How good are these forecasts?
Every forecast scored on seasons the model never saw while its settings were chosen.
Held-back seasons
| Forecast | Forecasts | Log loss | Favourite won |
|---|---|---|---|
| The model | 215 | 0.697 | 49% |
| Base rate | 215 | 0.695 | 48% |
| Recent form | 215 | 0.703 | 50% |
Against the betting markets
Each market's price before the start, scored on the same finished games as the model. A negative figure means the market was more accurate.
| Market | Since | Priced | Model log loss | Market log loss | Model vs market |
|---|---|---|---|---|---|
| Bookmakers (Pinnacle, DraftKings, bet365) | 28 Mar 2026 | 73 | 0.697 | 0.701 | 0.6% |
| Polymarket | 24 Apr 2025 | 98 | 0.702 | 0.701 | −0.2% |
| Kalshi | 29 Apr 2025 | 73 | 0.697 | 0.706 | 1.4% |
A team's home ground is the city it plays in most; it gets home advantage there and nowhere else. Matches abandoned without a result are left out.
A win by wickets is turned into runs (about eight a wicket) so the size of a win can move the rating.
Franchise T20 results are close to a coin flip before a ball is bowled: on the held-back seasons the model is about level with the base rate (see the track record).
Tested on the held-back seasons of the five franchise leagues together (566 matches) and left out, because none beat the ratings alone: player ratings from every men's T20 match (runs above average with bat and ball, or an Elo for each player's XI, which follows a player between leagues), the share of a side's XI kept from last season (what auctions and retentions change), one set of model settings for every league, and counting balls to spare as well as wickets in a chase's winning margin.
The toss isn't in the model: its winner went on to win 52% of these leagues' matches, but it is decided half an hour before the start, after the forecast is made, and on the held-back seasons it helped by less than the noise.
Cricsheet adds matches a few days after they're played, so the latest result can lag.
Questions and answers
How accurate are PodiumOracle's IPL predictions?
On 215 games from held-back seasons (2024 to 2026), which the model never saw while it was tuned, the side it favoured won 49% of the time. Its log loss was 0.697, against 0.695 for the base rate and 0.703 for recent form. Against the betting markets on the same finished games, its log loss was 0.697 against the bookmakers' 0.701 over 73 games, 0.702 against Polymarket's 0.701 over 98 games and 0.697 against Kalshi's 0.706 over 73 games (lower is better).