Earlier this spring I presented my “way-too-early” projections for seven major conferences. Due to time and space constraints, I never published my projections for the A10 and CUSA. But with the announcement that VCU will be joining the A10 for the 2012-13 season, I thought it would be a good time to share my projections for that league.

These projections remove all graduating seniors, announced transfers, and early entrants from rosters. My transfer information comes from Jeff Goodman’s list as of May 14th. In these projections, I use the tempo free player statistics to predict how the margin-of-victory numbers will change between seasons. Then I use that information to predict the 2013 conference standings. For now I assume the A10 sticks with a 16-game schedule next season.

PW = Predicted Conference Wins

PL = Predicted Conference Losses

P% = Percentage of Possessions Returning – (Possessions are a more powerful predictor of future offense than minutes, although the model includes returning minutes as well.)

The remaining column headings were described in a previous post, but for a refresher, scroll to the bottom of this page.

VCU brings every key player back except Bradford Burgess. I don’t want to understate how important Burgess was to the Rams. He led the team in minutes, shots when on the floor, and he was one of the two most efficient players on the team. He will clearly be missed. But the four A10 teams that made the NCAA tournament also lost key players. Xavier lost Kenny Frease and Tu Holloway to graduation and Mark Lyons to transfer; St. Bonaventure lost Andrew Nicholson; Temple lost Ramon Moore, Michael Eric, and Juan Fernandez; and St. Louis lost Brian Conklin. None of those players will be easy to replace. I’d feel much more confident if VCU was bringing in a strong recruiting class, but Jordan Burgess was not a consensus Top 100 recruit.

Quite frankly this projection isn’t as much about elite talent as it is about Shaka Smart’s ability to bring his players together the last few years. His team had the top steal rate in the nation last season and as long as he is teaching a unique brand of full court basketball, he can win in the A10. His margin of victory numbers would have been second in the A10 last season, and his team returns 82% of its possessions. That’s a recipe for success. The model likes VCU to finish 3^rd in the A10 next year.

I’m not making a projection for Butler here, because they won’t be in the league until 2013-14, but if they were in the A10 next season, my model would have them at 10-6, right in the middle of the pack. Butler had a disappointing year by their new lofty standards because they simply couldn’t score. But the addition of one of the best three point shooters in the country (transfer Rotnei Clarke) as well as Kellen Dunham, a consensus Top 100 recruit, should help turn the offense around.

I’m looking forward to an annual battle between VCU and Butler where they re-air the highlights of the 2011 NCAA tournament, but the A10 absolutely must improve its television deal. The last few years this league has had a ton of great players who simply haven’t gotten the publicity they deserve nationally because they haven’t been on TV. St. Joseph’s Carl Jones and Massachusetts Chaz Williams are incredibly exciting players to watch, but I rarely saw their highlights on ESPN last year. The good news for those two players is that both St. Joseph’s and Massachusetts bring back their primary rotation and both teams should be in the hunt for the NCAA tournament next season.

I’m a little surprised Richmond isn’t picked higher by the model. Last year’s seniors all had very inefficient seasons and the 1.039 mark in the relative value column says Richmond is bringing back the exact right offensive players. But the Spiders had serious problems on defense last year and it is hard to predict a big turnaround. It isn’t that Chris Mooney doesn’t know what he is doing, but this really appears to be a “size” issue more than an effort issue. Most people remember the guard play during Richmond’s stellar Sweet Sixteen run from a few years ago, including Kevin Anderson’s amazing clutch shot against Vanderbilt. But that team was anchored in the middle by 6’10” Justin Harper, and so far Mooney hasn’t quite been able to find the right replacement in the middle.

Here is why my model likes St. Louis to win the league. Despite finishing second in the standings, St. Louis had far and away the best margin-of-victory numbers in the conference last year. Their defense was Top 10 caliber, and while Conklin will be missed, the biggest factor was having Rick Majerus on the sideline. Majerus reportedly spoke to SMU about their coaching vacancy this spring, but the fact that he stayed at St. Louis should mean the Billikens will have an elite defense once again. And in an A10 without any dominant teams, that should be the difference.

The model currently projects Xavier to go 10-6 in the A10 next season which would be the same conference record as this year. The model isn’t saying that this year’s team is as good as last year’s team on paper. What I am saying is that the Musketeers significantly under-achieved in 2012 and still have a lot of talent. Dezmine Wells should be back, and at times he looked like Xavier’s best player last year. Transfer Isaiah Philmore is a fabulous scorer. And elite PG recruit Semaj Christon should help lessen the blow of losing Tu Holloway.

