sbr-odds-scraper 0.1.8

A web scraper that collects historical MLB, EPL, and MLS betting odds from SportsBookReview

SBR Odds Scraper

A web scraper that collects historical MLB, EPL, and MLS betting odds from SportsBookReview.

Based on Arnav Saraogi's mlb-odds-scraper.

Installation

pip install sbr-odds-scraper

Python API

import sbr_odds_scraper as sbr

# Single day - returns pandas DataFrame
df = sbr.scrape("2024-10-01")

# Date range
df = sbr.scrape("2024-10-01", "2024-10-05")

# Specific odds types (moneyline, pointspread, totals)
df = sbr.scrape("2024-10-01", odds_types=["moneyline"])

# Specific sportsbooks
df = sbr.scrape("2024-10-01", sportsbooks=["fanduel", "draftkings"])

# EPL soccer odds (default soccer league)
df = sbr.scrape("2024-10-05", sport="soccer")

# MLS soccer odds
df = sbr.scrape("2024-10-02", league="mls")

# Combine filters
df = sbr.scrape("2024-10-01", odds_types=["moneyline"], sportsbooks=["fanduel"])

# Faster scraping (may trigger rate limits)
df = sbr.scrape("2024-10-01", fast=True)

# Raw dict instead of DataFrame
data = sbr.scrape_raw("2024-10-01")

DataFrame Columns

Column	Description
game_id	MLB gamePk, EPL fixture ID, or MLS match_id
date	Game date
start_time	Game start time (ISO format)
away_team, home_team	Team full names
away_score, home_score	Final scores
venue	Stadium name
game_type	R=Regular, F=Wild Card, D=Division, L=League, W=World Series
sportsbook	Sportsbook name (fanduel, draftkings, betmgm, etc.)
odds_type	moneyline, pointspread, or totals
opening_*, current_*	Opening and current line values

CLI Usage

sbr-odds-scraper 2024-10-01 2024-10-05 -t moneyline pointspread -o odds.json
sbr-odds-scraper 2024-10-05 2024-10-05 --sport soccer -t moneyline
sbr-odds-scraper 2024-10-02 2024-10-02 --league mls -t moneyline

Flag	Description
-t, --types	Odds types: moneyline, pointspread, totals (default: moneyline)
-s, --sport	Sport: mlb, soccer, epl, or mls (default: mlb; soccer defaults to EPL)
-l, --league	Soccer league: epl or mls
-c, --concurrent	Concurrent requests (default: 5)
-f, --fast	Faster scraping (reduced delays)
-o, --output	Output filename (default: mlb_odds.json)

JSON Structure

The raw data is organized by date. Each date contains a list of games with sportsbook odds:

{
  "2021-04-01": [
    {
      "gameView": {
        "startDate": "2021-04-01T17:05:00+00:00",
        "awayTeam": {
          "fullName": "Toronto Blue Jays",
          "shortName": "TOR"
        },
        "awayTeamScore": 3,
        "homeTeam": {
          "fullName": "New York Yankees",
          "shortName": "NYY"
        },
        "homeTeamScore": 2,
        "gameStatusText": "Final (10)",
        "venueName": "Yankee Stadium",
        "gameType": "R"
      },
      "odds": {
        "moneyline": [
          {
            "sportsbook": "fanduel",
            "openingLine": { "homeOdds": -188, "awayOdds": 155 },
            "currentLine": { "homeOdds": -200, "awayOdds": 168 }
          },
          {
            "sportsbook": "draftkings",
            "openingLine": { "homeOdds": -175, "awayOdds": 148 },
            "currentLine": { "homeOdds": -195, "awayOdds": 165 }
          }
        ],
        "pointspread": [
          {
            "sportsbook": "fanduel",
            "openingLine": { "homeOdds": 122, "awayOdds": -144, "homeSpread": -1.5, "awaySpread": 1.5 },
            "currentLine": { "homeOdds": 100, "awayOdds": -120, "homeSpread": -1.5, "awaySpread": 1.5 }
          }
        ],
        "totals": [
          {
            "sportsbook": "fanduel",
            "openingLine": { "overOdds": -106, "underOdds": -114, "total": 8 },
            "currentLine": { "overOdds": -122, "underOdds": 100, "total": 7.5 }
          }
        ]
      }
    }
  ]
}

Notes

• Historical data available from ~2019-05-03 onwards
• Use fast=True / -f sparingly to avoid rate limiting
• Game types: R=Regular, S=Spring, E=Exhibition, A=All-Star, D=Division, F=Wild Card, L=League Championship, W=World Series

Credits

Original scraper by Arnav Saraogi.

Disclaimer

For educational purposes only. Review SportsBookReview's Terms of Service before use.