An explanation of terms: stats + tempo-neutral terminology used on the Rumble

While getting ready to review the St. John's basketball season on the Rumble, I realized that I had never compiled any sort of explanation for the terminology. I realize some of the tempo-fee/ tempo-neutral stuff isn't necessarily familiar to all readers. But they're not magic, they're cobbled together from the box score.  Though I do spend a little time with Excel and Access to slap together some quantitative evidence for what I'm talking about.

Why use these different stats?

Because when you see a fast team putting up 80 or 90 points, a savvy watcher knows that said team isn't necessarily better than a team that scores 65 but scores every time they have the ball. Those differences in style make it hard to make judgments about the quality of scoring when simply looking at the final score; scoring is inflated or deflated by style.

North Carolina coach Dean Smith used per-possession stats to evaluate his team, as did his predecessor, Frank McGuire. Dean Oliver is credited with writing "the book" (Basketball on Paper - find it at your bookseller) on tempo-neutral statistics; his book is more NBA focused, but very, very useful. Ken Pomeroy, John Gasaway, and others have taken on analyzing college basketball.

If you want to know more of the rationale, Gasaway's post, "This is TFS: tempo-free stats" for Big Ten Wonk years ago is a great start. And if you want a whole lot of simply laid out tempo-neutral stats, go to kenpom.com, Ken Pomeroy's site, widely used by bloggers, national writers, and some coaches (Brad Stevens, being one; Mike Krzyzewski and Buzz Williams being others).

(I prefer the term "tempo-neutral," myself, since many of the statistics normalize basketball activity over 1 possession or 100 possessions. There is a tempo!)

A tutorial of the basic tempo-neutral terms, below the fold:

 

Pace/ Possessions: Pace helps compare the offensive outputs for teams that shoot at different rates - the teams that shoot within 10 seconds of getting the ball, and teams that run a deliberate offense. Pace is measured in possessions per game, and can be measured for individual players. The "This is TFS" post goes into the formula and why it works, but it's estimated as FGAs - Offensive Rebs + TOs + (0.475 x FTAs) - basically, all the ways you can end a possession - shooting, turning the ball over, and shooting free throws, but minus offensive rebounds, which keep possessions alive.

This year, the median pace was 66.6 possessions; South Florida and Pittsburgh played the slowest - 63.1 possessions - and Providence was fastest, at 72.7 possessions per game.

Points per possession: How many points does a team score per possession (PPP)? This is a number that allows us to compare teams' (and players') efficiency on a level field. In the Big East, for example, Pittsburgh often plays a slow pace. So if they score 60 points per game, and Providence scores more than 70 points per game, does that mean Providence is a better offensive team? No. Put them in a game together, and no matter what the pace, Pitt will be expected to outscore Providence. (The defense is an issue as well, obviously.)

The median of points per possession - multiplied by 100, to set the "tempo" at 100 possessions - was about 101.1 for NCAA hoops in 2011. On offense, this is the same as offensive efficiency; and the points per possession given up on defense is defensive efficiency.

Efficiency margin: The difference between offensive efficiency and defensive efficiencies - much like points for and points against in any sport. Efficiency margin within conference play often corresponds closely to a team's standing in conference play. It's a basic measure, and holds to highlight teams that may not be as good as their record indicates.

This is prone to occasional skewing if a team is involved in a number of close losses or enjoys some blowout wins, but in a league of near-equals, efficiency margin makes strong hints at who are the pretenders and contenders.

Effective field goal percentage: Effective field goal percentage (eFG%) simply adds .5 points for three-pointers taken, giving an appropriate bump for the types of shots taken. And this makes field goal percentages equivalent, comparable. Two teams can hit 50%, but if one team is hitting all three-pointers, that's going to be a barrage of points, right? Three is still bigger than two.

The formula is (FGM + 0.5 * 3PM) / FGA. A basic truth: 50% and over is good. Below 50% isn't so good. Hitting 33.3% on three-pointers gives a player or a team a 50% on effective field goal percentage. So, if a team only shoots two-pointers but hits under 50%... or if a team only takes threes, but hits, say 28.9% of those shots like Seton Hall did last year... that's not great.