Of course Memphis is the league favorite because they have the most talent. As I noted last fall, no non-BCS team recruits like Memphis and they will finally be playing in a BCS league in 2013-14. Until then, anything short of another league title will be a disappointment.

Point guard AJ Rompza graduates, but Central Florida hopes that one of two transfers will fill the void. The team adds Calvin Newell from Oklahoma and CJ Reed from Bethune Cookman. Newell might be the more familiar name, but Reed’s statistics at Bethune Cookman were fantastic and he might be the better player. Regardless of who wins the job, they will have three prolific scorers to feed as Isaiah Sykes, Keith Clanton, and Marcus Jordan all return.

If you are looking for a sleeper pick, consider UTEP. The Miners lose two starters but the team gave a lot of minutes to freshmen last year (particularly Cedrick Lang and Julian Washburn) and if those young players make a big “sophomore leap” in production, UTEP could be a surprise.

SMU is tough to project. The problem is that I don’t have any college data for Larry Brown and so it is hard to give him credit for what he can do on the sidelines. Normally when a veteran coach takes over a bad team, he will focus on improving the defense first. But SMU was actually a defensive-minded team last year; it was that the offense that was dreadful. And the offense isn’t going to get substantially better until the talent level of the team is upgraded. Larry Brown’s staff has been hard at work adding transfers to fill that gap, but the goal seems to be to build towards the first year in the Big East, not this season. Sure Illinois transfer Crandall Head might be eligible mid-semester, but will Larry Brown even waste a year of eligibility by playing him in the spring? I won’t be surprised if SMU does a little better than 4-12, but on paper this looks like an offensively challenged team.

Having said all that, a large reason SMU’s offense was dreadful was because SMU’s offensive rebounding was off-the-charts terrible. Perhaps by focusing on those types of skills, Larry Brown can improve SMU’s offense. London Giles was a pretty solid shooter and Jalen Jones has some skills, so the team isn’t completely devoid of hope. But if they do manage to get to .500 in CUSA, Larry Brown deserves credit. It shouldn’t be the expectation with this team.

Overall, Houston and SMU should be thankful they won’t play their first Big East game for 19 months, because neither team is ready. On the other hand, Memphis, Temple, and UCF would be competitive in the Big East this season. UCF might not have a winning record in the Big East, but they wouldn’t be a laughingstock with this year’s lineup.

Column Headings:

PW = Predicted Conference Wins

PL = Predicted Conference Losses

FrP% = Percentage of Freshmen Possessions

T10Fr = Consensus Top 10 Freshmen Recruits

N100 = New Recruits Ranked 11-100 on the Roster – (This includes transfers and redshirt freshmen.)

Total = Total RSCI Top 100 high school recruits on the roster

NC = New Coach

RV = Relative Value = Offensive Rating of Returning Players, Incoming Transfers, and Players Returning from Injury (like UNC’s Leslie McDonald) divided by the Offensive Rating of Last Year’s Roster

MOV12 = Opponent Adjusted Margin-of-Victory in 2012 (see Pythag. rating on Kenpom.com)

The older I get, the more I see that one of the things I love most about sports is the variety of it, the diversity of it and the CHARACTERS. Men’s tennis is at its best in many years because, for the first time in a long time, the top three or four players all have wildly different styles. The Tim Tebow story was fun on so many levels, but one of those levels was that he was just SO DIFFERENT in how he played — I’d say we are entering a great time for quarterbacks, because Tom Brady and Aaron Rodgers and Eli Manning and Drew Brees and Michael Vick and Cam Newton and Tebow and others are not really alike at all.

-- Joe Posnanski

As a basketball fan, I’ve never understood the division that exists between fans of the NBA and the NCAA. While the NBA has the best basketball players in the world, March Madness is compelling in its own right and as entertaining as anything that happens on the professional level.

In the NBA, the owners of the 30 franchises consider turning a profit and getting an equal shot at the top players a right, regardless of how well (or how poorly) they run their organization and the respective size of their fan-bases. Since every losing team is a few ping pong balls from the rights to a LeBron James, Kevin Durant or Dwight Howard, personnel determines scheme in the NBA.

