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How We Calculate Everything

A complete breakdown of the math behind our tournament projections, seedings, and bracketology.

1 Quad System

Every game a team plays gets classified into one of four quality tiers based on where the game was played and the opponent's NET ranking. This is the exact system the NCAA Selection Committee uses.

	Home	Neutral	Away
Quad 1	vs NET 1–30	vs NET 1–50	vs NET 1–75
Quad 2	vs NET 31–75	vs NET 51–100	vs NET 76–135
Quad 3	vs NET 76–160	vs NET 101–200	vs NET 136–240
Quad 4	vs NET 161+	vs NET 201+	vs NET 241+

Location matters. A road win at NET #50 is a Quad 1 victory. That same opponent at home is only Quad 2.

2 Strength of Schedule

Our SOS is computed directly from each team's full-season schedule — every game, every opponent. It blends two independent signals into a single composite score:

Signal	Weight	What It Measures
Avg Opponent NET	65%	Mean final-season NET rank of every opponent played. Uses each opponent’s end-of-year NET (not their ranking at game time) so the schedule is evaluated by how strong opponents turned out to be.
Avg Opponent Win%	35%	Mean winning percentage of all opponents. A team that faced .700 opponents had it harder than one facing .500 opponents — even at similar NET averages.

Lower composite = harder schedule. Teams are ranked 1–365 by this score and assigned tier labels:

Tier	Rank Range	Meaning
Brutal	1–25	The toughest schedules in D1. Dominated by Power 6 conference teams in leagues that cannibalize each other.
Tough	26–75	Above-average difficulty. Mix of mid-tier Power 6 and top mid-major teams.
Standard	76–200	Average. The broad middle of D1 scheduling.
Soft	201–365	Below-average. Mostly low-major conferences with few ranked opponents.

Non-D1 opponents (D2/D3/NAIA) are assigned a proxy NET of 350. Teams without full schedule data fall back to a quad-tier estimation using the midpoint NET of each quad (Q1 ≈ 30, Q2 ≈ 90, Q3 ≈ 170, Q4 ≈ 280).

3 Composite Power Rating

This blends four major ranking systems into a single number, then adjusts for resume quality. It powers tournament chance (not seeding — that's separate).

Base Blend

The weighting adapts when data sources are missing:

Scenario	NET	KenPom	Barttorvik	Sagarin
All available	30%	30%	25%	15%
No Barttorvik	35%	35%	—	30%
No KenPom	35%	—	30%	35%
NET + Sagarin only	55%	—	—	45%

Resume Adjustments

Five factors shift the composite up or down:

• Quad record — Q1 wins (+1.0 each), Q2 wins (+0.5), Q2 losses (−0.3), Q3 losses (−2.5), Q4 losses (−6.0)
• Strength of schedule — Top-30 SOS teams get a boost; soft schedules get penalized (boost capped at +5, penalty capped at −3)
• Conference tier — Power 6 (+3), bridge conferences (+1), everyone else (−2)
• Streak — Win streaks add +0.3 per game and losing streaks subtract 0.5 per game, each capped at ±3 points
• AP ranking — Top 25 teams get a small +2 boost

4 Committee Seed Score

This is a completely separate calculation from the composite power rating. It models how the NCAA Selection Committee actually evaluates teams for seeding, based on committee member public statements and historical bracket analysis (2018–2025).

Six weighted factors, each producing a score where lower = better seed:

Factor	Weight	What It Measures
SOS-Adjusted NET	35%	NET ranking amplified or dampened by schedule strength. Hard schedule makes NET more trustworthy; soft schedule suggests inflation. Adjustment capped at ±15%.
Quad Quality Index	25%	Game-by-game resume score. Q1 wins have diminishing returns (the 1st Q1 win is worth more than the 15th). Q3 losses cost −5, Q4 losses cost −10.
Q1 Win Power	15%	Uses Bayesian regression to prevent small-sample flukes. A team that's 2-0 in Q1 isn't truly 100% Q1 quality — we add 6 pseudo-games at 50% to keep it honest. Also rewards volume.
Strength of Schedule	10%	Raw SOS rank. Harder schedule = better seed.
Conference Tier	10%	Historical bias: Power 6 teams seed 3–5 spots higher than mid-majors with identical profiles.
Eye Test	5%	AP Poll ranking + win percentage as a proxy for national perception.

