College Basketball Adjusted Efficiency Explained: How to Use It for Betting

Raw Efficiency vs Adjusted Efficiency

Raw offensive efficiency is simply: points scored ÷ possessions × 100. A team that scores 80 points in 70 possessions has a raw offensive efficiency of 114.3 points per 100 possessions. But if those 70 possessions came against the weakest defense in the country, the 114.3 is not very informative about how good the offense actually is.

Adjusted efficiency corrects for this by factoring in who the opponent was. Scoring 114.3 per 100 possessions against a top-10 defense is dramatically more impressive than the same output against a bottom-50 defense. Adjusted efficiency reweights each game based on opponent quality.

The Efficiency Margin

The efficiency margin is the gap between a team's adjusted offensive efficiency and adjusted defensive efficiency. A team with an adjusted offensive efficiency of 118 and an adjusted defensive efficiency of 100 has an efficiency margin of +18. This margin is the single most predictive metric for team quality in college basketball — more predictive than win-loss record, point differential, or any raw statistical average.

KenPom

KenPom.com (created by Ken Pomeroy) is the original and most widely cited source for college basketball adjusted efficiency ratings. KenPom's methodology adjusts for opponent strength, home court, and game location to produce clean offensive and defensive efficiency ratings for every Division I team. The KenPom efficiency margin ranking is the gold standard for comparing team quality across different conferences and schedule strengths.

KenPom also provides: adjusted tempo (possessions per 40 minutes), luck adjustment (how much close-game outcomes affected record), strength of schedule, and predicted scores for future matchups. Most data requires a subscription, but the top-level rankings are visible for free.

Barttorvik T-Rank

Barttorvik.com (T-Rank) is a free alternative to KenPom with a similar adjusted efficiency methodology plus additional features. Barttorvik adds shot-quality metrics — including effective field goal percentage, offensive rebound rate, free throw rate, and 3-point attempt rate — that are useful for evaluating specific prop categories.

T-Rank also provides game predictions with win probabilities and expected scores for every upcoming matchup. For bettors who don't subscribe to KenPom, Barttorvik is a fully capable free alternative that covers the same core research needs.

HaSlametric

HaSlametric provides player-level advanced analytics for college basketball, including usage rates, per-possession efficiency, and lineup data. While KenPom and Barttorvik focus on team-level efficiency, HaSlametric's player data is useful for evaluating individual prop matchups — specifically how a player performs in specific offensive systems and how their efficiency changes against different defensive schemes.

Evaluating Spread Picks

To estimate the expected spread for a matchup using efficiency data:

1. Look up each team's adjusted offensive efficiency and adjusted defensive efficiency.
2. Apply each team's offense against the opponent's defense to get a projected score per 100 possessions.
3. Multiply by the expected possession count (tempo) and divide by 100 to get a raw projected score.
4. The difference between projected scores is the model-implied spread.
5. Compare to the posted market spread. A gap of 2+ points is worth investigating.

Our CBB game model performs this calculation for every matchup automatically.

Evaluating Totals

Add the two projected team scores for a raw game total estimate. When the model total differs materially from the posted total, there is a potential edge on the over or under. Pace is the key variable — a game between two fast-tempo teams produces more possessions and higher totals than the simple efficiency calculation implies if you forget to adjust for tempo.

Evaluating Player Props With Efficiency Context

Adjusted defensive efficiency tells you how hard it will be for a player to score against today's opponent. A player going against a top-15 adjusted defense should be projected conservatively — even if their season average is strong. Our player projections incorporate opponent defensive efficiency adjustments from this directly into every projection.

Check the opponent's rank in points allowed per possession, then cross-reference with whether the defense is particularly strong against the player's primary scoring mode (perimeter vs post). A perimeter scorer against a team with a top-10 3-point defense rate faces a specific disadvantage that goes beyond just overall defensive efficiency.

Schedule Strength Distorts Raw Numbers

A team from a weak conference might average 85 points per game with a +18 scoring margin — but nearly all of those games came against opponents ranked outside the top 100 in efficiency. Their adjusted efficiency margin might be only +8 because the model adjusts for opponent quality. When this team enters the NCAA Tournament and faces a top-30 opponent, the raw numbers mislead. The adjusted numbers do not.

Home Court Creates False Impressions

Teams with favorable home schedules appear statistically stronger than they are in neutral-court or road environments. KenPom's home court adjustment (approximately 3.75 points) corrects for this systematically. A team that looks like a -8 favorite in their home gym may be closer to a -4.5 favorite at a neutral site — a 3.5 point difference that directly affects prop and total research.

What is adjusted efficiency in college basketball?

Adjusted efficiency measures how many points a team scores or allows per 100 possessions, with statistical adjustments for the quality of opponents faced and home/away context. It is more informative than raw scoring averages because it controls for schedule strength.

Where can I find CBB adjusted efficiency ratings for free?

Barttorvik T-Rank (barttorvik.com) provides comprehensive adjusted efficiency data for free. KenPom (kenpom.com) provides the most widely cited ratings but requires a subscription for full access. Both cover all Division I teams.

How do I use adjusted efficiency to evaluate a CBB game?

Look at each team's adjusted offensive efficiency and defensive efficiency. Apply each offense against the opposing defense to estimate projected scores. Multiply by the expected pace (possessions per game) to get raw point totals. Compare the implied spread and total to the market. Gaps between model and market are worth investigating.

Is KenPom or Barttorvik more accurate for betting?

Both produce similar predictive accuracy at the team level. KenPom's methodology is more widely cited and includes a luck adjustment. Barttorvik adds shot-quality data that is useful for specific prop research. Use both for a complete picture — they are complementary, not competing, tools.