MLB Scraper

Scrape MLB teams, rosters, schedules, scores, standings, statistics, game totals, and leaders from public data. Export MLB data as flat JSON, CSV, or spreadsheet rows for research, reporting, and applications that need an MLB data API alternative without maintaining seven separate collectors.

What data can you extract from MLB?

Mode	One row represents	Useful fields
teams	One club in one season	Team ID, name, abbreviation, league, division, venue, first year of play
players	One player on a club roster	Player ID, jersey, position, roster status, birth details, height, weight, batting and throwing side, debut date
schedule	One game	Start time, official date, status, clubs, scores, winner, venue, series and doubleheader details
standings	One club's season record	Wins, losses, winning percentage, ranks, games back, runs scored and allowed, streak, clinch details
playerStats	One player season statistic split	Player and team IDs, season, group, games played, hitting, pitching, or fielding measures
gameDetails	One club in one game	Batting totals, pitching totals, fielding totals, opponent and game identifiers
leaders	One ranked player in one category	Statistic category, rank, value, player, club, league

Output field reference

The table covers every field that may be emitted. Fields appear only in relevant modes. Season stat columns are taken from the selected group, so a hitting row and a pitching row have different measures. A missing field means that the source did not provide that measure for the row; a null value means the field belongs to the row but is unavailable at that point, such as a score before first pitch.

Field	Description	Example
abbreviation	Abbreviation	—
active	Active	—
age	Age	—
airOuts	Air outs	—
assists	Assists	—
atBats	At bats	—
atBatsPerHomeRun	At bats per home run	—
avg	Avg	—
awayLosses	Away losses	—
awayScore	Away score	4
awayTeam	Away team	Chicago Cubs
awayTeamId	Away team id	—
awayWins	Away wins	—
babip	Babip	—
balks	Balks	—
baseOnBalls	Base on balls	—
bats	Batting side code	—
battersFaced	Batters faced	—
birthCity	Birth city	—
birthCountry	Birth country	—
birthDate	Birth date	—
birthStateProvince	Birth state province	—
blownSaves	Blown saves	—
catcherERA	Earned run average while catching	—
catchersInterference	Catchers interference	—
category	Leaderboard statistic category	homeRuns
caughtStealing	Caught stealing	—
caughtStealingPercentage	Caught stealing percentage	—
chances	Chances	—
clinched	Clinched	—
completeGames	Complete games	—
dayNight	Day night	—
division	Division	—
divisionId	Division id	—
divisionRank	Division rank	—
doubleHeader	Doubleheader code	—
doublePlays	Double plays	—
doubles	Doubles	—
earnedRuns	Earned runs	—
eliminationNumber	Elimination number as displayed	—
era	Era	—
errors	Errors	—
fielding	Fielding	—
firstYearOfPlay	First year of play	—
gameDate	Scheduled game start in UTC	—
gameNumber	Game number	—
gamePk	Official game identifier	776318
gameType	Game type	—
games	Games	—
gamesBack	Games behind leader as displayed	—
gamesFinished	Games finished	—
gamesPitched	Games pitched	—
gamesPlayed	Games played	—
gamesStarted	Games started	—
groundIntoDoublePlay	Ground into double play	—
groundOuts	Ground outs	—
groundOutsToAirouts	Ground outs to airouts	—
height	Height	—
hitBatsmen	Hit batsmen	—
hitByPitch	Hit by pitch	—
hits	Hits	—
hitsPer9Inn	Hits per9inn	—
holds	Holds	—
homeLosses	Home losses	—
homeRuns	Home runs	55
homeRunsPer9	Home runs per9	—
homeScore	Home score	0
homeTeam	Home team	Pittsburgh Pirates
homeTeamId	Home team id	—
homeWins	Home wins	—
inheritedRunners	Inherited runners	—
inheritedRunnersScored	Inherited runners scored	—
innings	Innings	—
inningsPitched	Innings pitched	—
intentionalWalks	Intentional walks	—
jerseyNumber	Jersey number	—
league	League	—
leagueId	League id	—
leagueRank	League rank	—
leftOnBase	Left on base	—
locationName	Location name	—
losses	Losses	68
magicNumber	Division clinch magic number as displayed	—
mlbDebutDate	First major league game date	—
numberOfPitches	Number of pitches	—
obp	Obp	—
officialDate	Local official game date	2025-09-15
opponent	Opponent	—
opponentId	Opponent id	—
ops	Ops	—
outs	Outs	—
passedBall	Passed balls	—
pickoffs	Pickoffs	—
pitchesPerInning	Pitches per inning	—
pitchingBaseOnBalls	Pitching base on balls	—
pitchingHits	Pitching hits	—
pitchingInnings	Innings pitched by the club in this game	—
pitchingRuns	Pitching runs	—
pitchingStrikeOuts	Pitching strike outs	—
plateAppearances	Plate appearances	—
player	Player full name	—
playerId	Player id	660271
position	Position	—
positionAbbreviation	Position abbreviation	—
putOuts	Put outs	—
rangeFactorPer9Inn	Range factor per9inn	—
rangeFactorPerGame	Range factor per game	—
rank	Rank including ties	1
rbi	Rbi	—
recordType	Type of output record	game
rosterStatus	Roster status	—
runDifferential	Run differential	—
runs	Runs	—
runsAllowed	Runs allowed	—
runsScored	Runs scored	—
runsScoredPer9	Runs scored per9	—
sacBunts	Sac bunts	—
sacFlies	Sac flies	—
saveOpportunities	Save opportunities	—
saves	Saves	—
season	Season year	2025
seriesDescription	Series description	—
seriesGameNumber	Series game number	—
shutouts	Shutouts	—
slg	Slg	—
statGroup	Hitting, pitching, or fielding group	hitting
status	Status	Final
stolenBasePercentage	Stolen base percentage	—
stolenBases	Stolen bases	—
streak	Streak	—
strikeOuts	Strike outs	—
strikePercentage	Strike percentage	—
strikeoutWalkRatio	Strikeout walk ratio	—
strikeoutsPer9Inn	Strikeouts per9inn	—
strikes	Strikes	—
team	Club name	—
teamId	Team id	112
teamName	Team name	—
teamSide	Home or away side	—
throwingErrors	Throwing errors	—
throws	Throwing hand code	—
totalBases	Total bases	—
triplePlays	Triple plays	—
triples	Triples	—
url	Public site page for this record	—
value	Leaderboard value as displayed by the source	60
venueId	Venue id	—
venueName	Venue name	—
walksPer9Inn	Walks per9inn	—
weight	Weight	—
whip	Whip	—
wildCardGamesBack	Wild card games back	—
wildPitches	Wild pitches	—
winPercentage	Win percentage	—
winningPercentage	Season win percentage as displayed	—
winningTeam	Winner once final	—
wins	Wins	94

