Tennis Odds API: Live ATP & WTA Odds from 300+ Bookmakers
Why Tennis Is the Best Sport for Live Odds
Tennis is the sharpest live betting sport on the planet. Every point shifts the odds. Every break of serve creates a new market. A single tiebreak can flip a match — and the prices move in real time.
But most odds APIs treat tennis as an afterthought. 20 bookmakers, no sharp lines, no ITF coverage, and maybe a match winner market if you’re lucky. If you’re building a live tennis model, a scanner, or tracking line movements across books — you need more than that.
OddsPapi covers 110+ bookmakers per match, including Pinnacle, Singbet, and Betfair Exchange. That’s match winner, set betting, game totals (71 lines), game handicaps, tiebreak markets, and 159+ markets total — across 5,605 tournaments from ATP and WTA down to ITF Futures. All on a free tier.
Tennis Odds Coverage: OddsPapi vs The Competition
| Feature | The Odds API | SportsGameOdds | OddsPapi |
|---|---|---|---|
| Bookmakers per match | ~15-20 | ~30 | 110+ |
| Sharp books (Pinnacle, Singbet) | No | No | Yes |
| Betfair Exchange (order book) | No | No | Yes |
| Game totals lines | 1-2 | Some | 71 lines |
| Game handicap lines | Limited | Limited | 41 lines |
| Set betting markets | Limited | Some | Full (exact sets, set winner, handicap) |
| Tournaments | ~20 leagues | ~40 leagues | 5,605 tournaments |
| Live/in-play odds | Delayed | Limited | Real-time (REST + WebSocket) |
| Historical data | Paid add-on | No | Free tier |
| Free tier | 500 req/mo | Limited | 250 req/mo |
Why Tennis Is the Sharpest Live Betting Market
Team sports move in quarters and halves. Tennis moves point by point. Here’s why that matters for your model:
Break of serve = massive line swing. A single break can shift match winner odds by 30-50%. If you’re tracking this across 110 bookmakers, you’ll see which books react first and which lag behind. That’s where the edge is.
Momentum is measurable. Tennis momentum is real and quantifiable — a player winning 5 straight games creates predictable pricing patterns across bookmakers. Sharp books like Pinnacle adjust instantly. Soft books like Bet365 lag. That gap is your signal.
Year-round fixtures. Unlike NFL (September-February) or NBA (October-June), tennis runs 11 months a year. ATP, WTA, Challengers, ITF Futures — there are fixtures every single day. Your models never go cold.
279+ daily fixtures. On any given day, OddsPapi has 200-300+ tennis fixtures across all levels. That’s 200+ opportunities to test your live betting logic.
5,605 Tournaments: Every Level That Matters
OddsPapi covers 5,605 tennis tournaments — if a bookmaker prices it, we have it:
| Level | Examples | Coverage |
|---|---|---|
| Grand Slams | Wimbledon, US Open, Australian Open, Roland Garros | 110+ bookmakers |
| ATP Masters 1000 | Indian Wells, Miami, Paris, Madrid, Rome | 110+ bookmakers |
| ATP 500/250 | Dubai, Rotterdam, Basel, Houston, Acapulco | 100+ bookmakers |
| WTA 1000/500/250 | Charleston, Bogota, Monterrey | 100+ bookmakers |
| ATP Challengers | San Luis Potosi, Sao Leopoldo, Miyazaki | 50+ bookmakers |
| ITF / UTR | Monastir, Heraklion, Jackson, Nantes | 20+ bookmakers |
| Doubles | All levels (Grand Slam through Challengers) | 50+ bookmakers |
That’s not 20 “top leagues” — it’s every tournament that bookmakers actively price, from Wimbledon Centre Court to ITF Futures in Monastir. Singles and doubles.
