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Reminder

There’s still time to enter the First Annual and World’s Only (As Far As We Know) Big Ten Tournament Bracket Contest and win a free t-shirt. Post your entries in the comment section of the blog post located here.

Detroit Still a Possibility?

I didn’t notice this until a friend pointed it out: Joe Lunardi projects MSU to play in Detroit if they advanced to the regional semifinals. It appears this is still a technical possibility. This from a Joe Rexrode post from Saturday (before the loss in Columbus):

The rules to remember:
* The top three seeded teams in any league can’t be in the same region.
* Teams in the same league can’t meet until at least the Elite Eight.
That’s really it. The idea that it would be “unfair” for a higher seeded team to have to play MSU in Detroit is meaningless. Texas A&M was a 3 seed in San Antonio last year, for a recent example.

My guess is its unlikely the selection committee would put a 1 seed in the position of having to play an effective road game in the first game of the second weekend of play–which is the scenario Lunardi projects with MSU as a 5 seed. It’s more likely it would happen if MSU lost Thursday and dropped to a 6 or 7 seed, so they would only be putting a 2 or 3 seed at a potential disadvantage.

As I have a ticket to go to the NCAA games at Ford Field, this will be a small measure of consolation if MSU is one and done in Indy. Of course, being a 6 or 7 seed won’t guarantee (1) being placed in the Detroit regional or (2) advancing through the first two rounds of the NCAA Tournament to get to Detroit.

I’d say winning the Big Ten Tournament championship and advancing to play in a lovely regional location like Phoenix would be the way to go.

Izzo Agrees With Me About Attacking the Press

OK, OK. Probably more accurate to say I agree with Izzo about attacking the press. Here’s what the coach said yesterday:

“I did not think we attacked the press, we pulled it out more,” MSU coach Tom Izzo said at Monday’s weekly press conference. “I’ve always wanted to attack a press, and so we didn’t make them pay for pressing us and that’s something we’re gonna work on this week.”

Here’s what I said Sunday:

If you’re going to get pressed, you can’t afford to be passive. The defense is going to pick up some turnovers. So you have to attack the press for some easy baskets. Otherwise, there’s no downside to pressing.

As long as MSU implements this plan on Friday, I’ll go ahead and let Izzo take credit for it.

Graphy Goodness

To date, the standard graphical format for displaying tempo-free stats has been the tempo-free aerial. As TAFKATBTW recently noted, however, the data on which such a graph is based doesn’t tell us anything about consistency. Further, it doesn’t tell us whether a team is getting better or worse as a season progresses.

I am pleased, therefore, to present the next generation of tempo-free graphical data presentation: the tempo-free trend curve. To demonstrate, here’s a graph of MSU’s trend curves:

The markers connected by the dotted line plot MSU’s game-by-game offensive and defensive efficiency figures (points per 100 possessions) for each of their 18 conference games (in chronological order). The solid lines are polynomial trendlines (3rd order, for the geeks among us).

I copied this approach from what the Football Outsiders people do in their annual preseason Football Prospectus. For each NFL team, they graph game-by-game DVOA (their measure of football performance on a down-by-down basis) and look at the curved trendline.

The idea is to smooth out individual game performance to see the general direction a team’s performance seemed to be moving in at a given point in the season. Intuitively, this should tell us whether a team is on the upswing or downswing as the regular season ends–although I can’t definitively say the method is predictive. I should also note there are a couple flaws in this approach:

• It doesn’t account for quality of opposition–an upward trend could represent a grouping of weak opponents on the schedule (or vice versa).
• It doesn’t account for home/away game. Other than the occasional three-game bunch of home or away games for a particular team, though, the home/away factor should be smoothed out by the trendlines in most cases.

As we look at the graphs for each Big Ten team below, I think you’ll agree the results make intuitive sense for most teams.

OK, back to MSU’s graph. The trendlines indicate their offensive efficiency (blue line) increased over the course of the season–fueled in part by the blowouts of Penn State and IU (which are literally off the chart)–before tapering off at the very end of the conference season. The five-game stretch of turnover-free play before the Ohio State loss was, of course, a big key to the offensive improvement.

