An NBA second-half total of 104.5 is two different bets. One settles on the points scored in the third and fourth quarters. The other counts overtime as well. Both carry the line number 104.5, both read as a totals market, and different bookmakers quote different ones.<\/p>\n
The OddsPapi catalogue separates them with a field called One call to Two rows in that table shadow two other rows. Pull the handicap values off both ladders and the collision is total.<\/p>\n The regulation ladders are half-point rungs in steps of a full point. The overtime ladders take the same half-point rungs and add the whole numbers between them. Sort a merged board by line number and the two clocks interleave without a single duplicate to warn you.<\/p>\n The market name does carry the clock, in the suffix Authentication is a query parameter. The key rides on Group the definitions by Two ladders, 140 regulation line numbers, and all 140 appear again on the overtime clock. Spreads and team totals dodge the problem by existing on the overtime clock alone: Detroit Pistons v Boston Celtics opens the 2026-27 season on 20 October. One unfiltered Twenty-nine days out, four market IDs sit on a half or quarter clock. The The quarter and half ladders fill in during the days before tip-off, which is where the trap sits. A resolver written against a T-29d board never meets the twin clocks, then meets both of them an hour before the first jump ball. Build the branch now and test it on a fixture that has already finished.<\/p>\n A live board outside the market-open window reports a false zero, so test coverage on a game that has been played. San Antonio Spurs v New York Knicks, Game 5 of the 2026 Finals, tipped at 00:30 UTC on 14 June. Caesars closed 104.5 on the regulation clock at 1.909 and BetRivers closed 104.5 on the overtime clock at 1.84. Merge on the line number and Caesars reads as a 3.8% better price on the Over. The two quotes are not competing, because they settle on different scores. Caesars ran 6.94% overround across all three of its rungs and BetRivers ran 6.43%, so the margin gap does not explain the price gap either.<\/p>\n The split runs deeper than one line. Across the eleven books read on that fixture, DraftKings priced the second half on both clocks, 25 market IDs on Game 5 finished in regulation, so The detector is one comparison. If Key every basketball market on the pair The same field carries the same weight in ice hockey, where 118 markets ship in both flavours<\/a>, and in baseball, where the result settles under four IDs across three clocks<\/a>. Basketball is the version where the two ladders overlap on every rung.<\/p>\n One Start on the free tier<\/a>: 250 requests a month, every sport, every bookmaker, no card. Then read how the full-game ladders sort by the handicap field<\/a>, how to rank the books on an NBA board<\/a>, and what the NBA player-prop menu holds<\/a>. If you want the wide view first, the free-tier walkthrough<\/a> covers auth, discovery and pagination in one pass.<\/p>\n Ten values plus a null. Read Yes. Over Under Second Half holds 90 rungs from 40.5 to 129.5 in steps of a full point. Over Under Second Half (incl. overtime) holds 180 rungs from 40.5 to 130.0 in steps of half a point, and all 90 regulation rungs appear in it. Fourth-quarter totals behave the same way at 50 and 100 rungs.<\/p>\n It varies by book and by market. On San Antonio v New York on 14 June 2026, DraftKings priced the second half on both clocks, 25 market IDs on The catalogue holds 90 second-half totals on the regulation clock and no spread or team total there. Handicap Second Half and the team totals exist on period<\/code>. Read it and the two bets separate. Skip it and a cross-book comparison lines up a regulation bet against an overtime bet and calls the gap an edge. Every number below comes from a call made on 21 September 2026.<\/p>\nBasketball Runs on Ten Clocks<\/h2>\n
