{"id":5329,"date":"2026-10-28T10:00:00","date_gmt":"2026-10-28T10:00:00","guid":{"rendered":"https:\/\/oddspapi.io\/blog\/?p=5329"},"modified":"2026-10-23T13:38:26","modified_gmt":"2026-10-23T13:38:26","slug":"world-series-odds-api","status":"publish","type":"post","link":"https:\/\/oddspapi.io\/blog\/world-series-odds-api\/","title":{"rendered":"World Series Odds API: Price the Next Game 65 Hours Early"},"content":{"rendered":"

If you search for a World Series odds API, you want the moneyline on every game of the series, from more than one book, as JSON. On 23 October 2026 at 13:35 UTC, eleven hours before the first pitch of Brewers v Rays, OddsPapi listed seven series fixtures. Game 1 carried 273 books. Game 2 carried Kalshi and the two Polymarket feeds. No sportsbook had posted it yet.<\/p>\n

To check whether that gap is normal, we pulled the price history of all 29 played 2026 postseason games and found the pattern on every series. Pinnacle, DraftKings and FanDuel post the next game after the previous one ends: the first of the three arrived a median 41 minutes after the last out, and never later than 82 minutes. Kalshi listed 16 of those 19 follow-on games before the previous game had even finished, a median 64 hours ahead. If you want a line on Game 5 while Game 4 is still a day away, you read it from a prediction market, then watch for the sportsbooks to arrive.<\/p>\n

Why a scraper sees an empty series<\/h2>\n

A scraper that polls a sportsbook’s MLB page sees one World Series game at a time. Games 2 to 7 do not exist on that page until the book posts them, so your model has nothing to price and your alert has nothing to compare. When the book does post, it posts in the hour after the last out, which is the hour you are least likely to be watching.<\/p>\n

OddsPapi lists every scheduled game of the series as its own fixture, and attaches every book that quotes each game: 350+ bookmakers in the catalogue, sportsbooks and exchanges and prediction markets under one schema. One \/v4\/odds<\/code> call shows you who is on the board. One \/v4\/historical-odds<\/code> call, free on every plan, shows you when each of them arrived.<\/p>\n

\n\n\n\n\n\n\n\n\n\n
<\/th>\nScrape the sportsbooks<\/th>\nOddsPapi<\/th>\n<\/tr>\n<\/thead>\n
Games 2 to 7<\/td>\nMissing until each book posts them<\/td>\nListed as fixtures from day one, with Kalshi and Polymarket quotes days ahead<\/td>\n<\/tr>\n
Books on Game 1<\/td>\nThe sites you scrape<\/td>\n273 feeds on one call, deduped to 62 distinct price pairs in Step 2<\/td>\n<\/tr>\n
When a book opened a game<\/td>\nOnly if your poller was running<\/td>\nFirst snapshot per book on \/v4\/historical-odds<\/code><\/td>\n<\/tr>\n
Closing margins<\/td>\nYour own archive<\/td>\nLast active price before first pitch, any played game<\/td>\n<\/tr>\n
New game alerts<\/td>\nRe-poll every page<\/td>\nPoll one fixture ID, or take pushed updates over the WebSocket feed<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

When each book opened each LCS game<\/h2>\n

The table below covers both League Championship Series. Each cell shows the time of the book’s first moneyline price on that game, measured from the end of the previous game in the same series (the fixture’s trueEndTime<\/code>). A negative number means the book listed the game before the previous one had finished. The right half shows each book’s closing margin: the overround on its last active moneyline pair before the scheduled first pitch.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Game<\/th>\nStart (UTC)<\/th>\nPinnacle<\/th>\nDraftKings<\/th>\nFanDuel<\/th>\nKalshi<\/th>\nPinnacle close<\/th>\nDraftKings close<\/th>\nFanDuel close<\/th>\nKalshi close<\/th>\n<\/tr>\n<\/thead>\n
NLCS G1<\/td>\n10-12<\/td>\nopener<\/td>\nopener<\/td>\nopener<\/td>\nopener<\/td>\n1.97%<\/td>\n2.91%<\/td>\n2.86%<\/td>\n0.99%<\/td>\n<\/tr>\n
NLCS G2<\/td>\n10-12<\/td>\n+0.6 h<\/td>\n+1.1 h<\/td>\n+1.1 h<\/td>\n-74.7 h<\/td>\n2.04%<\/td>\n2.83%<\/td>\n3.35%<\/td>\n1.00%<\/td>\n<\/tr>\n
NLCS G3<\/td>\n10-15<\/td>\n+1.1 h<\/td>\n+1.5 h<\/td>\n+1.3 h<\/td>\n-102.0 h<\/td>\n2.07%<\/td>\n2.72%<\/td>\n2.86%<\/td>\n1.00%<\/td>\n<\/tr>\n
NLCS G4<\/td>\n10-16<\/td>\n+6.4 h<\/td>\n+1.6 h<\/td>\n+1.4 h<\/td>\n-152.8 h<\/td>\n2.08%<\/td>\n2.72%<\/td>\n2.62%<\/td>\n1.99%<\/td>\n<\/tr>\n
ALCS G1<\/td>\n10-13<\/td>\nopener<\/td>\nopener<\/td>\nopener<\/td>\nopener<\/td>\n2.08%<\/td>\n2.81%<\/td>\n2.97%<\/td>\n1.01%<\/td>\n<\/tr>\n
ALCS G2<\/td>\n10-14<\/td>\n+0.4 h<\/td>\n+2.1 h<\/td>\n+0.8 h<\/td>\n-46.9 h<\/td>\n2.04%<\/td>\n2.80%<\/td>\n2.91%<\/td>\n1.00%<\/td>\n<\/tr>\n
ALCS G3<\/td>\n10-15<\/td>\n+0.2 h<\/td>\n+1.4 h<\/td>\n+1.3 h<\/td>\n-70.6 h<\/td>\n1.93%<\/td>\n2.73%<\/td>\n2.79%<\/td>\n2.00%<\/td>\n<\/tr>\n
ALCS G4<\/td>\n10-18<\/td>\n+30.1 h<\/td>\n+31.5 h<\/td>\n+30.4 h<\/td>\n-39.3 h<\/td>\n1.95%<\/td>\n2.66%<\/td>\n2.86%<\/td>\n0.99%<\/td>\n<\/tr>\n
ALCS G5<\/td>\n10-18<\/td>\n+1.4 h<\/td>\n+1.7 h<\/td>\n+1.8 h<\/td>\n-19.6 h<\/td>\n1.99%<\/td>\n2.79%<\/td>\n2.87%<\/td>\n0.99%<\/td>\n<\/tr>\n
ALCS G6<\/td>\n10-20<\/td>\n+0.6 h<\/td>\n+1.8 h<\/td>\n+0.6 h<\/td>\n-0.2 h<\/td>\n2.04%<\/td>\n2.90%<\/td>\n3.37%<\/td>\n1.00%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

ALCS Game 4 breaks the pattern for a known reason. Its first date, 17 October, shows up on the feed as a Cancelled<\/code> fixture, and the books posted the new date 30 hours after Game 3. We left it out of the medians. Across the other 19 follow-on games of the postseason (1 to 20 October), the first sportsbook arrived 12 to 82 minutes after the last out, and Kalshi beat the first sportsbook to the game on 17 of 19, by a median 65 hours.<\/p>\n

Three more things the table shows:<\/p>\n