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2026 Guide

NET Rankings
Explained

The NCAA Evaluation Tool ranks every Division I team daily using machine learning developed with Google Cloud. It replaced the RPI in 2018 and is now the Selection Committee's primary metric for March Madness seeding. Here is everything you need to know.

362+
Teams Ranked
All Division I programs
Daily
Update Frequency
Throughout the season
2018
Replaced RPI
Built with Google Cloud
#1
Selection Metric
Used by NCAA Committee

What Are NET Rankings?

The NET (NCAA Evaluation Tool) is the official ranking system used by the NCAA Division I Men's Basketball Committee to evaluate and seed teams for the NCAA Tournament. Introduced for the 2018-19 season, it replaced the RPI (Rating Percentage Index) that had been the standard metric since 1981 — a system widely criticized for being easy to manipulate through scheduling and for ignoring scoring margin entirely.

The NCAA partnered with Google Cloud Professional Services to develop the NET using machine learning techniques. The resulting model evaluates every Division I game through two primary lenses: Team Value Index (TVI), a result-based metric that measures the quality of wins and losses, and Adjusted Net Efficiency, which measures points scored vs. allowed per 100 possessions after adjusting for opponent strength and game location.

The exact formula is proprietary — it cannot be reverse-engineered or independently replicated. This opacity is intentional: the NCAA argues that a secret formula prevents teams from gaming the system. Critics counter that transparency would allow the public to better understand selection decisions. What is known: the NET processes every game result daily, weighting recent results alongside full-season performance to produce a ranking of all 362+ Division I teams.

How NET Rankings Are Calculated

The NET algorithm evaluates five components, each capturing a different dimension of team quality. Adjusted Net Efficiency is the most heavily weighted, but the combination of all five creates a more robust ranking than any single metric alone.

High weight

Team Value Index (TVI)

Result-based metric that evaluates the quality of each win and loss. Rewards beating quality opponents on the road and penalizes losses to weak teams at home. The backbone of how NET evaluates resume quality.

Highest weight

Adjusted Net Efficiency

Points scored minus points allowed per 100 possessions, adjusted for opponent strength and game location. The single most heavily weighted component. Measures how efficiently a team plays on both ends of the floor.

Moderate weight

Winning Percentage

Simple win-loss record. Provides a baseline foundation, but carries less weight than efficiency-based metrics. A 25-6 record means more when the schedule is strong.

Moderate weight

Adjusted Winning Pct.

Win-loss record weighted by opponent quality and game location. A road win against a top-25 team counts more than a home win against a 300+ team. Bridges the gap between raw record and resume quality.

Lower weight

Scoring Margin

Average margin of victory, capped at 10 points per game. The cap prevents teams from being rewarded for running up the score. A 10-point win and a 40-point blowout are treated identically.

Why Efficiency Matters Most

Adjusted Net Efficiency strips away the noise of pace and schedule strength. A team that plays 75 possessions per game and scores 80 points is not necessarily better than one that plays 65 possessions and scores 70. Per-possession efficiency is the single best predictor of how a team will perform against a given opponent, which is exactly what the Selection Committee needs when filling a 68-team bracket.

Source: NCAA.com. The exact weighting of each component is not publicly disclosed. Relative weights are estimated from published research and committee statements.

The Quadrant System

The quadrant system categorizes every game into one of four quality tiers based on the opponent's NET ranking and the game location. The thresholds shift by venue because home court advantage is real — Division I home teams win roughly 60-65% of the time. Beating a team ranked NET #60 on the road is genuinely harder than beating them at home, so the quadrant system gives road and neutral-site games more favorable thresholds.

Example: An opponent ranked NET #60 is a Quad 2 game at home (since #60 falls in the 31-75 range), but a Quad 1 game on the road (since #60 falls within the 1-75 away threshold). This means the same opponent can be a resume-building Quad 1 win if you beat them in their arena, or a less impressive Quad 2 win if you beat them in yours.