\/v4\/markets<\/code> returns 33,115 definitions across every sport. Filter on sportId: 11<\/code> and 4,902 of them are basketball. Group those by period<\/code>.<\/p>\n\n\n
\n period<\/code><\/th>\nSettles on<\/th>\n Definitions<\/th>\n What lives there<\/th>\n<\/tr>\n<\/thead>\n \n\n result<\/code><\/td>\nthe final score, overtime included<\/td>\n 1,205<\/td>\n the two-way Winner, 401 totals, 321 spreads, every player prop<\/td>\n<\/tr>\n \n p3+p4+overtime<\/code><\/td>\nthe second half plus overtime<\/td>\n 781<\/td>\n 180 totals, 201 spreads, 400 team totals<\/td>\n<\/tr>\n \n p1+p2<\/code><\/td>\nthe first half<\/td>\n 691<\/td>\n 90 totals, 201 spreads, 400 team totals<\/td>\n<\/tr>\n \n p1<\/code><\/td>\nthe first quarter<\/td>\n 609<\/td>\n totals, spreads, team totals, first-quarter player props<\/td>\n<\/tr>\n \n p4+overtime<\/code><\/td>\nthe fourth quarter plus overtime<\/td>\n 521<\/td>\n 100 totals, 141 spreads, 280 team totals<\/td>\n<\/tr>\n \n p2<\/code><\/td>\nthe second quarter<\/td>\n 473<\/td>\n totals, spreads, team totals<\/td>\n<\/tr>\n \n p3<\/code><\/td>\nthe third quarter<\/td>\n 473<\/td>\n totals, spreads, team totals<\/td>\n<\/tr>\n \n p3+p4<\/code><\/td>\nthe second half, 48 minutes only<\/td>\n 90<\/td>\n totals and nothing else<\/td>\n<\/tr>\n \n p4<\/code><\/td>\nthe fourth quarter, 48 minutes only<\/td>\n 52<\/td>\n 50 totals, a three-way result, a two-way winner<\/td>\n<\/tr>\n \n fulltime<\/code><\/td>\nthe score after 48 minutes<\/td>\n 1<\/td>\n market 113<\/code>, Regular Time Result, with a draw leg<\/td>\n<\/tr>\n\n null<\/code><\/td>\nunset<\/td>\n 6<\/td>\n First Half Result, Second Half Result and four others<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n p3+p4<\/code> is the second half without overtime and p3+p4+overtime<\/code> is the second half with it. p4<\/code> and p4+overtime<\/code> do the same job for the fourth quarter. The first half needs no twin, because overtime cannot reach it.<\/p>\nEvery Regulation Line Number Has an Overtime Twin<\/h3>\n
\n\n
\n \nLadder<\/th>\n Rungs<\/th>\n Span<\/th>\n Step<\/th>\n Line numbers shared with the twin<\/th>\n<\/tr>\n<\/thead>\n \n Over Under Second Half<\/td>\n 90<\/td>\n 40.5 to 129.5<\/td>\n 1.0<\/td>\n 90 of 90<\/td>\n<\/tr>\n \n Over Under Second Half (incl. overtime)<\/td>\n 180<\/td>\n 40.5 to 130.0<\/td>\n 0.5<\/td>\n 90 of 180<\/td>\n<\/tr>\n \n Over Under Fourth Quarter<\/td>\n 50<\/td>\n 20.5 to 69.5<\/td>\n 1.0<\/td>\n 50 of 50<\/td>\n<\/tr>\n \n Over Under Fourth Quarter (incl. overtime)<\/td>\n 100<\/td>\n 20.5 to 70.0<\/td>\n 0.5<\/td>\n 50 of 100<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n (incl. overtime)<\/code>. That suffix is the only thing separating the names, so any normaliser that strips parentheses, lowercases and trims will fuse the two ladders into one. Match on period<\/code>, which is a short enum, rather than on a string you have to clean.<\/p>\nOld Way vs OddsPapi<\/h3>\n
\n\n
\n \nJob<\/th>\n Scraping or a single-book feed<\/th>\n OddsPapi<\/th>\n<\/tr>\n<\/thead>\n \n Tell a regulation half from an overtime half<\/td>\n Parse the market’s display name and hope<\/td>\n Read period<\/code> on \/v4\/markets<\/code><\/td>\n<\/tr>\n\n List every second-half line a book offers<\/td>\n Walk one sportsbook’s markup<\/td>\n Filter 4,902 definitions on two enum values<\/td>\n<\/tr>\n \n Compare the 104.5 across books<\/td>\n Match on the number and merge two bets<\/td>\n Key on (period, handicap)<\/code><\/td>\n<\/tr>\n\n Check what a closed market paid<\/td>\n No history, so no check<\/td>\n \/historical-odds<\/code> on the free tier<\/td>\n<\/tr>\n\n Grade it after the buzzer<\/td>\n Scrape a scoreboard<\/td>\n \/v4\/scores<\/code> returns every quarter as its own key<\/td>\n<\/tr>\n\n Price<\/td>\n Proxies, breakage, legal risk<\/td>\n Free tier, 250 requests a month, no card<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n Step 1: Print the Clock Map<\/h2>\n
