In case you missed it, last Thursday I presented my upgraded projections model. Then I presented my 13-14 season projections on ESPN Insider. My projections included the median simulation, best case, and worst case for every team. I also did a Q & A session with Eamonn Brennan and another one with John Templon. I have also been answering a few questions on Twitter. You would think after all those words I would have run out of things to say, but here are a few thoughts that did not quite make the cut in those articles:
The Underrated Club
Q: Why does the simulation hate Arizona St.? Jahii Carson is one of the best players in the country.
A: Arizona St. is a team with a lot of two-star players on the roster. In fact, they have the second lowest average star rating in the entire Pac-12, ahead of only Utah. Luckily a few of those players are transfers who played well for other teams. But what this really means is that Arizona St. just doesn’t have the same upside as many of the other schools in the Pac-12. Herb Sendek’s track record on defense is also a huge concern.
Q: Why does the simulation hate Maryland? A lineup of Shaquille Cleare, Evan Smotrycz, Dez Wells, Nick Faust and Roddy Peters sounds like it could hang with anyone. And Seth Allen, Charles Mitchell, and Damonte Dodd all seem like solid reserves. Why is the model so pessimistic?
A: The simulation is concerned that Maryland has only nine scholarship players on the roster. There is real downside risk with such a short bench because if a couple of players struggle or get injured, there are no alternates. Last year N.C. State entered the year with just nine scholarship players and things turned south early. Now, that doesn’t mean Maryland is destined to fail, but depth is a risk with this type of roster.
Q: Why does the simulation hate Denver? They had a great margin-of-victory numbers last year.
A: While I truly believe star ratings are important, the focus on recruiting evaluations really hurts the small conference squads in my projections. Only when a small conference team has virtually no lineup questions will that team be ranked near the top. (This year the two exceptions are North Dakota St. and Harvard. North Dakota St. brings back 95 percent of its minutes and gets a player back who was injured for much of last year. Meanwhile Harvard gets two star players back who were suspended last season.)
In Denver’s case even with several efficient players back, particularly star Chris Udofia, winning seems likely. But Denver has to replace two of the three players that played the most minutes last season. And the likely replacements will only be two-star athletes. That’s not to say that head coach Joe Scott cannot build a winner again. But it is very hard to get a Top 50 margin-of-victory in a small conference. And if Scott does it again, that should be considered a huge accomplishment. It shouldn’t be the expectation. (The real issue for Denver is finding another ball-handler to compliment Udofia. Last year Royce O’Neale and Udofia both were key distributors for the team, but with O’Neale transferring to Baylor, the remaining options are not great.)
Random Thoughts on Some Major Conference Teams
- In my Insider column, I said that the Spartans were the lowest risk team in the nation which sparked some jokes from Michigan St. fans on Twitter. I think this points out how insanely volatile college basketball can be. Even when the Spartans bring back five of their six top rotation players including three clear stars, their fanbase in nervous. Part of that is the fact that Tom Izzo’s teams notoriously struggle in November. But when a team with Top 10 talent brings nearly everyone back and their fans are nervous, you know that anything can happen in college basketball.
- Michigan’s position in 12th in my rankings is a little misleading. I honestly believe that Mitch McGary and Glenn Robinson can lead this team a long way. But I am legitimately concerned about the guard rotation. John Beilein was very reluctant to play Jordan Morgan and Mitch McGary together last season because they weren’t outside shooters. So I have to assume Robinson will play most of his minutes at the four-spot again this year. But then how does the guard rotation work? Does the team play Spike Albrecht, Derrick Walton, and Nick Stauskas together? What if Albrecht and Walton aren’t ready? That is why my model has such a low downside for the Wolverines. (And don’t tell me Caris LeVert is the answer. He was a low-ranked recruit and nothing he did last season leads me to believe he should be a key player on a Top 10 team.)
- When I first ran the model, I was a little surprised the downside for Kentucky was not lower. After all, a young Kentucky team lost in the first round of the NIT last season. But this is what happens when you return two efficient high potential players (in Alex Poythress and Will Cauley-Stein), and add five Top 10 recruits. With that many high potential players, even if two or three of them struggle immensely, Kentucky can still win. Kentucky could not afford for Archie Goodwin to struggle and Nerlens Noel to get injured last season. This year if Julius Randle struggles and Will Cauley-Stein gets hurt, the team can just say “Next man in.”
- I love the range for Indiana in my ESPN Insider rankings. The team has 7 top 100 recruits, and an elite season is still possible. But given all the new faces and how little most of the returning sophomores played last year, the downside risk is major.
- If you want to vote any of my model’s Top 34 teams into the Top 25, I can see arguments for all of them. But I stick by my model’s skepticism of Baylor. Pierre Jackson carried the Bears last year and I don’t see how they can be a better team without him. Their margin of victory was 26th last year (thanks to winning the NIT) and I only give them about a 20 percent chance to do better than that.
- If you have ESPN Insider, look at how painfully low Alabama’s downside is this year. After Devonta Pollard was arrested this offseason, the team is down to nine scholarship players who are eligible this year. If someone on Alabama’s squad doesn't play well, there are no alternatives. This is too bad because Anthony Grant is such a talented young coach, but off-court issues keep derailing his teams.