5 Tournament Chance

Tournament chance measures one thing: how likely a team was to earn an at-large bid on résumé alone.

At-Large Probability

All 365 Division I teams were ranked by composite power rating. A sigmoid function converts rank into probability:

The midpoint was set dynamically to the overall rank of the last at-large team to make the 68-team field. Teams well above the cutoff approach 99%. Teams right at the cutoff land near 50%. Below the cutoff, probability drops sharply.

Conference-tournament champions entered the field via their automatic bid regardless of this number — they're shown with a separate AUTO-BID badge, and their percentage remains the at-large-only chance.

Status Thresholds

6 Building the Field of 68

The tournament field is constructed in five steps:

1. Auto-bids: The best team from each conference (by composite power rating) earns an automatic bid. With 31 D-I conferences, that's 31 auto-bids.
2. At-large: The next 37 best teams who aren't already auto-bids fill the remaining spots. 31 + 37 = 68.
3. Seed scoring: All 68 field teams are scored using the committee seed score formula and sorted.
4. First Four: The worst 4 at-large teams play in two play-in games at the #11 seed. The worst 4 auto-bids play in two play-in games at the #16 seed. That's 8 teams in 4 games.
5. Main draw seeding: The remaining 60 teams fill the bracket:
   • Positions 1–40 → seeds 1–10 (four per line)
   • Positions 41–42 → seed 11 (two direct placements)
   • Positions 43–58 → seeds 12–15 (four per line)
   • Positions 59–60 → seed 16 (two direct placements)

7 S-Curve Regional Placement

The NCAA Selection Committee uses a "snake" pattern to distribute teams across four regions so that no single region is dramatically stronger than another.

This ensures the overall #1 team faces the weakest #2 seed in their region, while the #4 overall faces the strongest #2 seed. Regions stay balanced.

Play-In Game Placement

Each of the four play-in games is assigned to a region using the tail positions of the S-curve:

• Seed 11 play-in games go to Midwest and West
• Seed 16 play-in games go to South and East

Every region hosts exactly one play-in game. Both teams in a play-in share the same seed and region — the winner advances into that bracket slot.

8 Bubble Buckets

We surface four groups of four teams each to give a clear picture of the bubble:

Group	Who They Are
Last Four Byes	The 4 at-large teams just above the First Four cut. They made the field without having to play in.
Last Four In	The 4 at-large teams in the First Four play-in games at the #11 seed. They're in, but barely.
First Four Out	The best 4 teams that just missed the field entirely.
Next Four Out	The next 4 closest misses after that.

9 Bracketverse Rating

The Bracketverse Rating is our single composite number for every Division I team. It blends three independent systems into one percentile-normalized score from 1 to 99, where higher is better.

The Three Components

Component	Weight	Source
Power Rank	50%*	Composite blend of NET, KenPom, Barttorvik, and Sagarin (Section 3), adjusted for quad record, SOS, conference, streak, and AP ranking. Captures how strong a team is.
Seed Score	30%*	Committee-style 6-factor resume model (Section 4). Captures how the selection committee would evaluate a team: SOS-adjusted NET, quad quality, Q1 win power, schedule strength, conference tier, eye test.
Trajectory	20%*	Win/loss streaks, AP Poll movement, and ranked status. Captures which direction a team is heading. A team on a 10-game win streak is trending differently than one that just lost 3 in a row — even if their season numbers look similar.

*Early in the season (before streak data is available), the weights automatically shift to 60% Power Rank / 40% Seed Score. Once trajectory data lands, the full 50/30/20 blend activates. No manual adjustment needed — the system adapts. The full 50/30/20 blend is currently active.

How It Works

1. Rank all 365 teams independently on each component. Power rank #1 is the best effComp score; seed score #1 is the strongest committee resume; trajectory #1 has the hottest recent form.
2. Convert ranks to percentiles (0.0 to 1.0 scale) so each component contributes proportionally regardless of its native scale.
3. Weighted average the three percentiles using the weights above.
4. Re-rank the blended scores across all 365 teams and assign final percentiles: #1 → 99, #365 → 1.