?apiKey=<\/code> and never in a header.<\/p>\nimport os, requests, collections\n\nAPI_KEY = os.environ[\"ODDSPAPI_API_KEY\"]\nBASE_URL = \"https:\/\/api.oddspapi.io\/v4\"\n\nmarkets = requests.get(f\"{BASE_URL}\/markets\", params={\"apiKey\": API_KEY}).json()\nbasketball = [m for m in markets if m[\"sportId\"] == 11]\n\nclocks = collections.Counter(str(m[\"period\"]) for m in basketball)\nfor period, count in clocks.most_common():\n print(f\"{period:18} {count:>5} market definitions\")\n\nprint(f\"\\n{len(basketball)} basketball market definitions in all\")<\/code><\/pre>\nresult 1205 market definitions\np3+p4+overtime 781 market definitions\np1+p2 691 market definitions\np1 609 market definitions\np4+overtime 521 market definitions\np2 473 market definitions\np3 473 market definitions\np3+p4 90 market definitions\np4 52 market definitions\nNone 6 market definitions\nfulltime 1 market definitions\n\n4902 basketball market definitions in all<\/code><\/pre>\n\/v4\/markets<\/code> ignores a sportId<\/code> parameter and hands back all 33,115 definitions, so filter on the client. Six of the basketball definitions carry period: None<\/code>, among them Second Half Result and First Half Result. A dictionary keyed straight on period<\/code> will trip over those six, so coerce the value before you use it as a key.<\/p>\nStep 2: Find the Twin Ladders<\/h2>\n
marketName<\/code>, then look for any name that also exists with the (incl. overtime)<\/code> suffix.<\/p>\nladders = collections.defaultdict(set)\nfor m in basketball:\n ladders[m[\"marketName\"]].add(m[\"handicap\"])\n\nSUFFIX = \" (incl. overtime)\"\nfor name in sorted(ladders):\n twin = name + SUFFIX\n if twin not in ladders:\n continue\n regulation, overtime = ladders[name], ladders[twin]\n print(f\"{name}\")\n print(f\" regulation clock : {len(regulation):>3} lines, {min(regulation)} to {max(regulation)}\")\n print(f\" overtime clock : {len(overtime):>3} lines, {min(overtime)} to {max(overtime)}\")\n print(f\" line numbers on both: {len(regulation & overtime)}\\n\")<\/code><\/pre>\nOver Under Fourth Quarter\n regulation clock : 50 lines, 20.5 to 69.5\n overtime clock : 100 lines, 20.5 to 70.0\n line numbers on both: 50\n\nOver Under Second Half\n regulation clock : 90 lines, 40.5 to 129.5\n overtime clock : 180 lines, 40.5 to 130.0\n line numbers on both: 90<\/code><\/pre>\np3+p4<\/code> carries 90 totals and nothing else, and p4<\/code> carries 50 totals plus a three-way result and a two-way winner. Ask for a regulation second-half spread and no book has one to sell you.<\/p>\nStep 3: Split a Live Board by Clock<\/h2>\n
\/v4\/odds<\/code> call on it returned 9.23 MB at 13:09 UTC on 21 September, 29 days out.