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UCLA Bruins And The Michigan State Spartans By The Numbers

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Well, it has been a couple of years since I have had the opportunity to write up one of these posts before a UCLA NCAA Tournament game. For the newer members of Bruins Nation, back in the good old days (when the Bruins were fighting for Final Four bids, and yours truly was not yet on the front page) I wrote a series of posts looking at our upcoming tourney matchups looking through the lens of some of the different computer rating systems - such as those of Ken Pomeroy and Jeff Sagarin - as well as some reference to the much-maligned RPI. With the Bruins back in the Madness, and DCBruins and Co. doing a great job with game previews, and even a Q&A leading up to Thursday night's game, I'll be reprising that series here, starting with our game with Michigan State.

For folks unfamiliar with these ratings systems, or at least unfamiliar with the nuts and bolts of them, here's an explanation that I wrote in an earlier post of what the Pomeroy and Sagarin systems (and there are actually two different Sagarin ratings, which in turn are added together to create a third, main rating) look at, what type of result they create and the methodology that the systems use to reach it.

One quick note about the three rating systems which I cite here. Each of the ratings uses a different methodology, and a different way of measuring success in order to come up with a ranking. The RPI uses a formula based upon the win % of each team, plus the win % of each of its opposing teams, and the win % of the opponent's opponents. This formula does not look at how each team earns its record (does not look at score margin, turnovers or anything other than Wins and Losses). Ken Pomeroy's formula, rather than focusing on only W-L, uses a complex set of game data which aims to predict future performance, rather than accounting for how good or bad a team has performed to date. The Sagarin ranking that I post here is actually a synthesis of two separate ratings which Sagarin calculates; one being an RPI-like formula taking into account only wins and losses, the other taking into score margin rather than a team's record.

Michigan State enters the NCAA Tournament with a 19-14 record (18-14 against D-1 opponents), earning an at-large berth and the Southeast region's 10th seed after finishing in a 4-way tie for 4th in the Big 10 (9-9). In the Big 10 Tournament, the Spartans opened with a 66-61 win over Iowa, before thrashing Purdue 74-56 in the quarterfinals, in what was easily Michigan State's most impressive win of the year, and the win that likely gave them their spot in the field of 68. That victory was followed by a 48-61 loss to Penn State in the semifinal, a game which was considered even going in, and that was tied at halftime.

The Bruins and Spartans share a single common opponent - Washington. While UCLA got swept by the Huskies, Michigan State defeated them 76-71 early in the season at the Maui Invitational. While their 14 losses sounds like a lot for a tournament team, particularly an at-large selection, I should note that the Spartans have contested a very tough schedule this year; while the Big 10 (11) does not feature a complete home-and-home as the Pac-10 does, they did play a tough slate in what Pomeroy, at least, considered the toughest conference this year. They only had to play conference champions Ohio State once, but played the next five teams in the standings twice each in the regular season. As well, Michigan State played a worthy non-conference schedule, highlighted by games against Duke, Texas, Syracuse and UConn as well as the previously mentioned game with Washington. Of course, they lost all but the Washington game. In sum, the Spartans have played a total of 19 games against 12 different NCAA tournament teams this season.

Now, to the numbers...


RPI: UCLA - #44; Michigan State - #45

Pomeroy: UCLA - #53; Michigan State - #41

Sagarin: UCLA - #47; Michigan State - #37

The variance between the purely winning percentage-based RPI and the more holistic Pomeroy and Sagarin approaches is interesting. According to the RPI's methodology, the Bruins and Spartans are of equal strength and accomplishment - interesting that 7 v. 10 would be seeded so closely, while the latter systems both consider the Spartans to actually be the better team by about 10-12 places - making one wonder who should really be thought of as the higher and lower seeds. For whatever it is worth, the Sagarin rating that looks only at wins and losses preserves the margin between the teams, and not closing the gap as the RPI does.

By RPI measure, this is the closest matchup in the opening round. In terms of the other predictive ratings, this is the least favorable opponent that any high (1-8) seed has been given in this year's tournament. With that said, here is a look at the efficiency metrics and pace of play for the Bruins and Spartans. For information sake, I will show the teams' efficiency stats against only conference opponents, as well as their overall stats. I do not know how well, if at all those (latter posted) stats will help a comparison of the teams, but you can at least see how the teams fared against their peers - and separated from (mostly) early season non-conference tilts.

Michigan State

* Offense: 108.9 points/100 possessions (#67 in D-1). Big 10 only: 101.8 points/100 possessions (10th in Big 10)

* Defense: 92.5 points/100 possessions (#34 in D-1). Big 10 only: 106.1 points/100 possessions (4th in Big 10)

* Pace: 65.8 possessions/40 minutes (#220 in D-1). Big 10 only: 62.3 possessions/40 minutes (7th in Big 10)


* Offense: 106.7 points/100 possessions (#88 in D-1). Pac-10 only: 102.5 points/100 possessions (4th in Pac-10)

* Defense: 92.3 points/100 possessions (#32 in D-1). Pac-10 only: 95.7 points/100 possessions (1st in Pac-10)

* Pace: 66.2 possessions/40 minutes (#195 in D-1). Pac-10 only: 65.8 possessions/40 minutes (8th in Pac-10)

To start off with, that in-conference spread for Michigan State (outscored by more than 4 points/100 possessions) seems a bit high, but after looking at some of the other teams in the conference, it is more an indication of how dominant the top teams - particularly Ohio State - were in the Big 10 this year, plus the fact that most of their conference wins came by a small margin (six of their nine regular season wins - plus one of their two tournament wins - in conference came by 5 or fewer points, three of which ended in overtime). Of greater insight are the ranks within the teams' respective conferences; the issues that Michigan State has has scoring - as discussed by the folks at The Only Colors in yesterday's Q&A - really shows up here, having the second-least efficient offense in the Big 10 during conference play. Going further into Pomeroy's page on MSU, we see that the team is simply not shooting well, and particularly so at attempting 2-point FG's (as opposed to not scoring because they turn the ball over every other possession).

In Michigan State, Ben Howland has come across an opponent that likes to play at a similar, deliberate pace to that of his Bruin teams of recent years. Using the above efficiency measures, together with the average pace of the two teams' play, the average game score of each team, based upon an equal schedule composed of average Division 1 teams would be:

  • UCLA: 71-61
  • Michigan State: 72-61
  • Game Predictions: Pomeroy - Michigan State 65-64; Sagarin - Michigan State by 1.5 points.

By all measures, this game is looking to be a tight battle. Along with Vegas, the different ratings all have the Bruins and Spartans no more than a point and a half apart. While this game is by no means a UCLA lock (thankfully so, if you look at how the Bruins have treated 'gimme games' this season), this is a game that the Bruins can certainly win IF they come out of the locker room in Tampa and play a full, committed 40 minutes as they did last month against Arizona, earlier in the season against BYU, or even in their narrow loss at Kansas.