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)

Trent Johnson accepted the head coaching job at TCU this spring, a program transitioning to the Big 12. Johnson previously spent four years at Stanford and four years at LSU. Because the last three years at LSU were less successful, Johnson may have been looking to change jobs before he lost his job. But in looking back at his experience at Stanford and LSU, I am not convinced he was a worse coach at LSU.

The first thing I notice when looking at the players he recruited at both schools is how big a difference one or two players can make. Johnson’s recruiting at LSU was not substantially worse than his recruiting at Stanford, but Johnson was never able to recruit a superstar freshman to LSU of Brook Lopez's caliber. Brook was a high volume, efficient scorer, and the only thing that stopped him from playing more minutes his first season was an early season surgery. But other than Brook Lopez, Johnson hasn’t had any program changing recruits at either school. Anthony Hickey and Robin Lopez were fine freshmen, but they were not truly elite players in their first season.

One place Johnson caught up on recruiting at LSU was in accepting transfers:

In terms of player development, Johnson’s numbers aren’t that different at the two schools. In the next two tables, I look at changes in playing time and efficiency for all returning players. For inherited players, the change in minutes is the difference between the most recent season and the last season under the previous coach. For recruited players, the change in minutes is the difference between the most recent season and the player’s debut season with the team.

I also compare the change in ORtg for the same time period. But since shot volumes can impact efficiency, I adjust this based on the rule that 1% more possession’s used is worth 1.25 points of efficiency. Thus a player that moves from shooting 20% of the time to 24% of the time and keeps the same efficiency tallies a five point increase in his ORtg.

Once again, the player development numbers are not particularly different at the two schools. In both cases, Johnson has been able to take some players who were incredibly inefficient as freshmen (see Mitch Johnson at Stanford and Aaron Dotson at LSU) and turn them into passable major conference players. And plenty of other players from Chris Hernandez to Chris Johnson regressed slightly under Johnson.

So if Johnson was a similar recruiter at the two schools and had similar success at player development, why was his offense so terrible at LSU? There are really two reasons. First, Johnson had substantially more turnover at LSU. Some of that was by design after his recruiting classes flopped miserably, but with little continuity, his players were never put in a position to succeed.

But equally important was the difference in what he inherited. At LSU, Johnson inherited two senior stars (Marcus Thornton and Chris Johnson) and few other efficient players. And once Thornton and Johnson graduated, LSU’s performance fell off a cliff.  But the team he inherited from Mike Montgomery at Stanford was much deeper with efficient players throughout the lineup.

But here is the ultimate problem for Trent Johnson. He does not appear to be recruiting at the level consistent with an NCAA tournament coach. He seems to do a fine job developing players, but he needs to start with good players for that to be an NCAA tournament equation.

And at TCU, despite huge strides in the last year under Jim Christian, there simply isn’t the kind of talent that will typically make the NCAA tournament in a major conference. Even if Johnson does a great job bringing his current players along, that won’t be enough for an NCAA bid. TCU needs a coach who can upgrade the caliber of player in the program, and right now Johnson doesn’t appear to have the track record to do that.

A lot of coaches can make up for a lack of talented offensive players by teaching their players to play elite defense. For example, Bruce Weber and Frank Martin are always going to be on the NCAA tournament bubble by virtue of their defense alone. But Johnson isn’t quite that consistent at teaching defense:

One thing that really seems to make a difference for Johnson’s defensive scheme is having a 7 footer in the middle. His Stanford teams were at their best when they had Brook or Robin Lopez in the middle. And even this year, while Justin Hamilton was not an elite shot-blocker, his size in the middle frustrated numerous LSU opponents. Probably the most likely avenue for Johnson to succeed at TCU will be to find a few more 7 foot post players to anchor his defense, and hope to find a few special offensive players.

Bottom Line

Joining a BCS league can be a recipe for a complete disaster. Last year, Utah had a horrendous season because the caliber of talent on hand was not ready to compete in the Pac-12. (And it was a down year in the Pac-12). I think Johnson is skilled enough to keep TCU from having a disastrous season. He will bring his players along and he now has the experience to motivate players through a difficult season.

But TCU fans will be excited about the jump up to a major conference and expectations will be raised. Johnson won’t be expected to make the NCAA tournament next year, but he will be expected to make the tournament in three or four years. And the historical numbers suggest Johnson will need substantially better recruiting to make that happen.

