Most fans don’t see “KenPom-style rankings” for NBA teams because the league already has something very close to that built in: public advanced stats, power ratings, and team models that basically do what KenPom does for college — just under different names and for a very different environment. In college basketball, KenPom fills a big information gap; in the NBA, that gap barely exists.
What KenPom Actually Does
Ken Pomeroy’s system is designed for college basketball, where:
Teams play very different schedules.
There are hundreds of schools.
Upsets and randomness are common.
His site ranks every Division I team using:
Offensive efficiency: how many points a team scores per 100 possessions.
Defensive efficiency: how many points it allows per 100 possessions.
Adjusted numbers: efficiency is adjusted for strength of opponents and game location.
Pace/tempo: how fast a team plays, measured in possessions per game.
Extras like “luck,” strength of schedule, and predictive ratings.
Sports Illustrated and NCAA explain that KenPom’s main value is as a predictive, per‑possession system that compares teams with very different schedules and styles, especially for March Madness analysis and betting. It gives fans and analysts a cleaner way to answer, “Who is actually good?” when rankings and win–loss records can be misleading.
The NBA Already Has KenPom‑Type Numbers
Now look at the NBA. If you open NBA.com or Basketball Reference, you already see:
Offensive rating (points scored per 100 possessions).
Defensive rating (points allowed per 100 possessions).
Net rating (offensive minus defensive rating).
Pace (possessions per 48 minutes).
The official NBA advanced team stats page lists all of these for every team and lets you sort by net rating, offense, defense, and more.
Other public sites go even further:
Dunks & Threes publishes “team EPM” ratings, based on Estimated Plus‑Minus, and combines that with strength of schedule for a single power number per team.
TeamRankings and other power‑rating sites offer schedule‑strength‑adjusted ratings for NBA teams, very similar in spirit to KenPom’s approach for NCAA.
So, from a pure stats point of view, a “KenPom for NBA” already exists — just under different names and on multiple platforms.
Why KenPom Is Huge in College but Not Needed in the NBA
1. The Schedule Problem Is Smaller in the NBA
In college:
Teams play 30–35 regular‑season games.
They face very uneven competition (some mainly play small schools, others a brutal conference).
Many schools never face each other, so comparing them is hard.
KenPom’s adjusted efficiencies and strength of schedule help you compare, say, a mid‑major that dominated a weak league to a power‑conference team that finished 4th but played a much tougher schedule. That’s why bracketologists, bettors, and even the NCAA selection process talk about KenPom all the time.
In the NBA:
Every team plays 82 games.
Each team faces every other team multiple times in one common league.
There is still schedule strength (home/road balance, back‑to‑backs, travel), but the gap is much smaller than in NCAA. One big reason KenPom got famous — cleaning up a messy schedule landscape — just isn’t as necessary in a single, closed, 30‑team pro league.
2. Long Season Means Less “Luck”
KenPom even tracks “luck” because single‑game variance in college is huge. A hot three‑point shooting night or a weird foul run can totally change a 30‑game season. Over 82 NBA games, that noise washes out much more.
You still get randomness, but net rating and point differential already do a strong job of predicting who is good over a long NBA season. That’s why NBA media often uses net rating by default to judge team quality, without needing a separate branded ranking system.
3. NBA Advanced Stats Are First‑Class Citizens
In college, basic coverage still focuses heavily on win–loss record, polls, and simple box scores. KenPom stands out as a separate “analytics hub.”
In the NBA:
Advanced stats are already fully integrated into the league’s own site.
TV broadcasts often show offensive rating, net rating, pace, and lineup data during games.
Analytics blogs and models are everywhere, from public sites to gambling tools.
Because the league itself has embraced advanced numbers, there’s less room (and need) for one independent brand like KenPom to “own” the conversation.
4. Teams Already Use Even Deeper Private Models
NBA front offices employ analytics staff and data scientists who build internal power ratings more detailed than anything public:
They adjust for injuries, rest, travel, opponent lineups, and even garbage time.
They use tracking data (like player movement and shot quality), not just box scores.
Public systems like Dunks & Threes’ EPM or Cleaning the Glass’s net ratings already give fans a slice of that. In that environment, a simple KenPom‑style rating would feel like just one more version of something people already have in many forms.
5. Less Bracket Culture, Fewer Cinderella Stories
KenPom thrives because:
March Madness is single‑elimination and chaotic.
Fans are desperate for an “edge” when picking upsets and dark‑horse teams.
In the NBA:
The playoffs are seven‑game series; the better team usually wins.
There’s no 68‑team bracket where lower seeds constantly upset favorites in one night.
Because the NBA format is designed to let the best team win more often, predictive rankings are useful but less “sexy” as public tools. Power rankings and betting lines already fill that space.
“But Why Doesn’t Someone Just Copy KenPom for the NBA?”
Technically, people have. They just don’t call it “KenPom for the NBA.”
Examples:
TeamRankings publishes schedule‑adjusted NBA power ratings very similar in spirit to KenPom.