In contrast, the vast majority of the 344 Division I programs in college basketball have little chance of ever receiving a commitment from a McDonald’s All-American. But instead of petulantly trying to sabotage the sport in a misguided effort to legislate fairness, schools try many creative ways of leveraging the talents of the players they can recruit. As a result, scheme determines personnel in the NCAA.

At Syracuse, Jim Boeheim has made a Hall of Fame career out of running a contrarian scheme, in his case an aggressive 2-3 zone. The Orange traditionally have rosters full of “1.5’s”, 6’3+ combo guards lacking the quickness to defend elite PG’s and the size to defend SG’s, and “3.5’s”, 6’8+ combo forwards lacking the quickness to defend elite SF’s and the size to defend PF’s. However, because Syracuse never plays man defense, the athletic deficiencies of their players are minimized.

So while nearly every NBA team runs a fairly similar system of isolations, pick-and-rolls and man defense, an incredibly diverse array of styles can be found in the college game. On one end of the spectrum, teams like Missouri play four guards and pressure the ball 94 feet for 48 minutes, on the other, teams like Wisconsin run a deliberate motion offense, trying to minimize the number of possessions and shoot at the very end of the shot-clock.

In the NBA, the players are too good for the “40 Minutes of Hell” system (which Mike Anderson has brought to Missouri and Arkansas in the last few years) to be successful. Like Mike Leach’s bizarre pass-happy offense in college football, Anderson’s system, which he learned as a member of Nolan Richardson’s staff in Arkansas in the 1990’s, has philosophical holes that professional athletes can exploit. Nevertheless, that doesn’t make them any less entertaining on the collegiate level.

And with 68 teams set to compete in the NCAA Tournament, there are a lot more surprises in the college game. Even programs ranked in the top-15 like Murray State have barely been on national TV this season.

We have a pretty good idea of how teams like the Pacers and the 76ers match up with the top of the Eastern Conference but not whether an undersized Murray State squad can handle the size of an elite team from a Power Six conference. It’s an open question how Isaiah Canaan’s speed and athleticism translates outside of the Ohio Valley Conference. Non-conference play in college basketball generally ends in late December, so it’s almost impossible to gauge how younger teams like Texas, Washington and Tennessee who have found their groove in the last two months will fare in March.

In the NBA, it’s hard to envision a scenario where Chicago, Miami and Oklahoma City aren’t three of the final four teams left in the playoffs. In the NCAA, as many as two dozen teams have a legitimate shot at making a run at the Final Four.

Of course, in terms of entertainment, none of this makes the NCAA necessarily better or worse than the NBA, just different. But, as Posnanski writes, there’s something to be said for the concept of “different” in the modern sports world. Basketball fans of all stripes should enjoy March Madness; the NBA will still be here in a few weeks.

This weekend Michigan St. beat Ohio St. by forcing Jared Sullinger to commit 10 turnovers, Texas Tech beat Oklahoma to become the final BCS team to win a conference game, Alabama head coach Anthony Grant suspended his four best players for a violation of team rules in a loss to LSU, and Texas had a huge comeback to beat Kansas St.

There were plenty of exciting games, from Louisville’s comeback against West Virginia to UNLV holding off San Diego St. on a last second steal. But the heart of the season is sort of an awkward mix. There aren’t very many surprises any more. (I already knew Florida and Creighton didn’t play defense.) And we are too far from Selection Sunday to make blanket statements. (I’m pretty sure Pittsburgh’s loss at Seton Hall means their NCAA hopes are over, but I’ll feel a lot more certain in a couple of weeks.) So rather than focus on what happened this weekend, let me spend a little time talking about some player data.

Understanding Breakout Offensive Players 

College basketball fans might think that the major contribution of Dean Oliver is the creation of tempo free player statistics. But the “tempo free” part is actually a minor part of his ORtg formula. His key contribution was figuring out how to give players credit for assists and offensive rebounds. Clearly on a possession, the player who scores the basket might not be the only player who deserves credit for the points.

Let’s take North Carolina as an example. In this table ORB=Offensive Rebounds, AST=Assists, PTS=Points Scored, and PP=Points Produced.