Their defense efficiency (red line), meanwhile, regressed over the course of the season (the defensive trendline going up is bad). I think that’s probably mainly a function of the schedule being back-loaded, though.

The main thing to look for in terms of overall performance is whether, and by how much, the blue line is above the red line. That shows the team’s level of efficiency margin (margin of victory/loss divided by game possessions times 100). If we graph just MSU’s efficiency margin, we get this:

This graph implies that MSU peaked around the time of the Penn State win and has declined as the regular season wound down. I would offer the caveat, though, that MSU’s near-record inconsistency may make this approach less useful than for other teams. For example, if you just remove the Ohio State loss, the graph tells a dramatically different story about their current momentum:

So the optimistic take here is that the final 11 minutes of the Ohio State were an anomaly. If the team can forget about those 11 minutes, we’ve got the Big Mo on our side.

Below is a tempo-free trend curve graph for each of the other Big Ten teams with brief comments below each graph. I’ll show the graph that includes both offensive and defensive efficiency, so you can see what’s driving overall performance trends. You’ll have to imply the efficiency margin graph from the gap between the two trendlines. We’ll work from the top of the conference standings down.

This graph is very, very frightening. The only consolation is that none of their final six games were against one of the other three NCAA Tournament locks.  Oops.  Badgercentric notes that the MSU game was one of the last six games Wisconsin played.  All that staring at data fried my brain.  I can only blame the enormous chasm between Wisconsin’s trendlines at season’s end on their final two games–against Penn State and Northwestern.

When the conference season began, we thought Purdue was an average Big Ten team. And they were; it’s just that they steadily improved over the full 18 games of conference play, particularly on defense. Five of their first 10 opponents posted effective FG percentages above 50%; only 2 of their final 8 opponents did so.

Indiana was a very good team for two-thirds of the conference season. Then Sampson departed. In five games under Dakich, they’ve become an average team. A steep decline in offensive efficiency has been the culprit. This is precisely the opposite of what I predicted.

Based on a one-game sample, it appears the departure of Sampson may hurt IU more on the defensive end than the offensive end, where they can rely on the supreme talents of Gordon and White.

Of course, their defense had already been on the decline before Sampson departed.

This team went from good to average over the first half of the season, as their defensive efficiency regressed substantially. Ohio State didn’t allow an opponent to shoot above an effective FG% of 50% in their first 8 games. Five of their final 10 opponents did so. The blue line is back above the red line (barely), though, on the strength of the wins vs. Purdue and MSU.

Minnesota was basically an average team all year long, finishing at 8-10 in the conference. Their defense did gradually decline over the 18 games, as teams figured out how to beat their pressure. Their first 8 conference opponents all posted turnover percentages above 22%. Only 3 of their final 10 opponents did so.

Penn State was bad on defense for the entire season. Eleven of their 18 opponents put up effective FG percentages above 55%. They started out pretty good on offense, then declined after the loss of Geary Claxton, but rebounded back toward offensive mediocrity as their freshmen developed.

Iowa was up and down on defense, but improved steadily on offense over the full conference season. A lot of the apparent improvement is based on big offensive performances against Penn State and Northwestern late in their last three games, though.

Michigan managed to get to an average level of performance for about a 5-game stretch (which included 4 of their 5 conference wins). Their defensive improvement was led by better rebounding; just one of their final eight opponents had an offensive rebounding % above 35%.

The trendlines would seem more appropriate for a .500 team, rather than a team that finished 5-13 in conference play. The problem for Illinois is that most of their wins were blowouts, while they lost a lot of close games. Illinois is a pretty veteran team, so there wasn’t a lot of room for improvement as the season went along.

We didn’t need a fancy graph to tell us Northwestern played very poorly this season. Even the three-game stretch of losing close to Iowa and Indiana and beating Michigan could only minimally shrink the gap between their trendlines.

There you go: 13 graphs, all suitable for framing.