believe 68 teams is just the first step towards further expansion, I hope the second Tuesday plan continues to be discussed as a possibility.

Can a role player catch a break?

Besides sports, I obviously have a crazy love for numbers and spreadsheets. Thus I had to smile this weekend when my wife decided to create a spreadsheet categorizing her “mostly inexpensive” shoe collection. Here’s what I’ve learned from the database so far. Sandals and flip flops seem to dominate. Also, purple shoes were always the favorite, but black shoes are just as numerous. And brown shoes have a surprisingly high count.

In basketball news, I’ve been meaning to compile the bench utilization data for some time. And I finally got around to putting it together. The next table lists the average percentage of bench minutes for each coach from 2007-2010. APBM = Average percentage of bench minutes. (Kenpom.com only has bench utilization data back to 2007 so we only have 4 years of data at most for each coach.) For the 347 coaches for the 2011 season, 318 of them have at least 1 year of data. Scroll up or down to see the full table.



There are not a lot of surprises in these numbers. Mike Anderson, Tubby Smith, and Bruce Pearl all give their young players a lot of playing time, in part because they use high-energy pressure defense. But it seems like a larger number of BCS coaches stick to very tight rotations. Guards are less subject to foul trouble so perimeter-oriented-teams like Marquette, Notre Dame, and Ohio St use their bench less frequently. Also, some of the back-cut systems that rely on precision and execution also rely heavily on their starters. See Herb Sendek’s Arizona St. team.

I also want to emphasize that playing your starters major minutes can be a winning strategy. As Mike Krzyzewski and Billy Donovan have shown, you can win a national title by finding a tight rotation of elite players and sticking with them. But Roy Williams has also won a national title while running an up-tempo attach and using his bench more frequently. So it is not really a question of whether fewer bench minutes is bad or good. Both can work with the right players.

The key is simply finding what works for the coach. Rick Barnes at Texas has traditionally had a tight rotation, but the embarrassment of riches last season simply led to an embarrassment of an inconsistent lineup. Barnes played his bench way more minutes than normal in 2009-2010 and the season did not live up to expectations.

I am also intrigued that many of the new coaches are such extreme outliers. Jeff Bzdelik’s precision offense at Colorado used a very short rotation and Fran McCaffery also shined with a few star players at Siena. On the flip side, Tad Boyle, Kevin Willard, Mike Rice Jr., and Dana Altman all went deep on their bench with their previous teams. Altman’s numbers are particularly stunning as he used his bench almost half the time the last three year’s at Creighton. Now part of that was the fact that Altman could not find a consistent rotation the last few years. But it also suggests that if you are a recruit and you want to play next year, it would not be a bad idea to give Oregon a chance.

In general, I wonder how important bench utilization is to recruiting and keeping players in the program. Consider these examples: Under John Thompson III, Georgetown has frequently been able to recruit star players, but has lost numerous bench players to transfers. Conversely, Minnesota has not been able to matriculate elite recruits, but Minnesota seems to find an endless supply of decent three-star prospects. Could bench utilization explain some of this? While Georgetown’s John Thompson III plays his starters heavy minutes, Minnesota’s Tubby Smith will gladly play a rotation of 11 players even in March. I think this difference can mean a lot to a recruit. If you are a star player and you go to Georgetown you are going to get major minutes and plenty of exposure. But if you are a borderline prospect, you may never get off the Georgetown bench after December. On the flip side, if you are a starter for Minnesota, Tubby Smith will not hesitate yank you if you make a couple of idiotic decisions in February. But even the weakest scholarship player will still get on the court in conference play. There is a lot that enters in a recruit's decision to choose a school, but as the July recruit evaluating period passes by, I wonder how important this type of factor can be to a recruit's final decision. Because for many recruits, playing time is the best thing a coach can offer.

The Akron Grill or the Cheescake Factory?

Wow, I posted three straight weekends, and since there is some benefit to readers from being predictable, here's another post. (Sadly the tempo free stats will be getting a DNP - coaches decision this week.)

“A superstar player decided to take less money and sacrifice individual glory to try to win championships, but it’s not OK because he’s not having to work hard enough to win them, so they don’t count as much. To announce his decision, he created a special TV program that wound up generating millions of dollars he donated to the Boys & Girls Club, but he’s a bad person because it was egotistical.”-Kevin Pelton points out the irony at Basketball Prospectus

“Big freakin deal, Cleveland. Signed, Seattle.” -Bill Simmons reader comment on ESPN

I guess the fact that these were my two favorite comments means I don’t have a lot of sympathy for Cleveland fans.

