# Adjusted Efficiency

Last updated 2 months ago

Offensive and defensive efficiency come directly from a box score. The four factors lead to the amount of points a team scores and how they choose to play contributes to the amount of possessions a team uses.

It's raw information. The raw offensive efficiency and raw defensive efficiency don't factor in competition.

### Why is is this important?

Here are 2 additional examples of the importance of adjusted efficiencies using KenPom's analysis.

Take Virginia in the 2017-2018 season, Virginia's raw OE was 110.4. This ranked 52nd amongst all Division-I teams.

Virginia plays in the Atlantic Coast Conference. Virginia's strength of schedule was 37th in the country in the 2017-2018 season.

Virginia's AdjO was 115.2, 30th in the country, 22 spots ahead of their raw OE ranking.

In the same season, Villanova posted a raw DE of 99.3. This raw number is good for 51st in the country.

Villanova is part of the Big East Conference. Their strength of schedule was 6th out of 351 teams.

Villanova's AdjD was 94.0, which ranked 11th in the nation, 40 spots ahead their raw DE ranking.

This is why adjustments are important. Competition.

### Another Example

Let's revisit the earlier example of styles of play. We'll use round numbers to make it easier in this fictional example.

Virginia averages 60 possessions per game.

North Carolina averages 72 possessions per game.

The average college basketball game contains 70 possessions.

When North Carolina and Virginia play each other, what is the expected possessions of the game?

The expected possessions in this match-up is 62.

Virginia plays 10 possessions slower than the national average. North Carolina plays 2 possessions faster. The sum is 8 possessions slower than normal.

`Expected possessions = 70 - ((70 - 60) + (70 - 72)) = 62`

A team's pace is determined by how they like to play and how their opponents like to play.

This is the reason efficiency numbers need to be adjusted. It accounts for competition or how a team and their opponents want to play.

## Adjusted Tempo

In every game, each team wants to play at a certain pace. Adjusted tempo tries to tell you the pace each team wants to play.

For example, let's say North Carolina defeated Virginia 72-70.

• Virginia: averages 60 possessions per game

• North Carolina: averages 72 possessions per game

• Expected: 62 possessions

• Actual: 64 possessions

Since we expected the game to result in 62 possessions, an adjustment must be made in the way each team wanted to play this game.

Both team's average possessions are adjusted to reflect the actual game pace. The actual tempo of the game was 3.25% higher than projected possessions.

Each team's average possessions is adjusted by this same percent increase.

This is the adjusted tempo. It's an estimate of the pace a team would have against the team that wants to play at an average Division-I tempo.

`AdjT = Avg. Possessions adjusted by % increase/decrease of actual possessions`

North Carolina's Adjusted Tempo is 74.34 possessions.

`1% of 72 = 0.72 * 3.25 = 2.34 + 72 = 74.34`

North Carolina would have around 74 possessions against a team that plays at the average Division-I tempo.

Virginia's adjusted tempo is 63.87 possessions.

`1% of 60 = 0.60 * 3.25 = 1.95 + 60 = 61.95`

Virginia would have 62 possessions against an opponent that plays at the average Division-I Tempo.

Each team's preference resulted in a game pace of 64 total possessions against each other.

How does this work throughout the season?

â€‹KenPom examines every Division I game with this formula. A season-long adjusted tempo results from averaging a team's adjusted tempo for every game played.

## Adjusted Offensive & Defensive Efficiency

Let's use a fictional example with fictional numbers.

Villanova has an offensive efficiency (OE) of 120.

Alabama A&M has a defensive efficiency (DE) of 120.

The national average for OE is 105.

Villanova's expected OE is 150.

Both team's efficiency is plus 15 from the national average. This is why the expected OE is 150.

Villanova's actual OE is 115.

Alabama A&M's actual DE is 115.

The OE and DE are adjusted to account for competition.

The percent difference of the expected OE and actual OE is 4.35%.

Vilanova's Adjusted OE is 125.

1% of 120 = 1.20 * 4.35 = 5.22 + 120 = 125.22

Villanova's OE would be around 125 against the average Division-I defense.

Alabama A&M's Adjusted DE is 117.

1% of 120 = 1.20 * 4.35 = 5.22 + 120 = 125.22

Alabama A&M's DE would be around 125 against the average Division-I offense.

Remember: Villanova has an above average offense and Alabama A&M has a below average defense in this scenario. Against other competition or average competition, it makes sense Villanova would be perform better and Alabama A&M would perform worse.