Dunks & Threes offers a team ratings page built from player EPM, giving a predictive team metric and precise strength of schedule, which is exactly the kind of thing Pomeroy does for college.
NBA.com’s advanced team stats show offensive rating, defensive rating, and net rating with league filters; many analysts simply interpret those as “true strength” rankings.
So the real answer is:
The functionality exists.
It’s just not centralized into one famous name the way KenPom is in college.
If someone today launched “NBAPom.com” with:
Adjusted offensive and defensive rating.
Net rating and pace.
Schedule and opponent adjustments.
…it would look almost identical to stats we already get from existing NBA metrics sites.
Key Differences Between KenPom and Typical NBA Team Metrics
Here’s a simple comparison:
| Aspect | KenPom (NCAA) | NBA Team Metrics Today |
|---|---|---|
| Main stats | Adjusted O‑rating, D‑rating, efficiency margin | O‑rating, D‑rating, Net Rating |
| Adjustment for opponents | Yes, heavily (conference and non‑conference) | Yes, via SOS metrics and power ratings on third‑party sites |
| Schedule balance | Very uneven, many small leagues | Single league, everyone plays everyone |
| Core use case | Bracket building, betting edges, seeding discussions | Power rankings, playoff projections, betting lines |
| Data owner | Independent (KenPom site) | League (NBA.com), analytics sites, betting models |
Sources like Sports Illustrated, BetStamp, and NCAA coverage repeatedly highlight how KenPom matters for NCAA seeding and bracket debates. For the NBA, league stats and sites like Dunks & Threes and TeamRankings cover that niche already.
Unique Challenges If You Tried to Build “KenPom for NBA”
If you tried to build your own KenPom‑style NBA rankings site today, here’s what you would run into:
You’d compete directly with NBA.com, which already shows per‑possession team efficiency.
You’d compete with popular analytics platforms that have stronger models (EPM, RAPM, etc.).
You’d need a “hook” beyond what fans see in curated power rankings from ESPN, The Athletic, and others.
You could:
Strip out garbage time, like Cleaning the Glass-style net ratings do, and market that as a more “serious” ranking.
Add luck and schedule‑strength indices to tell fans which teams are overperforming or underperforming expectations.
Provide tools for bettors to simulate series or playoff brackets using your ratings.
But again, that’s a very niche audience compared to the college basketball world, where a single trusted ranking system can shape the entire March Madness conversation.
Practical Example: How An NBA “KenPom Clone” Would Look
Imagine you build this simple model:
Start with NBA.com’s offensive and defensive ratings.
Adjust each team’s stats based on opponent ratings using a TeamRankings-style schedule strength model.
Express each team as:
Adjusted offensive rating.
Adjusted defensive rating.
Overall efficiency margin (Net Rating).
Your final ranking list would look very similar to existing power ratings from sites like Dunks & Threes or other analytics platforms already used in NBA discussions.
So the technical part isn’t hard; the problem is differentiation. For college, KenPom was unique and filled a huge need. In the NBA, you’d basically be re‑branding what many places already provide.
FAQs About KenPom and the NBA
Do NBA teams use something like KenPom internally?
Yes – and more. Teams use models that go beyond simple offensive and defensive ratings. They include player tracking, lineup combinations, shot quality, fatigue, and more. These tools are private and tailored to each franchise’s philosophy.
Could Ken Pomeroy himself create an NBA version?
He could, but his whole brand and business are built around college basketball, where his expertise and value are highest. On the NBA side, the ecosystem is more crowded, and his system wouldn’t stand out as much.
Are there any public “NBA KenPom” sites today?
The closest equivalents are:
NBA.com advanced team stats for raw per‑possession efficiency.
Dunks & Threes team EPM ratings and predictions.
TeamRankings’ schedule‑adjusted NBA ratings.
These all cover much of the same ground, just without the KenPom name.
Why does KenPom matter so much more for college bettors and bracket makers?
Because college has:
More teams.
More uneven schedules.
More randomness in a short season and one‑and‑done tournament.
KenPom helps cut through that chaos and find true team strength in a way basic standings can’t.
Final Thoughts
The short, honest answer to “Why doesn’t anyone create KenPom rankings for NBA teams?” is this:
The NBA already lives in a KenPom‑style world.
Per‑possession efficiency, strength of schedule, and predictive ratings are widely available and built into league and third‑party platforms.
The specific problems KenPom solves for college basketball — uneven schedules, huge team pools, chaotic tournaments — just aren’t as big in the NBA.
If you want KenPom‑type insight on NBA teams, you don’t need to wait for someone to invent it. It’s already there every time you sort teams by net rating on NBA.com, check a power rating on TeamRankings, or look at team EPM on Dunks & Threes.
Sam, a dedicated blogger, has immersed himself in the world of content creation for the past five years. His journey reflects a profound passion for storytelling and insightful commentary. Beyond the digital realm, Sam is a devoted NBA enthusiast, seamlessly blending his love for sports with his writing pursuits.