Monthly Archives: February 2013

Michigan: Destined for an early exit?

Michigan is my favorite college basketball team, and for the first time in awhile, they are threatening to make a deep tournament run. However, they just lost three of four during a tough stretch against Indiana (L, away), Ohio State (W, home), Wisconsin (W, away), and Michigan State (W, away). I’m not writing them off — they only lost the away games — but some bad signs appeared in these games. Here’s the Game Stack for all four combined:

Mich 4 games 2-2013

Michigan looks good on turnovers, but that comes at a cost — they get crushed on free throws and two point percentage. Having watched the games, I can connect the dots for you: the Wolverines don’t drive to the hoop much against good teams. They have some great shooters who can get reasonably open (Trey Burke, Tim Hardaway, Jr.) who are happy to “settle” for jumpers.

This keeps the ball out of danger in the lane (low turnovers), but it means that Michigan never gets to the line and shoots a lower percentage on twos as well. Michigan also rebounds a lower percentage of their own misses than the opponent, which could be related — a lot of “second chances” are just put-backs after a shot close to the hoop.

So, is Michigan sunk? We’ll see. I have some faith that Mitch McGary can improve and find some high percentage twos down low, but right now, Michigan is probably not efficient enough offensively and not good enough on the boards to compete with the best teams in the country. I would worry less about four games if the problem was just poor shooting in a small sample, but the problem seems to be about playing style against good defenses. I don’t think that’s going to change.

If you’re interested, here are the Game Stacks for all four games. The trends I discussed are pretty consistent across the games:

Michigan at Indiana 2-2-2013 Ohio State at Michigan 2-5-2013

Michigan at Wisconsin 2-9-2013 Michigan at Michigan State 2-12-2013

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Basketball Stacks part 2: Rebounding

Yesterday, I posted a new idea for visualizing box scores: Game Stacks. While the first version did a good job of showing shooting percentages and turnover rates, it didn’t do a good job on rebounds. As my pops pointed out, Indiana had a big rebounding advantage over Michigan by the basic numbers (36-22), so it seemed wrong to rely only on the height of the stacks to determine who rebounded better. The reality: Michigan got more chances not because they rebounded better, but because they had more misses — and you have to miss to get a second chance. The height of the stacks just showed that Michigan got more offensive rebounds, even though their rebounding rate was terrible.

So, round two. Here’s the Michigan-Indiana Game Stack redesigned to capture rebounding:

Michigan at Indiana 2-2-2013

Without play by play data, I had to keep the rebounding simple — I figured out the offensive rebound rate for each team:

Off reb rate = your off rebs/(their def rebs + your off rebs).

Then, I multiplied this rate by the relevant number of shots to generate the “Missed (O Reb)” category for each type of shot (the dashed regions). Each dashed/empty combo now visualizes the offensive rebound rate for the relevant team.

Now the picture is clearer:

Visualization: Basketball Game Stacks

Note: On my dad’s advice, I posted another version¬†of the Game Stacks that depicts rebounding rates, rather than just total offensive rebounds. The discussion in this post is a little naive on that point — the new version yields a better analysis of rebounding.

I have a general hang up when looking at the box score for basketball (or listening to announcers list off statistics). I see some rebounding numbers, but I can’t tell who rebounded better without offensive and defensive breakdowns, plus the number of shots missed by each team. And I see shooting percentages and shot attempts, but it’s hard to put it all together into how a team got its points.

I realized that what I really want to see is not complicated. Here’s the list:

  • What each team did with their scoring chances:
    • Two point attempts
    • Three point attempts
    • Free throw trips (2 attempts)
    • Turnovers
  • Efficiency on each type of shot
  • Rebounding advantage in terms of extra scoring chances
  • And, of course, total score

All these stats exist, but there should be an easy way to see all of it at once and get a sense for how the game was won. Here’s my first try, the Game Stack:

Michigan at Indiana 2-2-2013

The picture shows total “plays,” or chances to score, for each team, and total points, broken down by type. In a quick glance, you can see that Indiana was out-rebounded (Michigan got three more chances to score) and turned the ball over a ton. However, on just over 60 non-turnover plays, the Hoosiers Continue reading