- Iowa St. made a great move adding Marshall transfer DeAndre Kane. But I suspect Fred Hoiberg needed to add a couple more transfers to keep his transfer winning streak going. With 64% of the lineup gone and four of Iowa St.'s six most efficient players departing (Melvin Ejim and George Niang return), expect Iowa St. to take a step back.
- My model is more optimistic about Seton Hall than what you see in some other rankings. Texas transfer Sterling Gibbs will be a huge upgrade over Tom Maayan and his 50% turnover rate. And with fewer injuries, Kevin Willard should have the defense playing better.
Random Thoughts on Some Mid-Major Conferences
- I’ve still got St. Mary’s on the NCAA bubble. Many will discount the team after Matthew Dellavedova's departure. But Beau Leveasque and Stephen Holt aren't suddenly going to forget how to shoot. Brad Wadlow isn't going to stop being a physical force on the boards and finishing over 60 percent of his shots. This team still has talent.
- The team I think most pundits have over-rated this year is Northeastern. The Huskies were extremely lucky last year. Despite the 7th best MOV in the CAA, they won a ton of close games, including a 4-1 record in OT. Their conference title is very deceiving. With the team's leading scorer and most efficient player Joel Smith gone, a repeat conference title seems unlikely.
- One team I am buying is Weber St. Weber St. had the best margin-of-victory in the Big Sky last year. They even outscored Montana by 19 points in their three meetings. But somehow they went 1-2 against the Grizzlies and that 1-2 mark gave Montana the regular season and conference tournament title. Weber St.’s aggressive and efficient inside-outside combination of Davion Berry and Kyle Tresnak is going to make sure that doesn't happen again.
- The conference champion I expect to come out of nowhere this year is Manhattan. Manhattan somehow lost 10 games to conference foes, but only one of those games was by double digits. This team was much better than last year's conference record would indicate.
- The race for the Big West title is wide open. I have five teams projected within one game of first place in that league.
- The CUSA race should also be highly entertaining. Louisiana Tech is the only team in CUSA that returns over 70 percent of its minutes from last year. (Tech brings back 85 percent of its minutes.) And Tech's losses won't hurt the offense. The team loses its least efficient player Brandon Gibson, and the extremely passive JL Lewis. With an already solid defense and an improved offense, Louisiana Tech could be headed for the NCAA tournament. But Southern Miss is just as formidable a competitor. The newest Golden Eagle, transfer Aaron Brown, shot the ball extremely well as a sophomore at Temple. His addition could give Southern Miss the CUSA title.
- Speaking of transfers, transfer Jay Harris was the PG on a Valparaiso team that won the Horizon league title in 2012. He could be the key addition that gets Wagner an NEC conference title in 2014.
- Finally, Indiana St. PG Jake Odum has to be kicking himself that RJ Mahurin transferred out in order to play his senior year with his younger brother. Mahurin was the team's only efficient big man, and the Sycamores could have been a more realistic NCAA bubble team had Mahurin returned.
Late Breaking News
- The news that Josh Smith was eligible immediately didn’t break until after I finished my rankings. With a full season of Smith you can move the Hoyas up to 27th in my projections. But as many people have noted, because of his conditioning, it still isn’t clear how much Smith will play. The downside risk for the Hoyas remains real. However, I do think that it is a major break that Smith will be around from the start of the season. The Hoya offense is a nuanced system that depends on precise cuts and passes, and integrating Smith mid-season would have been much more difficult.
- I had already assumed Joseph Young would be eligible for Oregon so their ranking is not affected by that news. It is clear that the transfer combination of Mike Moser and Young could be one of the best inside-outside combinations in the country. But I want to offer several cautionary tales. Ryan Harrow, Trey Ziegler, and Aaric Murray were three transfers that received a ton of hype last summer, and they were all such poor fits in the new environment, they have all moved on again. We’ve seen teams bring in a bunch of transfers and live up to expectations (like Iowa St.), but we have also seen teams take in a lot of transfer and disappoint (like Missouri last year.) Transfers are high risk players, and that is why my model has such a large range for the Ducks this season.
Dan Hanner vs Ken Pomeroy
Ken Pomeroy also released his preseason rankings on Saturday. While he is rather humble about his algorithm, I think it is important to note how well his system did last season. From a modeling perspective, a more complex system is not always better.
I would argue that the real advantage of my lineup-based system is not the predictive power. The advantage is that by focusing on the lineup, my model has fewer head-scratching conclusions. For example, Ken’s team level model has Miami at 62nd this year. With basically everyone in last year’s rotation gone and Angel Rodriguez electing not to apply for a transfer waiver, that’s an extremely optimistic prediction. But that prediction is based on how well Miami did last season, not any reasonable evaluation of the current roster. The same can probably be said of Minnesota at No. 35. The Gophers had strong margin-of-victory numbers last year, so Ken’s model loves them again this season. But my model sees that the Gophers made a substantial downgrade in the front-court and added an unproven coach. My model based on the current lineup has Miami at No. 102 and Minnesota at No. 63, and I think that’s much closer to what I have seen in most expert rankings.
But while Ken’s model can cause us to scratch our heads at certain results, do not overlook his predictions. The last five seasons of data are a very strong predictor in the aggregate. (If a team had a great offense before it tends to have better facilities, higher caliber recruits, and better coaches today.) And when the results of both our models agree, those are probably the strongest predictions of all.