<\/p>\nFIXTURE = \"id1100013273682354\" # Detroit Pistons v Boston Celtics, 20 Oct 2026\n\nclock = {str(m[\"marketId\"]): m[\"period\"] for m in basketball}\n\nboard = requests.get(f\"{BASE_URL}\/odds\",\n params={\"apiKey\": API_KEY, \"fixtureId\": FIXTURE}).json()\n\nids = collections.defaultdict(set)\nbooks = collections.defaultdict(set)\nfor slug, book in board[\"bookmakerOdds\"].items():\n for market_id in book.get(\"markets\", {}):\n period = clock.get(market_id, \"UNKNOWN\") or \"null\" # 6 definitions ship period None\n ids[period].add(market_id)\n books[period].add(slug)\n\nprint(f\"{len(board['bookmakerOdds'])} bookmakers on the fixture\\n\")\nfor period in sorted(ids, key=lambda p: -len(ids[p])):\n print(f\"{period:14} {len(ids[period]):>4} market IDs {len(books[period]):>4} bookmakers\")<\/code><\/pre>\n221 bookmakers on the fixture\n\nresult 526 market IDs 220 bookmakers\np1+p2 4 market IDs 4 bookmakers\nfulltime 1 market IDs 65 bookmakers<\/code><\/pre>\nresult<\/code> clock holds 526 of the 531 priced IDs and 220 of the 221 books. Market 113<\/code>, Regular Time Result, draws 65 books on its own: that is the three-way bet on the 48-minute score, draw leg included, and it settles differently from the two-way Winner that 220 books quote on the same fixture. Both markets read the same scoreline and they pay out under different rules.<\/p>\nStep 4: Read the Twins on a Played Fixture<\/h2>\n
\/historical-odds<\/code> keeps the full menu after the buzzer and takes at most three bookmaker slugs a call.<\/p>\nFIXTURE = \"id1100013270505012\" # San Antonio v New York, tipped 14 Jun 2026 00:30 UTC\nTIP_OFF = \"2026-06-14T00:30:00.000Z\"\nNAMES = (\"Over Under Second Half\", \"Over Under Second Half (incl. overtime)\")\n\ndefs = {str(m[\"marketId\"]): m for m in basketball}\n\nhistory = requests.get(f\"{BASE_URL}\/historical-odds\",\n params={\"apiKey\": API_KEY, \"fixtureId\": FIXTURE,\n \"bookmakers\": \"caesars,betrivers,draftkings\"}).json()\n\ndef closing(snapshots):\n live = [s for s in snapshots if s[\"active\"] and s[\"createdAt\"] < TIP_OFF]\n return live[-1][\"price\"] if live else None\n\nrows = collections.defaultdict(dict)\nfor slug, book in history[\"bookmakers\"].items():\n for market_id, market in book.get(\"markets\", {}).items():\n spec = defs.get(market_id)\n if not spec or spec[\"marketName\"] not in NAMES:\n continue\n labels = {str(o[\"outcomeId\"]): o[\"outcomeName\"] for o in spec[\"outcomes\"]}\n quote = {}\n for outcome_id, outcome in market.get(\"outcomes\", {}).items():\n price = closing(outcome[\"players\"][\"0\"]) # a LIST on this endpoint\n if price:\n quote[labels[outcome_id]] = price\n if len(quote) == 2:\n rows[spec[\"handicap\"]][slug] = (spec[\"period\"], quote)\n\nfor line in sorted(rows):\n for slug, (period, quote) in sorted(rows[line].items()):\n print(f\"{line:>6} {slug:<11} {period:<15} Over {quote['Over']:<6} Under {quote['Under']}\")<\/code><\/pre>\n 103.5 caesars p3+p4 Over 1.833 Under 1.909\n 104.5 betrivers p3+p4+overtime Over 1.84 Under 1.92\n 104.5 caesars p3+p4 Over 1.909 Under 1.833\n 105.5 betrivers p3+p4+overtime Over 1.92 Under 1.84\n 105.5 caesars p3+p4 Over 1.909 Under 1.833\n 106.5 betrivers p3+p4+overtime Over 1.93 Under 1.83<\/code><\/pre>\np3+p4<\/code> and 24 on p3+p4+overtime<\/code>. Pinnacle priced 17 second-half IDs and 27 fourth-quarter IDs, every one of them on the overtime clock and none on regulation. Caesars went the other way on the second half. Rank a second-half board across those three books without branching and you rank three different bets.<\/p>\nStep 5: Grade Both Clocks<\/h2>\n
\/v4\/scores<\/code> returns each quarter under its own key, so you can build either settlement figure yourself.