Quad 1Elite
Home
NET 1-30
Neutral
NET 1-50
Away
NET 1-75

Wins that make resumes. Losses that are forgivable.

Quad 2Quality
Home
NET 31-75
Neutral
NET 51-100
Away
NET 76-135

Good wins. Expected wins for contenders.

Quad 3Neutral
Home
NET 76-160
Neutral
NET 101-200
Away
NET 136-240

Wins that don't help. Losses that start hurting.

Quad 4Weak
Home
NET 161+
Neutral
NET 201+
Away
NET 241+

Wins are expected. Losses are resume killers.

Quadrants Are Dynamic

Because quadrant assignments depend on your opponent's current NET ranking, they change throughout the season. A November win that was Quad 2 at the time might become Quad 1 by March if your opponent improved, or drop to Quad 3 if they collapsed. The Selection Committee evaluates quad records based on the NET rankings as of Selection Sunday — not when the games were played.

NET vs KenPom vs BartTorvik vs RPI

The NET is not the only ranking system that matters in college basketball. Analysts, bettors, and even committee members reference multiple systems to build a complete picture. Each has different strengths, and understanding how they differ helps you interpret tournament selection decisions.

NET

Free
NCAA Evaluation Tool
Methodology
Machine learning (proprietary)
What it measures
Overall team quality via TVI, efficiency, results
Strengths
Official NCAA ranking; used by Selection Committee; accounts for game location
Weaknesses
Formula is secret; cannot be independently verified; sometimes slow to react to injuries
Authority: Official

KenPom

$20/year
Pomeroy Ratings
Methodology
Deterministic formulas (transparent)
What it measures
Offensive & defensive efficiency per 100 possessions
Strengths
Fully transparent; predictive; offensive/defensive splits; tempo data; four factors
Weaknesses
Does not weight wins/losses directly; subscription required; single methodology
Authority: Industry standard

BartTorvik

Free
T-Rank / BartTorvik
Methodology
Efficiency-based with recency weighting
What it measures
Adjusted efficiency with garbage-time filtering
Strengths
Free; eliminates garbage time; recency bias captures form; historical database
Weaknesses
One-person operation; recency bias can overreact; less established than KenPom
Authority: Growing influence

RPI

Free
Rating Percentage Index
Methodology
Simple formula (25% WP, 50% OWP, 25% OOWP)
What it measures
Win-loss record weighted by opponent strength
Strengths
Simple to understand; long historical record; still referenced for context
Weaknesses
Superseded in 2018; no scoring margin; easily gamed through scheduling; poor predictive power
Authority: Historical only

Which Should You Use?

For predicting tournament selection: focus on NET rankings and quad records, because that is what the committee uses. For predicting game outcomes and evaluating true team quality: KenPom and BartTorvik are more useful because their methodologies are transparent and their efficiency ratings are more predictive. The best analysts use all three — NET for selection context, KenPom for efficiency analysis, and BartTorvik for recent form.

Why NET Rankings Matter for March Madness

The Selection Committee uses NET rankings and quad records as their primary quantitative metrics when filling the 68-team bracket. While they also consider head-to-head results, road records, recent performance, and game film, the NET-driven quad record is the single most discussed data point in the selection room.

Bad losses override good wins. A team with 8 Quad 1 wins but 3 Quad 4 losses will face more scrutiny than a team with 5 Quad 1 wins and zero bad losses. The committee has consistently shown that they view Q3 and Q4 losses as disqualifying red flags — they suggest a team that cannot consistently perform against inferior competition is not tournament-worthy, regardless of their ceiling.

Historical Quad 1 Win Thresholds for At-Large Bids

Lock
8+ Q1 Wins

Virtually guaranteed an at-large bid regardless of other factors. These teams have proven themselves against elite competition repeatedly.

2025-26: Auburn, Florida, Houston had 10+ Q1 wins

Strong
5-7 Q1 Wins

Very likely in the field. Need to avoid bad losses (Q3/Q4) and maintain a reasonable overall record to stay safe.