Part of that is probably just pettiness on my part. As long as the Vikings are near the top of Bill Simmons’ Levels of Losing, I just don’t have a lot of empathy when bad things happen to other cities. Everyone says Cleveland has not won a title in 50 years. But if you grew up in Cleveland and have not cheered for Ohio St. winning a national title down in Columbus, then that is your own fault. (Sort of like being a Cubs fan and not fully enjoying the White Sox recent World Series.) I just do not believe that Cleveland fans have had nothing to cheer for in their lives. Perhaps if the Vikings were two-time Super Bowl Champs, I’d be a bigger person, but I’m not.

But I think my reaction is a little more than my personal lack of empathy. I think part of it is a general acknowledgement of what pro sports have become. The days of players spending their whole career with one team are over. ESPN has a list of “lifers” in MLB, long-term players that have stayed with one team. And the list is incredibly short. I simply no longer hold it against players for changing teams. When Kevin Garnett won a title in Boston, I smiled. And when Joe Mauer signed with the Twins I was happy, but I didn’t feel he was obliged to do so as a hometown player. If Mauer had gone the way of Johan Santana and moved to New York, I would not have batted an eyebrow.

And maybe that is why I have grown to like college so much more. Players are only making short-term commitments. We know that even under the best of circumstances they will be gone in four short years. But no matter where they go and no matter who they become, they will always be alumni of the university fraternity. Dee Brown and Deron Williams will never have another shot at a national title at Illinois, but they will always be Illini.

Moreover the spontaneous support of team is so much more genuine with a university. I remember when Illinois lost in the national title game, the fans held an unplanned pep rally to congratulate the returning team. It was an unbelievable experience.

But watching part of the extravagant welcoming ceremony down in Miami where Wade, Bosh, and LeBron received keys to the city, none of it felt genuine. Perhaps it was the callous celebration when nothing had been accomplished yet. But I think I was more offended by congratulating people for making a business decision.

When you graduate from college, people celebrate. When you switch jobs to take advantage of a new opportunity, you go out and have a nice quiet dinner with your immediate family.

Which New Hire was the Biggest Mistake?

Two weeks ago I listed some doubts about recent coaching hires:
1) Iowa St.’s Fred Hoiberg – Can he really succeed with no college coaching experience?
2) Clemson’s Brad Brownell – Is it a bad sign that he did not make the NCAA tournament the last three years at Wright St.?
3) Colorado’s Tad Boyle – Can a small conference coach successfully jump directly to a BCS league without a stop at a mid-major first?

Today I want to see if we can learn anything from the historical record. One outcome to examine is wins and losses. For example, how many games have Big Sky coaches won after they jumped to a BCS league? Unfortunately, we have a limited sample of hires, and each school’s situation is unique. As an example, Bill Carmody left Princeton for a Northwestern team that has never made the NCAA tournament. Shortly thereafter, John Thompson III left Princeton for a Georgetown team with a rich history and NCAA title. It might not be fair to label Carmody’s tenure a failure just because he has fewer wins per season.

Instead today I am going to focus on whether coaches are meeting expectations. To do this I will use the “termination” model I presented last week. The basic idea is simple. If a coach keeps his job, he is meeting expectations. If that coach is fired, he is not meeting expectations. And I can ask three questions that may help us to evaluate former hires:

1) When a BCS school hired someone who was not a D1 head coach, was he more likely to get fired?
2) When a BCS school hired someone without a recent NCAA appearance, was he more likely to get fired?
3) When a BCS school hired someone directly from a small conference, was he more likely to get fired?

Today I am focusing on only BCS coaching hires made after the 1984-1985 season. This limits my sample substantially to only 233 coaches. This includes
-26 from small schools
-48 from mid-majors
-74 from high majors and other BCS schools
-85 from the assistant coaching ranks, the NBA, unemployment, or non-D1 employment

When a BCS school hired someone who was not a D1 head coach, was he more likely to get fired?

The first table essentially presents the raw survival data. The blue data are hires of D1 head coaches. The red data are hires from assistant coaching ranks, the NBA, unemployment, or non-D1 employment.