On this site, I'll talk about 2-point percentage (2P%) and three-point percentage (3P%) as well, to get a better sense of what's going right and wrong.

Turnover percentage: On what percentage of possessions does the team (or player) turn the ball over? If a team can't get into its offense, it can't score. You won't get anything if you don't get in position to make an attempt - true in life, and true in basketball.

Calculated as TO/Poss, Turnovers on just over 20% seems to be the median in college basketball. The extreme outliers on the low end are teams like Wisconsin (13.4% last year) who execute very well, and Brigham Young, who get the ball up court and take decisive shots (instead of dribbling the ball around). The bottom was 26.7% from Centenary.

Free throw rate: Free throw rate is the comparison of how many times a team gets to the line versus how many field goals they take - giving a sense of how many times teams get to the line in comparison to each other. Some folks use a free throw rate that includes free throws made (FTM) divided by field goals attempted (FGA); others use FTM/FGA for offense and free throws attempted divided by field goals attempted for defense, since a team can't help how well their opponent shoots at the line. I prefer free throws attempted divided by field goals attempted for both, which focuses on the opportunities created by the offense to score - and it keeps things simple.

Jump shooting teams tend to go to the free throw line less, meaning they have one less way of scoring points. Free throws can help make up shooting disparities - as we will see when we review St. John's banner 2011 season.

Offensive rebounding percentage: How many offensive rebounds does a team get? How many does the team prevent? The basic rebound numbers that you hear in recaps is misleading, because it doesn't speak to what those boards lead to. Did they prevent the other team from getting more shots up? Did those rebounds come as a result of missed shots from the rebounders' team? Many players specialize in one or the other... and that doesn't always mean they're a great rebounder, it might just mean that they're hungry for shots on the offensive end. Not a bad thing, but a factor.

The percentage is calculated by dividing a team's offensive rebounds by the sum of all of available rebounds on that end (team's offensive rebounds + opponents' defensive rebounds), so TEAM's O Rebounds/ (TEAM's O rebounds+ OPP D Rebounds) The median last year was about 32.3% - meaning that the median team grabbed about 32.3% of their own missed shots.

The Old Dominion Monarchs and Pittsburgh Panthers were monster rebounding teams this year. Old Dominion grabbed 45.3% of their misses and only allowed opponents to snag 28.2% of their misses - in other words, they cleared the defensive glass. Pitt grabbed 42.7% of their misses, and only allowed opponents to grab 28.4% as well. In comparison, the young Samford team allowed opponents to grab 37.6% of their available offensive rebounds, and only grabbed 20.4% of their own. (Teams with weak rebounding numbers also tend to attempt a lot of offense from beyond the arc - and Samford also shot the highest ratio of 3-pointers as a percentage of field goals taken - 53.1%.)

The Four Factors: Basketball Reference has a great post on the four factors (with how to calculate them), as developed by Dean Oliver. There are even weights, i.e., the importance of each factor. Note that these are for pro basketball, and the college ball weights might be different... but the order remains around the same:

  • Shooting (40%)
  • Turnovers (25%)
  • Rebounding (20%)
  • Free Throws (15%)

Shooting the ball - and preventing the other team from shooting - is the most important aspect of the game.

Getting shots and restricting how many shots the other team takes is second most important.

Making sure the other team doesn't get second shots - or getting second shots for an offense is third.

Getting to the line is important, but less so than the rest of the factors - GENERALLY. For some teams, based on the year or their system, certain factors are more correlated with a good performance.

For individual statistics, pretty much the same rules apply, though they have to be adjusted for possessions that the player accounted for, or for rebounds available during the time on the floor - which is approximated by using a Minutes Percentage multiplier.

So if you're looking for the offensive rebounding rate for a player who spent 20 minutes of a regulation game on the floor, that player would have had a chance for 50% of the total ORebounds + DRebounds available. It's an approximation, true, but it functions pretty well. The percentage multiplier works for stats like steal percentage. And for more stats and a glossary, check out Basketball Reference's glossary.

Here's hoping this was clear and informative. If you have questions or need clarifications in general, holler at me in the comments or email me (pico [dot] dulce [at] gmail [dot] com).

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