[NOTE: Almost the exact same article can be written for Baylor, except that Baylor hasn’t played any tough games, and as a result are undefeated. But I wanted to choose just one team to refer to throughout. So, Baylor fans, just Ctrl+H and replace “Michigan State”/”Tom Izzo” with “Baylor”/”Scott Drew”.]

A 6-3 record against a tough schedule certainly isn’t the end of the world, and as The Only Colors pointed out, the Spartans have had plenty of success in the postseason after slow November/December starts. But Michigan State was ranked #2 in the preseason AP poll, and the team is clearly struggling more than expected. Taking a look at their stats page on kenpom.com, what jumps out are the big red splotches on the left: they’re ranked 322nd nationally in Turnover%, 293rd in FT%, and 298th in Steal%. But what are those marks costing Tom Izzo’s team? Quite a lot of offense, it turns out.

#### TURNOVERS/STEALS

One way to gauge the effect of turnovers is to look at what happens when a team *doesn’t* turn the ball over. To calculate a team’s offensive efficiency on possessions where they managed to hang on to the ball (TOAdjOff), I used a simple formula:

TOAdjOff = Adjusted Offensive Efficiency / (1 – Turnover%)

I then subtracted this from their actual adjusted offensive efficiency, to get what I’ll call turnover cost. It tells us how much a team’s adjusted offensive efficiency would increase if they somehow never turned it over. Here’s the top 20 in the country:

In case you’re wondering, that value of 150.6 for TOAdjOff is 3rd in the country, behind Duke and Georgetown. When the Spartans don’t turn it over, they’re among the best of the best.

Of course, a turnoverless team is a pipe dream; a more reasonable goal for the Spartans is to try to improve their TO% from abysmal to merely average. This seems doable – the average MSU TO% over the last 8 years has been 21.4%, which is right in line with this year’s national average of 21.2%. Using the same concept as above, but adjusting TO% to 21.2% instead of 0%, Michigan State ends up with an offensive efficiency of 118.7 (a gain of 6.5 over their current 112.2). That would bump their offensive rank from 26th to 4th, and their Pomeroy ranking from 14th to 5th. Couple that with what I can only assume would be a dip in opponent transition points, and they could rise even higher.

#### FREE THROWS

Michigan State is nearly as poor at free throw shooting as they are at preventing turnovers, but it’s not nearly as important because: A) a missed free throw only costs 1 point, while a wasted possession costs, as we saw above, 1.5 points; and B) there tends to be far fewer free throw attempts than possessions.

The Spartans have a 63.4 FT% so far, compared to a national average of 68.1%. Over their 202 FTA, that amounts to a difference of 9.6 total points. Working back from their number of possessions, that works out to 1.5 points per 100 possessions.

#### ALL TOGETHER NOW

If you add those 1.5 points onto the 6.5 gained from reducing turnovers, Michigan State’s offensive efficiency would rise to 120.2. However, because the gap between the top 4 teams (Duke, Kansas, Ohio State, and Pittsburgh) and the rest of the field is so large, their overall ranking wouldn’t change. Still, if Tom Izzo can tighten up (see also: tighten up) his leaky boat, he’ll have a good chance of floating down to Houston, come April.

Hey, I tweeted at ya. I had to do a bit of algebra before I believed that your formula made sense.

ReplyDeleteI think it would be wiser to just use raw offensive efficiencies, as this better measures how it impacts them on a game-by-game basis. No team ever loses an 'adjusted' point.

Also, an increase in TO% increases your defensive rating as well, which you might want to look into.

On raw vs. adjusted, I think it depends on what you're interested in. If you want to know how many actual points the turnovers have cost, then raw efficiency is better. But if you want to know how it affects your judgment of the quality of the offense, isn't adjusted efficiency better? I guess going forward, I should do something like show both A) the raw points a team has lost, and B) what the new estimate for their adjusted efficiency should be.

ReplyDeleteIt isn't helpful that I used raw numbers in the FT section, huh?

And yeah, I did try to acknowledge the defensive impact of turnovers with the throwaway line in there about allowing fewer transition points, but it is something I'll try to explore more. (I guess by regressing offTO% onto raw DefEff, right?)

Alright, so I regressed offTO% to DefEff and got a correlation of roughly zero.

ReplyDeleteSo here's what turnovers do to an offense, keeping their other four factors equal (tweeted the same, sorry for the tweetspam):

https://spreadsheets.google.com/ccc?key=0AqP4OA02ndh7dG12ZXU2dDZtdy1mMDY4N3Nia05kdGc

After thinking more about this, and reading your blog post (http://thebasketballdistribution.blogspot.com/2010/12/ncaa-four-factor-impact.html for anybody that hasn't seen it - definitely check it out), I'm not sure I want to be using a regression above to deal with either the turnover or the free throw issue.

ReplyDeleteIf it were something more complicated like rebounding, a regression would probably be necessary. But turnovers are simple: every possession has either 1 or 0 turnovers; for possessions with 1 turnover, points=0. So when I want to see how efficient MSU is on possessions where they don't turn it over, I can calculate the exact number (Points/(Poss-TO)). Whereas with rebounding, you could in theory have a possession where you get 500 offensive rebounds and 0 points, or you could eventually score after every single rebound - there's no way to know without looking at the play-by-play. In that case, a regression is probably more helpful.

Now, to estimate the defensive impact of turnovers, a regression will be useful. Even if offTO% and DefEff have a correlation of ~0, I bet offTO% might come in as significant once you account for the defensive Four Factors. I'll work on that this morning if I get a chance (i.e. if my girlfriend doesn't wake up for another hour).

As for free throws, I just realized I am underestimating their impact, because some of the misses are likely on the front end of 1-and-1's. That won't make a huge difference - even if all 9.6 of MSU's extra misses are on the front end of 1-and-1's, that's only costing them ~6.5 more points (assuming ave FT%). But clearly they're NOT all on 1-and-1's, so that number is much lower. Any idea on where I can get info on how what proportion of FTA's are the front end of 1-and-1's?