Tempo-Free NCAA Basketball Stats: Thinking outside the Box (Score)

USA TODAY Sports

A quick primer on the stats we'll use all year

We here at Streaking the Lawn are strong proponents of using tempo free statistics to analyze college basketball. We do this because, first of all, it makes us look better. And, second of all, it's the best way to compare players who may play in different systems or are used in different ways.

Tempo-free stats are statistics that, well, don't use tempo. Because different teams play at different tempos, their games will have varying numbers of possessions in which they have the opportunity to garner statistics.

Don't be a pacist! Remember - the Hoos play slow, and limit possessions. So, don't make us look bad! Avoid any statistics that aren't adjusted for pace.

First, I'll discuss why it's important to think critically about the numbers that you may see most commonly referred to in the media. Then, I'll introduce some alternatives that we use at STL, and why they give us a fuller understanding of the game. We'll all be loyal KenPom disciples in no time! The best places to go to use these are scacchoops.com (best place to track live tempo-free stats) and KenPom.com (for ratings and projections).

AVOID...OR USE WITH CAUTION:

Comparing Points (or rebounds or steals or ANYTHING) per game: Points scored is the easiest and most common stat cited when analyzing how a player performed in a game. And we aren't QUITE so pretentious to ignore it here. If Joe Harris scored 25 points in a matchup, that's something to report. However, do use caution using ppg averages to compare players across teams. Per game stats are heavily influenced by the amount of possessions recorded in a game. As a rule of thumb, the slowest teams (UVA) will average 10% fewer possessions than the NCAA average, while the fastest teams (UNC) will average 10% more. So, if Joe Harris averages 20 ppg this season, while PJ Hairston averages 21, Harris is actually averaging significantly more points on any given possession.

Using Rebound Margin EVER: "UVA isn't just outscoring Virginia Tech 30-10 at halftime, but they're outrebounding the Hokies 14-4 also!" is something you will likely here an announcer exclaim this season. And, while this is all very well and good, they've just told you very little about which team is rebounding better. Remember, it's far easier to rebound misses on defense than offense (and impossible, obviously, to rebound after a possession ending in a made basket). If the Hoos just don't miss, their opponents will get very few rebounds, and it's not the fault of how they're playing on the boards. (For the same reason, teams that force many turnovers will tend to have fewer rebounds). Please: NEVER USE REBOUND MARGIN. (Hat tip to @rmj_equals_hero for first showing me the light, years ago).

Comparing shooting %s...without context: If Evan Nolte and Mike Tobey both scored 12 points on 50% shooting, who had the better game, scoring wise? (Hint: They may not have been equal). To know the answer, you'd have to be told more: Nolte shot 8 three-pointers and made 4. Tobey attempted 12 lay-ups, and made 6. Remember, players who shoot lots of three-pointers may shoot a lower %, but be more efficient. Context matters.

Citing +/- information from a given game: Ken Pomeroy wrote more on this than we'll get into here. The short version: There is far too much randomness for this to be meaningful in a 40 minute game.

Stats to use:

These could all be calculated from a simple box-score! If you want to calculate possessions in a given game, the best approximation to use is: Possessions=(FGA-OREB)+TO+(.475*FTA). (A possession could either end in a field goal attempt that is missed or rebounded by the defense, a turnover, or a free throw - Ken Pom determined that the average number of free throws per trip is just a shade under 2, explaining the ".475."

Effective field goal percentage: This is a way of calculate a player's shooting percentage that solves that issue of Nolte hoisting threes, and Tobey banking twos. eFG% is equal to (2pt FGM + 1.5* 3pt FGM) / FGA, since three-pointers are worth 50% more than twos.

Rebounding percentage: Defensive Rebounding % and Offensive Rebound % are our go-tos to see how a team is rebounding. DReb% is simply a team's defensive rebounds divided by their total defensive rebound "opportunities" - to be specific, DReb% = defensive rebounds / (defensive rebounds + opponent offensive rebounds). OReb% is calculated using the same formula, with the terms reversed: OReb% = offensive rebounds / (offensive rebounds + opponent defensive rebounds).

See why this tells us more than "rebound margin"? All external factors are essentially eliminated, and we only look at the likelihood of grabbing a missed shot. In a single game, the DReb% of team A = (1 - OReb% of team B), since every missed shot must be rebounded by one of the two teams.

Free Throw Rate: Calculated as FTA / FGA, this tells us how often a team (or player) is getting to the free throw line and can be used on either offense or defense. UVA's .316 FTR (a tad under 1 free throw attempt for every 3 field goal attempts) was one of its weakest team stats last season. The better teams have this closer to .4.

Turnover Rate: Nothing too complicated here; what percent of possessions result in a turnover (on offense and defense), TO / # possessions. The league average last season was .2 (so 1 in 5 possessions ended in a turnover).

(Team) points per possession: This will show us, at the simplest level, what we can expect a team's offensive and defensive output to be, adjusted for tempo. It's calculated simply as PPP = Total Points / Total Possessions. The league-wide average is generally 1.00; for any given trip on the floor, we expect 1 point to be scored.

Last season, UVA's adjusted (for opponent strength) defensive PPP (or adjusted defensive efficiency), was a solid .897, while it averaged 1.07 PPP on offense. Generally speaking, anything higher than 1.1 PPP (on offense) is very good, as is anything lower than .9 PPP on defense. Remember to adjust for opponent in your mind if you're calculating this yourself.

Offensive Rating: This is one that is hard to calculate...so don't worry about it day-to-day. But it's important in the big picture, and useful at the end of the season in determining which players have been most valuable (and deserving of awards, etc.) KenPom explains it, "The formula is very complicated, but accurate." Generally, KenPom says, anything over 1.10 is good and 1.20 is great, but this is heavily dependent on how much a player is used by his team.


That should cover us for now...but feel free to ask anything down in the comments (or opine if I missed anything important, you geeks!) Looking forward to plenty of elevated, tempo-free discussions here this season!

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