Sports Edge Index

Rolling accumulator: sum of game edges over the last full season. Tracks who is beating market expectations.

Formula

Index = 1,000 + Accumulator + Live

1. Rolling window
Accumulator sums game edges from last 82 games (NBA/NHL) or 17 games (NFL). Old games drop off automatically.
2. Capture pre-game probability
Before each game, we snapshot the Polymarket win probability. Lakers at 60% → Market Prob = 0.60.
3. Calculate game edge
After game settles: K × (Result − Market Prob)
60% favorite wins: (1 − 0.60) × 20 = +8
60% favorite loses: (0 − 0.60) × 20 = −12
4. Accumulate and rank
Sum of game edges in rolling window. Teams ranked by who consistently beats or misses expectations.

20% underdog winning: +16 pts

80% favorite winning: +4 pts

80% favorite losing: −16 pts

A team can have a losing record but high rating if they consistently cover the spread.

NBA82 games, K=20

NHL82 games, K=20

NFL17 games, K=45

F124 races, tier-based

NFL uses higher K because fewer games means each result carries more weight.

Between games, index adjusts based on odds movement for all upcoming matchups.

Live = Σ (Current − Open) × K × 0.5

All scheduled games contribute equally to live adjustment.

K = 20 (NBA/NHL) or 45 (NFL)

Tier-based accumulator tracking how drivers perform against team's expected baseline over 24-race window.

Team tiers

Tier 1 (McLaren, Ferrari, Red Bull): Expected P1-P6

Tier 2 (Mercedes, Aston Martin): Expected P4-P10

Tier 3 (Alpine, Haas, etc.): Expected P8-P15

Tier 4 (Williams, Sauber): Expected P12-P20

Edge calculation

Edge = (Expected − Actual) × K where K=3. Finish above expected → positive.

Polymarket — Pre-game win probabilities from real-money prediction markets. Prices captured before game start and stored as snapshots.