Worked Example: Duke (W11 streak)

What Makes It Different

• It's not just one ranking system. NET, KenPom, Barttorvik, and Sagarin all contribute to the power rank component. No single system dominates.
• Resume matters independently. The seed score component evaluates your actual games — who you beat, who you lost to, where you played — the same way the selection committee does.
• Trajectory is weighted separately. A team peaking at the right time gets credit for it. A team collapsing down the stretch gets penalized — even if their season stats still look strong.
• Simulator-aware where it matters. The canonical Bracketverse Rating and Bracketverse Top 25 are computed independently of simulator picks — they reflect the actual season record. The Path to NCAAT simulator uses the same underlying formulas but with hypothetical outcomes layered on, so projected seeds and tournament chances respond to your picks without affecting the published rankings.

10 Bracketverse Top 25

Our own weekly-style ranking of Division I teams, powered entirely by the Bracketverse Rating. No voter bias, no ballot stuffing, no regional favoritism. Pure data.

How Teams Are Selected

1. Sort by Bracketverse Rating (highest first). The top 25 form the official ranking.
2. Tiebreakers (when two teams share the same integer rating):
   • First: higher win percentage
   • Second: tougher strength of schedule (lower SOS rank)
3. Others Receiving Votes: teams ranked 26–35 are listed separately, just like the AP Poll’s tail section.

Tier Labels

Each team gets a tier label based on their Bracketverse Rating value:

Tier	Rating Range	What It Means
Elite	97–99	Championship-caliber teams. Dominant across all metrics — power, resume, and trajectory.
Strong	93–96	Clear tournament teams with strong resumes. Likely seeded 3–6 in bracketology.
Solid	88–92	Tournament-quality teams with some resume gaps. Typically seeded 7–11.
Bubble	Below 88	On the bubble or just outside. Teams that needed late-season wins to secure a bid.

What Makes This Different From AP / NET / KenPom

• No voters. The AP Poll reflects the opinions of 62 media members. Ours reflects data.
• Not single-source. NET is one system. KenPom is one system. Bracketverse blends four ranking systems plus a 6-factor committee resume model.
• Trajectory-aware. When streak and movement data are active, teams trending up get credit and teams fading get penalized — even before their season stats fully reflect the shift.
• Simulator-independent. The published Bracketverse Top 25 reflects the actual season record and will not shift based on hypothetical simulator picks. The game simulator’s projected seeds and tournament chances are computed separately.

No Conference Quotas

There are no rules like “must include at least one team from every power conference.” If 8 of the top 10 are from the SEC, that’s what the data says. We let the numbers speak.

11 Fan Suffering Index

The Fan Suffering Index scores how much a fanbase has endured — a 0–100 "pain" number that powers the Hardest-Luck board. It is deliberately not a measure of how good a program is; blue bloods can score high precisely because expectations make every early exit hurt more. Higher = more suffering.

The Four Components

Component	Weight	What it measures
Drought	35%	Years since the last national title (8 × √years, capped 75; never won = 55) plus years since the last Final Four (0.7 × years, capped 25; never reached = +35).
Tournament	30%	Seed-vs-exit underperformance (a 1-seed bounced in the first round hurts far more than a 12-seed), plus deep-run agony — losing a national championship game (+70) or Final Four (+35) is painful regardless of seed. Recency-weighted so recent wounds count more.
Heartbreak	27%	Season-by-season close losses (×8) and overtime losses (×12), plus a share of the tournament upsets above. The "so many one-possession games" tax.
Snub	8%	Number of seasons left out of the field despite a tournament-worthy resume (×28 per snub).

Seed Expectations

The tournament component compares where a team was seeded to how far it actually went. Each seed carries a reasonable minimum expectation; falling short of it is what generates pain (each round short ≈ 28 points, capped 95, then recency-weighted). Seeds 5 through 8 carry no real burden — a first-round exit costs them nothing, because nobody is shocked when an 8-seed loses.

How the Score Is Built

1. Compute each component on its own 0–100 scale from the team's history feed (title/Final Four droughts, every tournament appearance 2016–2026, per-season close/OT losses and snubs).
2. Blend them: 0.35 · Drought + 0.30 · Tournament + 0.27 · Heartbreak + 0.08 · Snub. Drought leads by design — the longer the wait, the deeper the ache.
3. Forgive recent champions. A team that won the title within the last year has its whole score multiplied by 0.10 — a fresh banner erases the suffering (a 2026 champion should not sit near the top of a pain board).
4. Round and clamp to a final 0–100 score.

Data source: the tournament-history feed covers 211 programs and 627 tournament appearances (2016–2026), with a legacy fallback for any team not yet in the feed. The index is recomputed whenever the underlying data refreshes.