Tennis Markets: 22 Market Types, 159+ Lines Per Match
Each tennis fixture on OddsPapi can have 159+ unique markets across 22 market types. Here are the key ones with market IDs — you’ll need these for API calls:
| Market | Market ID | Outcomes | Books |
|---|---|---|---|
| Match Winner | 121 | Player 1 (121), Player 2 (122) | 102+ |
| First Set Winner | 123 | Player 1 (123), Player 2 (124) | 69+ |
| Second Set Winner | 125 | Player 1 (125), Player 2 (126) | 59+ |
| Total Games Over/Under | 1229+ | Over (odd), Under (even) | 64+ per line |
| Game Handicap | 12179+ | Player 1 (odd), Player 2 (even) | 59+ per line |
| Set Handicap | 12239+ | Player 1 (odd), Player 2 (even) | 55+ per line |
| Total Sets Over/Under | 12231+ | Over, Under | 51+ |
| Total Games First Set | 12267+ | Over, Under | 54+ per line |
| Total Tiebreaks | 12251+ | Over, Under | 40+ |
| Exact Sets | 12877 | 2-0, 2-1 | 45+ |
| Correct Score | 12883 | Set-by-set scores | 30+ |
| Odd/Even Games | 12875 | Odd, Even | 35+ |
71 Total Games Lines — Not Just “Over/Under 20.5”
This is where most APIs fall short. OddsPapi gives you 71 different total games lines — from 15.5 through 35.5 and beyond. Each line is a separate market ID with its own outcome IDs. That means you can compare Pinnacle’s Over 22.5 line against Bet365’s Over 22.5 line directly, across 64+ bookmakers per line.
Same for game handicaps: 41 separate lines, each independently priced by 59+ bookmakers.
Python Tutorial: Tennis Odds in 5 Steps
Step 1: Setup
import requests
from datetime import datetime, timedelta
API_KEY = "YOUR_API_KEY" # Free at oddspapi.io
BASE_URL = "https://api.oddspapi.io/v4"
SPORT_ID = 12 # TennisStep 2: Browse Tournaments
def get_tournaments():
"""Get all tennis tournaments."""
response = requests.get(f"{BASE_URL}/tournaments", params={
"apiKey": API_KEY,
"sportId": SPORT_ID
})
tournaments = response.json()
print(f"{len(tournaments)} tournaments available")
return tournaments
tournaments = get_tournaments()
# Filter to Grand Slams and ATP/WTA
for t in tournaments:
name = t.get("tournamentName", "")
if any(s in name for s in ["Wimbledon", "US Open", "Australian Open", "ATP", "WTA"]):
live = t.get("liveFixtures", 0)
upcoming = t.get("upcomingFixtures", 0)
if live + upcoming > 0:
print(f" {name} (ID: {t['tournamentId']}) — {live} live, {upcoming} upcoming")Step 3: Get Today’s Fixtures (Including Live)
def get_fixtures():
"""Get today's tennis fixtures with odds."""
today = datetime.now().strftime("%Y-%m-%d")
tomorrow = (datetime.now() + timedelta(days=1)).strftime("%Y-%m-%d")
response = requests.get(f"{BASE_URL}/fixtures", params={
"apiKey": API_KEY,
"sportId": SPORT_ID,
"from": today,
"to": tomorrow
})
fixtures = response.json()
with_odds = [f for f in fixtures if f.get("hasOdds")]
live = [f for f in fixtures if f.get("statusId") == 3]
print(f"{len(fixtures)} fixtures today | {len(with_odds)} with odds | {len(live)} live")
return fixtures
fixtures = get_fixtures()
for f in fixtures[:10]:
status = "LIVE" if f.get("statusId") == 3 else "Pre-match"
print(f" [{status}] {f['participant1Name']} vs {f['participant2Name']} ({f['tournamentName']})")Step 4: Fetch Odds from 110+ Bookmakers
def get_odds(fixture_id):
"""Get odds from all bookmakers for a fixture."""
response = requests.get(f"{BASE_URL}/odds", params={
"apiKey": API_KEY,
"fixtureId": fixture_id
})
return response.json()
# Pick a fixture with odds
fixture = next(f for f in fixtures if f.get("hasOdds"))
odds = get_odds(fixture["fixtureId"])
bookmakers = list(odds.get("bookmakerOdds", {}).keys())
print(f"{len(bookmakers)} bookmakers pricing {fixture['participant1Name']} vs {fixture['participant2Name']}")Step 5: Compare Match Winner Odds Across Books
def compare_match_winner(odds_data):
"""Compare match winner odds (market 121) across all bookmakers.
