Shot Blocking in 2013

Last season, the player of the year was known for his defense and shot-blocking. But 2013 has been a better year for shot blockers.

First, for those who are unfamiliar with the stat, block % is: Blocked Shots / Opponent 2-pointers Attempted

Before diving into the numbers, I’d like to recommend another article from a couple of years ago about blocked shots. According to Jeff Haley’s math at Burnt Orange Nation, a blocked shot is worth approximately 0.7 points.

The block statistics for this year will be slightly inflated due to the weaker competition of the non-conference schedules, but we’ll re-visit these numbers at the end of the season to see what unfolded.

The data from Kenpom.com shows that there are 36 players this year with a block rate at 10% or higher. The previous mark (in the years with data available) was 26 in 2011.

The chart below looks at the top 20 players in block rates going back to 2005. The average of these shows that the top shot blockers this season have a slightly higher block rate and that it has increased each year since 2009.

Typically good shot blockers also draw more fouls, since they are contesting more shots. The point value of a block can be quickly negated by a foul that sends the other team to the free throw line.

The chart below shows that there are fewer fouls this year, which would indicate that players are blocking with less fouls. However, we would need to look at individual players’ fouls to make that claim.

In the preseason, Jeff Withey was expected to be one of the best shot blockers in the nation. But Withey seems to have also improved in his timing and spacing. Last season, his block-to-foul ratio was 1.87 and he has more than doubled that figure this year. It would take some digging, but he may be on a record-setting pace in this category.

The blocked shot is one my favorite plays in basketball. But it can also be infuriating when a player has an easy block but decides to swat it into the bleachers instead of towards a teammate. In those instances, I’m sure the point value of the block would be much lower than 0.7. Someone should tell Dwight Howard.

2013 seems to be the year of the blocked shot. The infusion of athletic shot blockers has altered the game and has changed the way that teams value recruits.

Blocks Per Minute: Anthony Davis

Below is a scatter plot of blocks and minutes played since 2007 (entire careers, through 2012 season). Anthony Davis blocked a lot of shots.

I don’t usually write too much with my posts, but felt this was important enough…

While going through the charted data, I came across the name Kenny George and my heart sank. He only came on TV a few times, but when he did social media nearly exploded. He was between 7′ 9″ and 7′ 11″. There was so much attention paid to him when he had televised games but, as that last link shows, the attention died down afterwards. Even after his three-month hospitalized battle with a foot infection (where he fought for his life), the number of search queries was about ten times less than when he first came on television.

In any case, he had the eighth-best block-per-minute ratio. (Papa Lo had the highest).

As pointed out in this post by Matt Johnson, Anthony Davis might be the closest thing we’ve seen to Bill Russell. And he doesn’t foul too much either. In the photo below, his entire body is so close to the shooter, but it doesn’t look like he’s touching him at all (even his fingers!). Crazy body control.

 

Best Season Since 1998? A Perspective on Kentucky

In my day job, a lot of respect is given to the Gartner Magic Quadrant. The chart below attempts to plot regular season college basketball data into a similar structure. But the measurements here are much more basic than Gartner’s process.

2012 Kentucky looks like a historically well-balanced team in the one-and-done era. Interestingly enough, while putting this together, I listened to the Apr 4 CBS College Hoops Podcast where Matt Norlander and crew debated whether Kentucky was better than the 1999 Duke.

Side note: If you have any interest in attempting to create a more detailed measurement system similar to the Gartner MQ criteria (“ability to execute” and “completeness of vision”), let me know.

The Final Four: Preseason AP Poll Accuracy

A recent blog post by Ken Pomeroy got me thinking about the preseason AP college basketball poll.

Clicking some of the links within the post made it apparent that, despite having never seen the teams play a real game, the AP voters have been fairly consistent in predicting future success.

As mentioned in this post, once the regular season begins, most AP voters tend to follow an unwritten set of rules (ex. If you lose, you drop. If you win, you move up).

However, in the preseason there isn’t much outside pressure and each voter is able to rank the teams in an organic way. While voters may have a couple of sleeper teams in their top 25, once the ballots are combined it provides a fairly accurate projection…

“The end result is that it provides a better picture of the state of college hoops before the season begins than any single person or algorithm could produce. It’s informed groupthink at its finest.”

Also from the blog post: The preseason #1 has made it to the title game a total of 10 times compared to just six for the final #1.

After looking at the results, of the nine Final Four teams that were unranked in the pre-tournament poll since 1986, five of them were ranked in the preseason poll. (I originally saw ten pre-tourney unranked teams, but received a correction from Pomeroy himself. I’ll blame that on the V-lookup).

By simply adding up the numerical rankings of the teams who have made the Final Four (in the preseason and pre-tournament polls), you’re able to compare the accuracy. The chart below contains data from 1969-2011, separated into four-year segments.

The preseason poll is worse, but not by much. Especially in the last fours years.

Preseason AP College Basketball Poll Performance