At the beginning of April, I used my lineup-based model to project the 2013-14 college basketball season. If you would like a brief capsule on all these teams, please click on that link.

At that time, I had to guess which early entrants would declare for the 2013 NBA Draft. Now that the NBA’s early entry deadline has passed, I thought I would update the Top 25 projection:

My predictions about who would declare for the draft were surprisingly accurate. (I even pegged Russ Smith correctly.) But a few surprise entrants and transfers have altered the rankings slightly. Here is what has changed:

Out of Top 25

Colorado: The unexpected departure of Andre Roberson drops Colorado out of the Top 25. Don’t let Roberson’s poor efficiency in 2012-13 fool you. He was much better as a freshman and sophomore and the model fully expected him to bounce back and have a dominant senior year. Without him, Colorado will still be good, but not quite Top 25 material.

Memphis: Losing Tarik Black and Antonio Barton in addition to Adonis Thomas was enough to knock the Tigers out of my Top 25, but they are still close.

Alabama: The transfer of Trevor Lacey hurts. Alabama seems destined to remain a football school.

Creighton: While I was right about Doug McDermott returning, I was wrong about another player. I was under the impression that Grant Gibbs would return. Gibbs has only played three seasons of basketball. But because he didn’t play one year at Gonzaga and then transferred and sat out again, it does not look he will be eligible for a sixth year. Without Gibbs, Creighton will still be good, but not quite a Top 25 squad.

Into Top 25

Oklahoma St.: I did not expect Marcus Smart to return. His return single-handedly boosted Oklahoma St. from outside the Top 25 and into the Top 10.

Gonzaga, VCU: They move up because other teams dropped out.

Maryland: In the early April projections I had already projected Alex Len to leave, so Maryland moves up as other teams lose players. Several things suggest that Maryland will make a big leap this season. First, the team gave a ton of minutes to freshmen last year (namely 34%). The typical sophomore leap in efficiency for those players should improve the team’s performance. And Maryland can avoid a lot of those first-year mistakes this year because of its depth. Six quality rotation players return and those players will be joined by Michigan transfer Evan Smotrycz and highly hyped freshmen PG Roddy Peters. Among teams at this level of the rankings, that kind of depth is rare.

More importantly, none of the team’s losses will be impossible to replace. The loss of Pe’Shon Howard is really addition by subtraction. Howard was incredibly inefficient at the PG spot and #52 recruit Roddy Peters should be able to easily eclipse Howard’s efficiency. And even if Peters isn’t ready to dominate from day one, Seth Allen and Dez Wells are great ball-handlers and passers and can help ease Peters into the ACC. Alex Len will be harder to replace, but not impossible. Shaquille Cleare is the most natural choice to step in at the center spot. Cleare won’t quite take as many shots as Len, but he was efficient in limited time last year and as the #34 recruit out of high school, he is exactly the type of player who will typically become a star as a sophomore. Smotrycz’s ability to stretch the floor with his three point shooting can also take up some of the scoring load. Finally, the main reason to be high on Maryland next season is that the Terrapins have a true superstar in Dez Wells.

Note: I don’t disagree with anyone who has Harvard in the Top 25 next year. The model is skeptical of the team’s defense after the poor performance last year, but it is likely that the two players returning from suspension will upgrade that unit substantially. But the defensive stats just don’t have much predictive power, and the model doesn’t generate that result. I may think about a way to account for this (for example pretending last year didn’t happen), but this is a very unusual circumstance to say the least.

It also seems like most experts have Wichita St. in their Top 25 for next year. Even with the Final Four run, Wichita St. still only had the 17th best margin-of-victory numbers last year and the Shockers return just 48 percent of their possessions from last year. The good news is several tournament stars are back and they have a potentially dangerous lineup, but they lack the depth and incoming talent to project them for the Top 25 right now.

Finally, with the players returning, Baylor absolutely has the talent to be a Top 25 team. But the model does not respect Scott Drew as a coach at this point. Even with talented teams, he far too often fails to generate a dominant offense or defense.

Falling, but still in the Top 25

North Carolina: Reggie Bullock’s departure knocks the Tar Heels down from third to eight in my projections.

Michigan: Tim Hardaway Jr.’s departure caused Michigan to drop below Arizona and Duke. But Hardaway was the least efficient rotation player for the Wolverines last year and Michigan fans should still count themselves lucky that Mitch McGary and Glen Robinson are back. Probably the most efficient lineup for Michigan would be Jordan Morgan, McGary, Robinson, Nik Stauskas and elite PG recruit Derrick Walton on the floor at the same time. (Walton has a trivially higher expectation than Spike Albrecht according to the model but both should play major minutes.) But John Beilein seemed reluctant to play Morgan and McGary together this year, and it isn’t clear Robinson can play the wing spot in a perimeter-oriented offense. The lack of depth on the perimeter is really the only question mark on this team as the development of McGary and Robinson should help offset the loss of Trey Burke.

Marquette: The loss of Vander Blue is devastating as Marquette falls from eighth to 18th in my model. Vander Blue was projected to play the most minutes, take a ton of shots, and do so in efficient fashion. While the Golden Eagles still have plenty of good players, he was the clear star. I have also adjusted the rankings to account for Chris Otule’s return for a sixth year, but this is a mixed blessing. Otule was supposedly a substantially better defender than Davante Gardner, but by the measured statistics (namely defensive rebounds) Otule was not very good last season.

Georgetown: I had already forecast Otto Porter to leave at the start of April. But I decided to lower the projected minutes for transfer Josh Smith. The model expected that since Smith was a clear star early in his career that he should be able to play major minutes after joining Georgetown mid-season. But in his career, Smith has never been able to play 75 percent of his team’s minutes because of his conditioning. While he could get in shape, I decided his minutes’ projection was too optimistic and manually lowered his minutes to something more plausible. Without Smith’s offense, Georgetown’s projection looks worse. They still have all the pieces for an elite defense, especially with Greg Whittington coming back.

Not Falling

Arizona: With so many talented forwards, no team was probably as better prepared to lose a player like Grant Jerrett than the Arizona Wildcats.

Virginia: The transfer of Paul Jesperson is not meaningful to Virginia’s expectations next year. He never shot last year and when he did, he only posted a 91.7 ORtg. He was projected to play substantially fewer minutes in the upcoming season and that is exactly why he transferred.

A few other notes:

I cleaned up some roster issues with walk-ons which may explain why some of the numbers seem slightly different.

Also, I ran my initial projections before the Final Four was over. I have now updated the numbers to reflect the final stats. Louisville’s defensive projection fell because of what happened in the final two games. Similarly, some other teams were impacted because they had played the Final Four teams. For example, Ohio St.’s defense improved trivially on Kenpom.com over the last weekend. I wouldn’t even mention this, but it explains why Ohio St. went from being percentage points behind Iowa to being percentage points ahead of Iowa in my projection.

Finally, I had to correct one major error. My code included several “if 2013” statements to project the 2013 season. And I had to change them to “if 2014” to project the 2014 season. In my rush to get this done on Final Four weekend, I missed one line of code where I multiply each returning player by a standard player development factor. This impacts every team and essentially didn’t change the rankings, but it does explain why the offensive projections are higher here than they were a month ago. I apologize for any confusion.

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