As you may remember from last week’s post, the format of my database includes a number of interim head coaches who are usually assistants. This leads to a large peak in assistant coaches who get fired after 1 year and a large drop in the red line at year 1. But since these are not official hires, I do not want them to skew the results. Thus I’m going to drop all one-year coaches and estimate the rest of the hazard curve. The model also includes controls for NCAA appearances, as discussed last week.

The next table shows an estimate of the probability a coach will be fired at any point in time. Again, the blue data are hires of D1 head coaches and the red data are the other hires.

The results are only borderline statistically significant, but the results do match expectations. Coaches hired from the NBA or assistant ranks, that have not been D1 head coaches lately, are more likely to struggle and be fired.

When a BCS school hired someone without a recent NCAA appearance, was he more likely to get fired?

Next I include a control for whether the coach made the NCAA tournament in the year prior to taking their current job. And the graph looks very similar to the graph above. But in fact, the result is driven by the graph above. It is the lack of success by assistants and NBA types that makes previous NCAA tournament appearances meaningful.

When I contrast only D1 head coaching hires, the tournament effect disappears. For D1 head coaches that move to new programs, whether they made the tournament the previous year or not has no measurable effect on their future job security.

Now this doesn’t mean that any D1 coach could just step into a BCS job and do well. But it does say that the candidates that get hired without a recent NCAA tournament appearance have demonstrated their ability in other ways. Brad Brownell may not have that signature NCAA tournament appearance lately, but he’s proven he can win at Wright St. regardless. And Clemson fans should not worry that a 2nd place Horizon league finish is a permanent black mark on their new coach.

I tend to think people jump on the bandwagon a little bit too much based on one or two tournament upsets. I prefer to look at the larger body of work for any coach. But there is some information in an NCAA tournament run. Coaches that make the NCAA tournament and win in the tournament do demonstrate something about their ability to build a winning team.

And in fact when I control for NCAA wins in addition to appearances, a run in the tournament does predict future success to some degree. But based on my small sample and the large variation in coaching outcomes, the results remain statistically insignificant.

When a BCS school hired someone directly from a small conference, was he more likely to get fired?

Next I break out small majors, mid-majors, and high majors and see if any groups are more or less likely to keep their jobs. I find that there is not a statistically significant difference between the three groups.

To directly address my small school question, here is a graph of the raw survival data comparing small schools (in red) to the others (in blue.)

Again, this does not mean that any small school coach could step into a BCS job and thrive. But the small school coaches that are selected are often quality candidates.

And believe it or not, you can succeed even if you come out of a small conference and did not make the NCAA tournament. Did you know that both Mike Montgomery and Ben Howland were both initially hired to BCS leagues directly from the Big Sky conference? And did you know that neither played in a post-season tournament the year before they were hired? Tad Boyle seems like a bit of a reach, but if he succeeds after being pulled from Northern Colorado, it would certainly not be unprecedented.

More thoughts

I still question the Boyle hire for another reason. In four years at Northern Colorado, Tad Boyle’s teams have played mostly atrocious defense. I realize the defense improved somewhat in his final year, but I think a quality defensive coach would have made more of an imprint in four years.

But is this fear valid? This is also a testable hypothesis. Do coaches with horrible adjusted defense at their previous school struggle in BCS leagues? Sadly, we only have seven years of tempo free stats on kenpom.com, so we do not have a large enough sample size to do this issue justice.

Also, while the above numbers make the Fred Hoiberg hire appear to be the most suspect, that doesn’t necessarily mean anything. Just because certain non-traditional hires have failed in the past, does not mean any specific hire will not work out. Any of these coaches can still prove to be great or prove to be mediocre.

Boring Data Notes:
-When defining mid-majors, I use a variation of Kyle Whelliston’s red line. Small schools are in conferences with avg MBB budgets under 1.4 million, mid-majors are from 1.4-2.4 million, and high majors are 2.5 million and above.
-I forgot to mention it last week, but much of the data is censored. Obviously we do not have data after 2010, so we do not know how things will end for many coaches. But the model accounts for this. It only uses coaches to estimate the shape of the curve in the years for which the coach has data.
-Also, I am only estimating the probability of being fired, not the probability of taking a new job voluntarily. Coaches that voluntarily leave are also treated as censored.