Defensive Score Sheet: Missouri@Kansas

If you’re unfamiliar with this series, check out my first Project Defensive Score Sheet post. This one’s a day late, but these numbers are pretty ugly, so I doubt anybody was exactly giddy with anticipation.

Let’s start with the table:

Nerds of a Feather Work Together

I don’t know if anybody has noticed my recent more frequent (and during usual business hours) posting, but that was a bit of foreshadowing. I’m excited to announce that, starting today, my primary job for the rest of the college basketball season will be to work with TeamRankings.com. I’ll be doing a lot of behind-the-scenes analysis and marketing work, but you guys will mostly notice that I should shortly begin posting regularly on their blog. I’ll continue posting here in my free time, but in order to read everything I write, I encourage you to bookmark the TR blog, and follow TR on Twitter (@TeamRankingsCBB for college basketball, @TeamRankings for general sports). So, head on over and check TeamRankings out. Here’s a fun place to start.

Defensive Score Sheet: Kansas@Nebraska

[For a recap of what the numbers below mean, and what this series is all about, see my first Project Defensive Score Sheet post.]

Here’s the score sheet (note that Nebraska’s team line has 10 free throws, because those were clearly strategic end-of-game intentional fouls). My thoughts are after the break.

Free throws and “Luck”

In light of today’s great post on Free Throw Plus by John Ezekowitz, I thought I’d share something I noticed a couple days ago. I had heard some Twitter chatter about Illinois consistently ranking low in Ken Pomeroy’s Luck metric, which essentially tells you which teams have tended to be on the right/wrong side of close games. (They’ve fared no better than 158th in the past 7 years.) It made me wonder if they were doing something specific that would lead to their low ranking. So, I decided to see if any of the stats kept by Pomeroy correlate to “Luck.”

Using 2010 team stats, here’s what I found. I highlighted SOS-related stats in yellow, offensive free throw stats in green, defensive free throw stats in red, and bolded tempo. The bars at the right represent the magnitude of the correlation, but keep in mind that the sign also matters:

Defensive Score Sheet: Kansas@Texas Tech

[For explanation of what’s below, check out the original Project Defensive Score Sheet post.]

This one will be quick, as it wasn’t a very intriguing game, and I’ve got a busy day. Here’s the table, notes after the break.

Defensive Score Sheet: Kansas State@Kansas

[As always, check out my first Project Defensive Score Sheet post for information on what this all mean. Also, shout out to Ray Floriani for taking a cue from by good/bad shots tracking, and doing it for St. Bonaventure.]

Sorry this is so late. I promise tonight’s game against Texas Tech will be up tomorrow. Here’s the table. My thoughts are after the break.

Time of Possession & single-team pace

Ohio State’s narrow escape against Northwestern last night presents a great opportunity to talk about an idea that I floated on Twitter a few days ago: keeping track of time of possession (TOP) for basketball teams. That was inspired by an absolutely fantastic post by Rohan Cruyff, who used shot clock data to break down NBA teams’ pace into offensive and defensive “Speed Indexes.” His basic idea: a single number that represents the pace of a team and/or game doesn’t really describe what happens on the court. A fast-paced game can be cause by one team playing at a normal speed, but the other team shooting super early in the shot clock.

Or, as happened last night, a slow-paced game can be caused by one team running the clock down on every possession.

I went through the play-by-play for last night’s game and recorded how much time elapsed on the clock before the first action (shot, turnover, or foul that leads to free throws) of each team’s possession. Here’s what that distribution looked like for each team: