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Clemson Basketball 2015-16 Season Preview: KenPom Stats Explanation and Examiniation

Ken Pomeroy's statistics, known colloquially as KenPom, provide extremely helpful tools to analyze Clemson through each season. To get you ready for 2015-16, we review some of our favorite KenPom stats and use them to take a peek at the Tigers.

Evan Pike-USA TODAY Sports

Offensive Rating (Ortg)

Offensive rating is a overall measure of offensive efficiency. When using this stat, we need to be careful when comparing feature players to complimentary players. Coaches ask more of feature players, making it challenging for them to remain as efficient as role players who can be more selective about their shots. That said, this is a great shortcut to get a quick view much like QBR for quarterbacks.

It uses a complicated formula that credits made shots, assists, etc and penalizes turnovers missed shots, etc.

"A measure of personal offensive efficiency developed by Dean Oliver. The formula is very complicated, but accurate..." (

Last year, Jaron Blossomgame was incredibly efficient when you consider his usage level and the role he played in the offense as the primary scorer. He had a team high Ortg of 110.1.

If we take a look at the now departed Austin Ajukwa's numbers, we find a 85.5 Ortg. What makes a Ortg dip that low? In his case, it was driven down by a poor shooting percentages. His .389 2P% and .263 3P% last season combined for an eFG% of .391. Speaking of eFG%...

Effective Field Goal % (eFG%)

This multiplies 3P% by 1.5 because 50 (of 100) 3-pointers is worth the same number of points as 75 (of 100) 2-pointers (150 points). This makes it fair to compare post players with 3-point shooters. It’s also the only way to compare teams when one shoots a lot of 3’s and one does not.

For example, when Pittsburgh and Boston College played last season, comparing team FG% might have been misleading. Pitt took very few three-pointers while BC was heaving them up left and right. An equivalent FG% wouldn't yield equivalent results. For the season, Pitt finished with a .446 FG% while BC was right behind them at .445. Of course, those shots don't add up to the same number of points, because BC shot so many more three-pointers. eFG% compensates for this as it adjusts Pitt up to .491 (because they took some three-pointers) and BC all the way up to .508.

Defensive Rebounding % (DR%)

This stat is great because it is easy to interpret and helpful when comparing players with very different levels of playing time (e.g., Blossomgame vs. Smith). It is simply:

Defensive Rebounds / Defensive Rebounding Opportunities

Someone like Josh Smith didn't play enough minutes to attain a high rebounds per game number, but in his limited minutes he did get a large proportion of the rebounding opportunities. At 20.5, Smith is grabbing over one-fifth of defensive rebounding opportunities, best on the team. Of course, Blossomgame had more rebounds, but he played more minutes. This accounts for that.

Additionally, this, along with most of the other KenPom statistics, controls for tempo. Last year, Clemson often slowed games down and minimized total possessions. This means fewer shots, fewer missed shots, and thus fewer rebounding opportunities. If you compare someone on an up-tempo team like VMI to a Clemson player, that VMI player will have an advantage in their opportunity to accumulate traditional statistics.

Offensive Rebounding % (OR%)

This is the same thing as DR% except on the offensive end. Comparing offensive rebounding totals isn't always fair because one team may have missed many more shots than the other had thus had more opportunities to get offensive rebounds. This stat can be especially useful in single game analysis. While others may fall into the trap of saying a team got beat on the offensive boards after looking at raw numbers, these adjusted numbers allow us to see if it was really just because one team missed more shots or if it was real. You'll notice we go out of the way to use these percentage rebounding numbers whenever possible.

Fouls Committed per 40 Minutes (FC/40)

This is pretty self-explanatory. It shows how many fouls a player commits in an average 40 minute span of playing time.

This stat is of special relevance to Clemson. A few players on the roster may qualify as "hackers." Sidy Djitte was the biggest culprit, committing 8.2 fouls per 40 minutes last season. To be a reliable #2 at center he needs to take the next step, and that means defending the basket without tallying foul after foul. Landry Nnoko was at 5.5 fouls and needs to lower that number if he wants to play the minutes you'd expect from a true #1 center. Fortunately, with Josh Smith and Legend Robertin in addition to those two, the Tigers have more front court depth than in recent memory.

Fouls Drawn per 40 Mins (FD/40)

This is the same as above except it’s drawing fouls. This is a great measure of aggressiveness. Last year, Jaron Blossomgame was drawing 5.1 fouls per game, even better than McDaniels the year before (4.8).

Free Throw Rate (FT Rate)

This is another metric that shows how good someone is at drawing fouls. It just divides FTs by FGs and multiplies by 100 so you can see how often they get to the line compared to how many shots they take. This normalizes for players who take more shots than others.

(Free Throws / Field Goals) * 100

Turnover Rate (TO Rate)

This one is fairly complicated and hard to explain for individuals. It's easier to use on a team level when it is simply percentage of possessions that end in a turnover. On an player level, it is the percentage of personal possessions ending in a turnover. We need to be careful when using this to compare players that a coach asks to do very different things. For example, a spot up shooter will have much fewer turnovers than a point guard who is asked to penetrate and create their own shot.

Assist Rate (AST Rate)

This is the same as TO rate only for ASTs. Again, this is a bit easier to use on a team level when it is percentage of possessions that end in an assist and basket.


Finally, a game statistic that's especially useful is the number of possessions in the game. More possessions equals more opportunities to accumulate raw stats. This fluctuation is one reason why advanced stats are so useful.

Last year, Clemson played 62.4 possessions per game, making them one of the lower tempo teams in the NCAA. We've heard that Brownell expects this number to tick up as the speedy Avry Holmes runs the offense. Additionally, the advent of the 30 second shot clock should force this. Clemson settled for jump shots late in the shot clock far too often last year and while I love the defense-first approach, this offense needs more easy scores off turnovers to improve unless they're ready to start knocking down jump shots. This is a stat we'll certainly be keeping an eye on.


For more, please visit this post from our friends over at Blogger So Dear or KenPom's definitions page.