Outcomes: 121 = Player 1, 122 = Player 2
"""
results = []
for slug, bookie in odds_data.get("bookmakerOdds", {}).items():
market = bookie.get("markets", {}).get("121")
if not market:
continue
p1 = market["outcomes"].get("121", {}).get("players", {}).get("0", {}).get("price")
p2 = market["outcomes"].get("122", {}).get("players", {}).get("0", {}).get("price")
if p1 and p2:
results.append({"bookmaker": slug, "player_1": p1, "player_2": p2})
results.sort(key=lambda x: x["player_1"], reverse=True)
print(f"\nMatch Winner from {len(results)} bookmakers:")
print(f"{'Bookmaker':<20} {'Player 1':>10} {'Player 2':>10}")
print("-" * 42)
for r in results[:15]:
print(f"{r['bookmaker']:<20} {r['player_1']:>10.3f} {r['player_2']:>10.3f}")
# Best prices
best_p1 = max(results, key=lambda x: x["player_1"])
best_p2 = max(results, key=lambda x: x["player_2"])
print(f"\nBest Player 1: {best_p1['player_1']} @ {best_p1['bookmaker']}")
print(f"Best Player 2: {best_p2['player_2']} @ {best_p2['bookmaker']}")
return results
compare_match_winner(odds)Live Odds Movement Tracker
This is where tennis gets interesting. Because odds move point-by-point, you can build a simple poller that detects line movements and steam moves across bookmakers in real time.
import time
def track_live_odds(fixture_id, market_id="121", interval=30, duration=300):
"""Track odds movement on a live tennis match.
Polls every `interval` seconds for `duration` seconds.
Detects when any bookmaker moves more than 5% between polls.
"""
history = {}
start = time.time()
print(f"Tracking market {market_id} every {interval}s for {duration}s...")
while time.time() - start < duration:
odds = get_odds(fixture_id)
timestamp = datetime.now().strftime("%H:%M:%S")
movements = []
for slug, bookie in odds.get("bookmakerOdds", {}).items():
market = bookie.get("markets", {}).get(market_id)
if not market:
continue
for outcome_id, outcome in market.get("outcomes", {}).items():
price = outcome.get("players", {}).get("0", {}).get("price")
if not price:
continue
key = f"{slug}_{outcome_id}"
if key in history:
old_price = history[key]
change_pct = abs(price - old_price) / old_price * 100
if change_pct > 5:
direction = "UP" if price > old_price else "DOWN"
movements.append({
"bookmaker": slug,
"outcome": outcome_id,
"old": old_price,
"new": price,
"change": f"{direction} {change_pct:.1f}%"
})
history[key] = price
if movements:
print(f"\n[{timestamp}] {len(movements)} movement(s) detected:")
for m in movements:
print(f" {m['bookmaker']} outcome {m['outcome']}: "
f"{m['old']:.3f} -> {m['new']:.3f} ({m['change']})")
else:
print(f"[{timestamp}] No significant movements")
time.sleep(interval)
# Usage: track a live fixture
live_fixtures = [f for f in fixtures if f.get("statusId") == 3 and f.get("hasOdds")]
if live_fixtures:
track_live_odds(live_fixtures[0]["fixtureId"])This is a starting point. In production, you’d store the history in a database, set alerts for specific thresholds, and compare movements between sharp and soft books to identify late-mover value.
Sharp vs Soft: Track Where the Line Originates
The real edge in live tennis isn’t just having the data — it’s knowing which book moves first. Pinnacle and Singbet are the benchmarks. When Pinnacle’s price shifts mid-match, the soft books follow — but not immediately.
def sharp_vs_soft_snapshot(odds_data, market_id="121"):
"""Compare sharp book prices vs soft book prices.
