Show HN: How NBA teams perform vs. prediction market expectations Hi HN, we built this. The NBA Edge Index uses pre-game win probabilities from Polymarket (real-money prediction markets). After each game finalizes, we compare the outcome to the pre-game odds. Beating expectations moves a team's rating up; underperforming moves it down. Each team starts at 2000, and ratings accumulate game-by-game throughout the season. Updates happen automatically after games finalize. A few data points we found interesting: Polymarket odds are pretty accurate on average: teams priced at 80%+ won 82% of the time (119 games), and teams priced 60–69% won 63%. Biggest overperformer: Phoenix Suns, +14.7% vs expectations (market gave them 45.8% avg odds; they won 60.5%). Most overrated by market: Cleveland Cavaliers — 55.8% win rate but market gave them 67.4% implied. They've lost 12 games as heavy favorites. Biggest called upset: Utah Jazz beat Cleveland on Jan 13 with 18.5% market odds; our edge model gave Utah 70.9%. Stability: After ~40 games per team, rankings start to diverge meaningfully and early noise smooths out. We're working on more indices like this. The core idea: prediction market data is fragmented across hundreds of contracts that expire and disappear. We turn it into persistent, trackable indices. Two patterns we use: Composite — Blend related markets into one number. Our Global Conflict Risk Index combines ~15 Polymarket contracts (Ukraine, Taiwan, Iran) into a single number. Rolling — Auto-replace expiring contracts. For example our weather indices track 6-city temperature deviations by rolling forward daily. Curious to hear feedback or suggestions of ideas for other indices. The live NBA Edge index is here: https://attena.xyz/nba |