2009 Player Projections: BC, FSU, and Miami

Quick first impressions:

• Boston College: Whatever defense the Eagles have ever played has been predicated on having a shot blocker under the basket to make up for the matadors on the perimeter. With no player on the roster taller than 6'8", Al Skinner is going to have to come up with a new strategy.
  
• Florida State: Toney Douglas is the star, but the season will ride on how well the six freshmen play.
• Miami: Why is it that whenever a team exceeds artificially low expectations one year they're always wildly overrated the next? The Hurricanes have a solid roster and a very good coach, but there's no way they're a top-10 team.
  

NCAA Preview: (7) Miami vs. (10) St. Mary's

If you can't see the tables below, click back to the blog to see them, or click here to see them.

The Gaels are a tough matchup for the Hurricanes. While they're not an elite defensive rebounding team (.691 adjusted DR%, 102nd nationally), they're strong enough to limit Miami's second chances. That's important, because St. Mary's forces numerous misses both inside (.437 adjusted d2G%, #40 nationally) and outside (.306 adjusted d3G%, #14 nationally) the three point line.

Tourney Preview: (5) Miami vs. (12) N.C. State

The tables below might not show up in an RSS reader; if all you see is text, either click back to the blog to see them, or click here to view the source spreadsheet.

Miami's a better team than N.C. State, but not so much better that it would qualify as a huge surprise should Sidney Lowe's charges win. State won the first and only meeting between these two teams eight weeks ago in Raleigh by a score of 79-77 (77 possessions), but it took an unlikely comeback in overtime to get the job done.

Miami's offensive efficiency is 1.0698 points per offensive possession in conference play, good for third-best in the league, despite being one of only four ACC teams to average less than 1 point per field goal attempt. With a turnover rate right around league-average, almost all of that offensive production is tied up in Miami's offensive rebounding prowess. Strong defensive rebounding teams should be able to negate Miami's advantage on the offensive glass, making them beatable by even some supposedly weaker teams. Unfortunately for Wolfpack fans, State is not a strong defensive rebounding team. Look for Miami to win the game on the glass.

Game Previews: The Overshadowed

Let's be honest here: there's only one game that anybody outside of Atlanta, Chestnut Hill, College Park, Coral Gables, Tallahassee, and Winston-Salem really cares about tonight. It's a damn shame, too, because all three promise to be good games. I'm running short on time this evening, so I'll run a paragraph on each along with a link to the respective reports.

The closest of the three is the first game of the night, when Maryland travels to Chestnut Hill to take on the Boston College. Maryland has a small advantage on paper, but when the difference between two teams is 2/3 of a point over 74 possessions it's hard to call them a favorite to win.

Also tipping at 7:00 are Wake Forest and Georgia Tech. The two schools everybody used to get confused with one another when they were kids square off in a game whose winner will reach the halfway point of the ACC season at .500. Wake is just under a 2-point favorite, and they won 55% of the simulations.

A half hour later, Florida State and Miami will tip off before a crowd of dozens. Miami's advantage on the glass makes them a 7-point favorite, making this the biggest mismatch of the night.

Game Preview: Clemson at Miami

Let's see if today goes better for the predictions than yesterday did. I found a glitch in the code that was overstating home court advantage by a factor of about two. Both of yesterday's games were still surprises, just not as big as they appeared given the numbers here yesterday.

Two of my favorite teams in this year's ACC square off in what looks to be one of the most evenly-matched games we'll see. Both Clemson and Miami have trouble shedding the "football school" label, and tend to be overlooked even when they have good teams. Choking out out of NCAA Tournament contention after a 17-0 start or losing three ACC games in a row after a promising beginning to a season don't help matters much. Even so, this game is worth watching.

Both these teams rebound the heck out of the basketball under normal circumstances, so they're likely to cancel each other out today. Whichever team is able to force turnovers to the greatest effect looks to come out on top today.

Hurricane Forecast

Miami's projections are ready.

I'm going to take a few days off from generating the projections. Half of them are up, and with the season still almost 4 months away I don't feel any real rush to get the rest out there. Instead I'm going to spend some time on a new project.

In developing the similarity scores used to generate the player projections, it's really jumped out at me just how close a correlation there is between a player's size and the statistics that he generates. Amazingly enough, height and weight are not used at all in generating the similarity scores, yet the top comps are almost always dead ringers, from a body-type perspective, for the base player.

I've been using player size as a proxy for position in PAPER, but that leads to a few different kinds of problems. First, sometimes there are guys--Ishmael Smith and Will Bowers, to cite one from either extreme off the top of my head--who are so far outside the normal range of players that the regressions that tell me what the "league average" player of their size should be doing just don't have enough good data to work with. They wind up with funky results (a player T.J. Bannister's size in 2005, for example, should have blocked -0.006 shots per defensive possession according to the model) that I've either got to just roll with or jury rig out somehow. In the grand scheme of things, it's not a huge deal, or one that affects the bottom line number much, if at all, but I've never cared for it.

The second problem is that it treats players who are big or small for their position differently than they probably should be. There's an adjustment using BMI that refines the raw height number into something a little bit closer to the truth, essentially adding an inch or so to the height of the stouter players while shaving one off of the scrawnier ones, but PAPER still treats Mamadi Diane and Greivis Vasquez exactly the same, even though they have vastly different responsibilities on the court.

Getting to the point, I think there may be a way to make PAPER better by scrapping the size adjustments and using positional adjustments instead. I'm already making what I think is a pretty safe assumption: players of similar size generally tend to play the same position. But if I can break that down, to find some markers in the numbers that say, "This guy is a shooting guard," or, "That guy is a defensive specialist," it will only make the system better.

I don't know if this will go anywhere or not, but I'm going to think on it for a few days and see what happens. In the meantime, if there's a player on a team that hasn't been posted yet, and you're just dying to see what the Magic Spreadsheet says he's going to do next year, drop me an email. Running the individual projections takes like 5 seconds, and I do them out of curiosity all the time; it's just the formatting everything into a nice little package that takes a couple hours for each team.