(Through Wed. Feb 8^th)

In terms of actual points scored, Kendall Marshall is a relatively quiet scorer in North Carolina’s rotation. But because Kendall Marshall assists on so many baskets, in Dean Oliver’s formula, Marshall gets a lot of credit. When you look at the PP (points produced) column, Marshall gets credit for almost 100 more points on the season in Oliver’s formula. Basically everyone else has to share credit for their points with Marshall. So everyone else has lower PP relative to PTS. Offensive rebounding numbers work the same way. Because Zeller grabs more offensive rebounds than Harrison Barnes, he gets some credit back.

ORtg just takes PP and divides by the number of Possessions each player uses. If you produce 115 points and use 100 possessions, your ORtg is 115.

If you want to try and back out the “weights” for assists and offensive rebounds in Oliver’s formula, you cannot. Oliver’s formula isn’t linear. Also, if PP isn’t complicated enough, Possessions also must give credit for things like assists and offensive rebounds. If you check out Dean Oliver’s book “Basketball on Paper” from the library, you’ll see the full formula fills up about a page of text and takes a chapter to explain. It is ridiculously complicated, but it does do an incredible job assigning credit based on the stats in the box score.

If you’ve been following college basketball for awhile, you probably know who the breakout players are this season. But my goal today is to tell you why those players are breakout stars. At first, I thought about generating these types of tables:

Biggest Jump in Percentage of Possessions Used

(Table includes only players with at least five games and a minimum of 25 possessions in both seasons in a top 18 conference.) 

When 80% of Penn St.’s production graduated, Tim Frazier became a high volume shooter. One of Ken Pomeroy’s classic observations is that role players rarely become high volume shooters, but when teams lose high volume shooters to graduation, it sometimes happens. I could also create this type of table:

Biggest Jump in ORtg

(Table includes only players with at least 5 games and a minimum of 25 possessions in both seasons in a top 18 conference.)

Jaquon Parker’s improvement in efficiency for Cincinnati seems very important, but has anyone even heard of Fred Gulley? (Hint: He transferred out of Oklahoma St. mid-year to attend Arkansas.) But because Gulley rarely played in either season, his explosion in ORtg isn’t terribly important. Now, I could make the list look a little more sensible with some strategic cut-offs. For example, I could require that players have over 40% of the team’s minutes in both seasons, ect. But that can be a bit of a puzzle because often breakout players go from few minutes to major minutes. 

And that’s where the PP concept from the beginning of this article comes into play. Why not take PP per Game and see how and why that has changed for various players. (Remember this isn’t literally Points Per Game, this is the Dean Oliver concept of Points Produced per Game.)

Taking these numbers, who are the Top 20 breakout players this year? I not only identify the breakout players, I can also explain why their stats have improved:

ChangePPG: Total Change in Points Produced Per Game (with credit re-assigned for assists and offensive rebounds.)  This has three components:

ChangeORTG: Given the players current role, how does the change in ORtg from last year impact the player’s Points Produced Per Game?

ChPossUsed: How does the change in percentage of shots taken (really possessions used) impact the player’s Points Produced Per Game?

ChPT: How does the player’s playing time (and team’s tempo) impact the Points Produced Per Game?

Top 20  Breakout Players

(Table is limited to Top 18 conferences.)

-With so many players graduating from San Diego St., Jamaal Franklin shoots a lot more often, and he plays a lot more minutes. His ORtg has slipped slightly, but that has only minimally held back his stats.

-Meyers Leonard isn’t necessarily being all that more aggressive on the floor, but he is converting at a higher rate, and playing more than last year.

-Thomas Robinson is no more efficient than last year, and while he is a little more aggressive in his shot selection, his main improvement in PP has come from additional playing time. (In other words, imagine what he could have done last year if he wasn’t stuck so low on the depth chart.)

Now, besides looking at the top overall improvements, we can also identify players where an improvement in ORtg has been the most critical:

Critical Improvements in Efficiency

(Table is limited to Top 18 conferences.)

Just to emphasize what this list means, this isn’t the players with the biggest improvements in ORtg, this is the list of players with big improvements in ORtg who also use a lot of possessions for their team. 

Indiana’s Matt Roth improved his ORtg from 131 to 165 (which is mind-boggling), but he plays and shoots so rarely that his offensive improvement is only worth about 0.8 PPG to Indiana. Instead, Will Barton’s improvement in efficiency is much more important. Will Barton’s ORtg has improved from 99 to 114 and given his role in Memphis’ offense, that translates to about 2.4 PPG.

More to come on Thursday!