This summer is the 4^th season that I am predicting next year's standings based on the tempo free player statistics. Last year my preseason predictions model appeared in ESPN the magazine, and my most recent 2013 predictions were featured on CBSSports.com. This summer I hope to make my predictions methodology more transparent to the reader, and as always I am looking for ways to improve the model. Let’s start with a fact that I mention rather frequently:

(Data are from 2003-2012 seasons, all D1 teams)

On average, the biggest improvement in efficiency happens between a player’s freshman year and sophomore year. Of course just looking at the raw numbers can be a bit misleading because of players transferring out. Typically extremely inefficient players either transfer to smaller programs or stop playing D1 basketball completely.  But if we limit the data to 4-year players, the pattern is still there:

Returning freshmen typically show the greatest improvement. Keep in mind that this is the average and that individual development patterns can vary widely. I will try discuss the unpredictability of player development in a future column, but the main point I want to emphasize is that this is not simply a case where everyone gets a little better every year. What happens is some players show dramatic improvement, some players tread water, and a few players get worse.

Not surprisingly, this also shows up in the team data. Teams that return more freshmen minutes are more likely to improve the following season. To my knowledge, my preseason predictions model is the only model that incorporates the importance of freshmen development.

In many ways, freshmen development is the kind of fact that is difficult to wrap our heads around when writing preseason predictions. When we predict the standings in a conference, we like known commodities. We like to write about can’t miss recruits and established players. We don’t like to talk about probabilities. West Virginia returns four freshmen who saw significant playing time last season (Jabari Hinds, Gary Browne, Aaron Brown, and Keaton Miles). None of those players was particularly dominant and that means that a lot of people are going to write West Virginia off next season. But the probability is that at least a couple of those players will be substantially better. I just can’t tell you who.

Different Development Curves?

One of the things I have been thinking about lately is whether we need to think more about the development curves for different types of players. Last summer Drew Cannon wrote about how big men develop more slowly than guards.

But last week when I was writing a look-back column on Frank Martin, I was thinking how we should really break out other types of players too. In particular, three point shooters are significantly more likely to be efficient off-the-bat, and significantly more likely to be efficient throughout their careers.  Conversely point-guards without an outside shot are typically terrible as freshman, and while they improve they rarely match the efficiency of other players:

I define a player as a Three Pt Shooter if he takes more than 4 threes per 40 minutes played in his career. The definition is based on attempts, not makes. I define a player as a Non-Shooting PG if he earns at least 4 assists per 40 minutes played in his career. This assist cutoff was chosen to be restrictive enough to exclude players like Henry Sims, but that also means it excludes some guards who are typically viewed as point guards. I also broke the data down to look at combo guards, guards who have an outside shot and set up their teammates. It turns out that passers who have three-point range tend to have similar efficiency to spot up three point shooters and thus I grouped all three point shooters together in the table.

This table is one of the key reasons people have criticized ORtg. Players that are spot-up three point shooters tend to be more efficient even though they might not be the most valuable players on the floor. Some people have argued that Dean Oliver’s formula should be adjusted to give the other teammates credit for getting open three point looks. Most analysts handle this by concluding that ORtg is a stat that requires context (such as Usage rates) in order to interpret it. But you can’t argue with the connection between three point shooting and team efficiency. Teams as varied as Florida and Wisconsin have proven that by taking and making a bunch of threes you can have an efficient offense. And freshmen who shoot threes are usually the most efficient incoming players.

Forwards

Over half of the D1 players with multiple seasons can be described as passers or three point shooters. The rest are typically described as “forwards”. For this group you can typically define efficiency based on whether the players grab offensive rebounds or not:

I define a forward as an Offensive Rebounder if he grabs at least 4 offensive rebounds per 40 minutes played, a skill that about 15% of forwards have.

If you want to be an elite offensive player at the forward position, offensive rebounding is a skill you almost certainly must possess. I am a little concerned with defining players based on this characteristic, because coaching can have such a big impact on this skill. In particular, a big reason to be optimistic about South Carolina next year is that Frank Martin will get his forwards to grab offensive boards. But whatever the source of the skill, offensive rebounding is essential to efficient play at the forward position.

Overall, when I look at these various tables, I think the most interesting thing is that the development curves are fairly similar. Pure point-guards tend to improve more between their freshmen and sophomore seasons, but for the most part players with various skill profiles tend to develop at a very similar rate.

But what these data really suggest is that we shouldn’t have equivalent expectations for players at every position. Offensive rebounders and three point shooters might be good right off the bat. But small forwards and point-guards are rarely polished players until later in their career.

Have you reached your potential?

When thinking about player development, the next table brings up even more questions. The X-axis shows a player’s ORtg as a Junior and the Y-axis shows the change in ORtg between the Junior and Senior season.