<\/p>\nperiods = requests.get(f\"{BASE_URL}\/scores\",\n params={\"apiKey\": API_KEY, \"fixtureId\": FIXTURE}\n ).json()[\"scores\"][\"periods\"]\n\ndef total(key):\n p = periods[key]\n return p[\"participant1Score\"] + p[\"participant2Score\"]\n\nq3_q4 = total(\"p3\") + total(\"p4\") # p3+p4\nsecond_half_with_ot = total(\"result\") - total(\"p1\") - total(\"p2\") # p3+p4+overtime\n\nprint(f\"quarters {total('p1')} \/ {total('p2')} \/ {total('p3')} \/ {total('p4')}\")\nprint(f\"regulation {total('fulltime')}\")\nprint(f\"final {total('result')}\")\nprint(f\"p3+p4 {q3_q4}\")\nprint(f\"p3+p4+overtime {second_half_with_ot}\")\n\nfor line in (103.5, 104.5, 105.5, 106.5):\n reg = \"Over\" if q3_q4 > line else \"Under\"\n ot = \"Over\" if second_half_with_ot > line else \"Under\"\n print(f\"{line:>6} p3+p4 {reg:<5} p3+p4+overtime {ot}\")<\/code><\/pre>\nquarters 36 \/ 43 \/ 58 \/ 47\nregulation 184\nfinal 184\np3+p4 105\np3+p4+overtime 105\n 103.5 p3+p4 Over p3+p4+overtime Over\n 104.5 p3+p4 Over p3+p4+overtime Over\n 105.5 p3+p4 Under p3+p4+overtime Under\n 106.5 p3+p4 Under p3+p4+overtime Under<\/code><\/pre>\nfulltime<\/code> and result<\/code> both read 184 and the two clocks graded the same way on all four lines. That is the ordinary case, and it is what makes the bug quiet. The clocks only separate when a game goes past 48 minutes, and a resolver that has never met one of those games looks correct for a whole season of backtests.<\/p>\nfulltime<\/code> and result<\/code> differ, the game went to overtime and every p3+p4<\/code> grade parts company with its p3+p4+overtime<\/code> twin. Add it to your settlement loop and the exceptions surface on their own.<\/p>\nThe Rule<\/h2>\n
(period, handicap)<\/code>, never on the name and never on the line number. That one change fixes four separate comparisons:<\/p>\n\n
111<\/code> settles after overtime and market 113<\/code> settles at 48 minutes with a draw leg.<\/li>\nGet the Board<\/h2>\n
\/v4\/odds<\/code> call returns every market a fixture carries, both clocks included, from a catalogue of 350+ bookmakers. Historical snapshots come on the same key at no extra cost, which is what makes a played-fixture test cheap enough to run before you trust a resolver. WebSocket delivery and the native market structures, Asian handicaps and player props among them, sit behind the same API.<\/p>\nFAQ<\/h2>\n
What does the period field return for basketball?<\/h3>\n
result<\/code> is the final score including overtime, fulltime<\/code> is the 48-minute score, p1<\/code> to p4<\/code> are single quarters, p1+p2<\/code> is the first half, p3+p4<\/code> is the regulation second half and p3+p4+overtime<\/code> is the second half with overtime. p4+overtime<\/code> covers the fourth quarter with overtime. Six definitions, including Second Half Result, ship period: null<\/code>.<\/p>\nHow do I tell a regulation second-half total from an overtime one?<\/h3>\n
period<\/code> on \/v4\/markets<\/code>. p3+p4<\/code> settles on the third and fourth quarters alone; p3+p4+overtime<\/code> adds anything scored after 48 minutes. The market name carries the same information in the suffix (incl. overtime)<\/code>, but a name normaliser that strips parentheses will merge the two ladders, so branch on the enum.<\/p>\nDo the two second-half ladders use the same line numbers?<\/h3>\n
Which bookmakers quote which clock?<\/h3>\n
p3+p4<\/code> and 24 on p3+p4+overtime<\/code>. Pinnacle quoted 17 second-half and 27 fourth-quarter IDs and used the overtime clock for all of them. Measure it per fixture rather than caching a map.<\/p>\nCan I get a regulation second-half spread?<\/h3>\n
p3+p4+overtime<\/code> with 201 and 400 definitions. The fourth quarter follows the same pattern, with a three-way result and a two-way winner added on p4<\/code>.<\/p>\nHow do I check a settled fixture for free?<\/h3>\n
\/historical-odds<\/code> returns the snapshot history for a played fixture on the free tier, capped at three bookmaker slugs a call, and \/v4\/scores<\/code> returns each quarter as its own key. Together they let you replay a closing board and grade it on both clocks before you trust the resolver on a live game.<\/p>\n