Sharps: Pinnacle, Singbet, SBOBet
Softs: Bet365, DraftKings, FanDuel, BetMGM
"""
sharps = ["pinnacle", "singbet", "sbobet"]
softs = ["bet365", "draftkings", "fanduel", "betmgm", "caesars"]
print(f"\n{'Book':<15} {'Type':<8} {'P1':>8} {'P2':>8}")
print("-" * 41)
for slug in sharps + softs:
bookie = odds_data.get("bookmakerOdds", {}).get(slug)
if not bookie:
continue
market = bookie.get("markets", {}).get(market_id)
if not market:
continue
p1 = market["outcomes"].get("121", {}).get("players", {}).get("0", {}).get("price", "N/A")
p2 = market["outcomes"].get("122", {}).get("players", {}).get("0", {}).get("price", "N/A")
book_type = "SHARP" if slug in sharps else "SOFT"
print(f"{slug:<15} {book_type:<8} {p1:>8} {p2:>8}")
sharp_vs_soft_snapshot(odds)When Pinnacle shows 1.89 and Bet365 still shows 1.61 on the same outcome — that’s a 17% discrepancy on the same match. During live play, these gaps open and close every few minutes. That’s why tennis is the best sport for live odds arbitrage and CLV tracking.
Grand Slams vs Regular Tour: Why It Matters for Totals
Men’s Grand Slams are best-of-5 sets. Everything else is best-of-3. This changes the total games markets completely:
| Format | Events | Typical Total Games | Over/Under Lines |
|---|---|---|---|
| Best-of-3 | ATP 250/500/1000, WTA all, Challengers | 18-26 games | Lines from 17.5 to 28.5 |
| Best-of-5 | Men’s Grand Slams only | 30-45 games | Lines from 28.5 to 48.5 |
OddsPapi handles this automatically — the total games lines adjust to the format. You’ll see 71 lines for a Grand Slam match (wider range) and fewer for a best-of-3. The market IDs are the same; the bookmaker handicap values change.
Free Historical Tennis Odds
OddsPapi includes historical odds data on the free tier. That means you can backtest your tennis models against real closing lines from Pinnacle and Betfair Exchange — without paying for a separate data subscription.
Use cases for historical tennis data:
- CLV analysis — did your bet close at a better or worse price than you got?
- Surface-based modeling — compare odds accuracy across clay, grass, and hard court seasons
- Serve-dominant vs rally players — backtest totals models against player archetypes
- Tournament-tier calibration — Challenger pricing behaves differently than ATP 1000 pricing
Frequently Asked Questions
Is there a free tennis odds API?
Yes. OddsPapi’s free tier gives you 250 requests/month with access to all 5,605 tennis tournaments, 110+ bookmakers, and historical data. No credit card required.
Can I get live tennis odds via API?
Yes. OddsPapi provides live/in-play tennis odds via REST polling on all tiers. WebSocket streaming is available on Pro plans for sub-second updates. The REST API shows current prices for all live fixtures with statusId: 3.
What tennis tournaments does OddsPapi cover?
5,605 tournaments: all four Grand Slams (Wimbledon, US Open, Australian Open, Roland Garros), ATP Masters 1000, ATP 500/250, WTA 1000/500/250, ATP Challengers, ITF Futures, UTR events, and all doubles draws.
Does OddsPapi have Pinnacle tennis odds?
Yes. Pinnacle is fully integrated with 41 markets per tennis match — match winner, set winners, total games (all lines), game handicaps, and more. Singbet and Betfair Exchange are also available.
What’s the best API for in-play tennis betting?
OddsPapi is built for it. 110+ bookmakers with live odds, sharp books that react point-by-point, and Betfair Exchange order book depth. Compare that to APIs with 15-20 soft bookmakers and delayed pricing.
How do I get Betfair Exchange tennis data via API?
Through OddsPapi. Betfair Exchange odds include full order book depth — back/lay prices with available sizes at each level. Market 121 (match winner) alone has 70 markets available on Betfair Exchange for major fixtures.
Stop Scraping. Start Building.
Tennis odds from 110+ bookmakers, 5,605 tournaments, and 159+ markets per match. Pinnacle, Singbet, and Betfair Exchange included. Historical data on the free tier.
Get your free API key and start tracking live tennis odds in under 5 minutes.