Typical range for 4-7 seeds on Selection Sunday

Bubble
3-4 Q1 Wins

On the bubble. Need strong supporting metrics — good road record, no Q3/Q4 losses, solid NET ranking — to earn an at-large bid.

The 'last four in / first four out' conversation

Auto-Bid Needed
0-2 Q1 Wins

Extremely unlikely to receive an at-large bid. Must win their conference tournament for an automatic qualification.

Most mid-major and low-major tournament teams

The Resume-Killer: Quad 3 and Quad 4 Losses

Even one or two Q3/Q4 losses can knock a team off the bubble entirely. The Selection Committee has repeatedly cited bad losses as the primary reason for excluding teams with otherwise strong profiles. A single road loss to a team ranked NET #200+ can undo months of quality wins. This is why coaches often say “every game matters” — in the quadrant system, it literally does.

Remember that quad records are dynamic. As opponents' NET rankings shift throughout the season, your quad record shifts with them. A November win over a team that was ranked #45 at the time might be a Quad 3 win by March if that team fell to #180. The committee evaluates the bracket based on Selection Sunday rankings, which means early-season wins against eventually-bad teams provide no shelter.

Frequently Asked Questions

How often are NET rankings updated?

NET rankings are updated daily during the college basketball season, typically in the early morning hours after the previous day's games are processed. The first NET rankings of the season are usually released in late November after teams have played enough games for meaningful evaluation. Rankings are not updated during the offseason.

What replaced RPI in college basketball?

The NET (NCAA Evaluation Tool) replaced the RPI (Rating Percentage Index) starting with the 2018-19 season. The NCAA partnered with Google Cloud Professional Services to build the NET using machine learning techniques. The NET is considered a significant improvement because it accounts for scoring margin (capped at 10 points), adjusts for game location, and uses per-possession efficiency metrics rather than raw win-loss records.

Do NET rankings determine NCAA Tournament seeding?

NET rankings are one of the most important factors the Selection Committee uses, but they do not solely determine seeding. The committee also evaluates quad records (wins and losses by quadrant), head-to-head results, road record, strength of schedule, recent performance trends, and the eye test. However, NET ranking and quad records are the two most quantifiable and heavily discussed metrics during the selection process.

Can a team with a low NET ranking still make the tournament?

Yes, through automatic qualification by winning their conference tournament. Any conference tournament champion receives an automatic bid regardless of NET ranking. At-large bids, however, heavily favor teams in the top 60-70 of the NET rankings with strong quad records. Historically, very few at-large teams have been selected with a NET ranking outside the top 75.

What is the scoring margin cap in NET rankings?

The NET caps the scoring margin at 10 points per game. This means a 10-point win and a 40-point blowout are treated identically for ranking purposes. The cap was designed to prevent teams from running up the score against weaker opponents. It encourages competitive play throughout the game rather than stat-padding in garbage time.

How does NET compare to KenPom?

Both NET and KenPom use efficiency-based metrics, but they differ in key ways. KenPom is a fully transparent, formula-based system that publishes offensive and defensive efficiency ratings, tempo, and four-factor statistics. The NET is a proprietary machine learning model whose exact formula is not publicly disclosed. KenPom tends to be more predictive of future performance, while NET has institutional authority as the NCAA's official ranking. Many analysts use KenPom for analysis and NET for tournament selection context.

Why do NET rankings sometimes disagree with the eye test?

NET rankings are purely mathematical and do not account for context that humans notice, such as injuries, lineup changes, or strength of play in the final minutes. A team that loses close games to elite opponents on the road may have a worse NET than their actual quality suggests. Conversely, a team that dominates a weak schedule may rank higher than the eye test would suggest. The Selection Committee acknowledges this by using both NET data and game film in their evaluations.

Related Pages

View Current NET Rankings Quad Records Guide March Madness Bracket Tips Tournament Simulator Prediction Model Guide NIL & Revenue Sharing Guide