How to scrape MLB

1. Choose a dataset with mode. Start with teams if you need club IDs, players if you need player IDs, or schedule if you need game IDs.
2. Select one or more seasons. For schedules and game details, optionally add a date, start date, end date, game type, or selected game IDs. A date range is the clearest way to keep a large schedule run focused.
3. Add filters only when needed. Club IDs narrow clubs, rosters, games, standings, and leaders. Player IDs restrict player stats. A leaderboard category names the statistic to rank.
4. Set maxItems to the largest number of rows you want returned. Run the scraper and export the dataset as JSON, CSV, or a spreadsheet file.

Input

Name	Type	Default	Description
mode	string	teams	Selects one of the seven datasets.
seasons	string array	current year	One or more season years; rows keep their season label.
season	integer	unset	Single season shortcut, merged with seasons.
teamIds	string array	all clubs	Restricts clubs or matching games to these official IDs.
teamId	integer	unset	Single club ID shortcut, merged with teamIds.
playerIds	string array	roster players	In player stats mode, fetches these people directly.
playerId	integer	unset	Single player ID shortcut, merged with playerIds.
gamePks	string array	games from schedule	In game details mode, fetches these games directly.
gamePk	integer	unset	Single game ID shortcut, merged with gamePks.
date	string	unset	One local official date for schedule or game details.
fromDate	string	unset	Beginning of a schedule or game-details date range.
toDate	string	unset	End of a schedule or game-details date range.
leagueId	string	both	Standings for both leagues, AL, or NL.
statGroup	string	hitting	Hitting, pitching, or fielding in player stats and leaders.
gameType	string	R	Regular season or another supported game classification.
leaderCategories	string array	homeRuns	Categories to rank in leaders mode.
maxItems	integer	1000	Hard cap on emitted dataset rows.

A date overrides a date range. When a date, date range, or explicit game ID is supplied in a game mode, the request is evaluated once rather than repeated for every season in seasons. All dates use YYYY-MM-DD. The gameDate value is an ISO timestamp in UTC, while officialDate is the date assigned to the game by the league; those can differ across time zones.

This example collects final scores and game details for a small, reproducible window:

{
  "mode": "schedule",
  "seasons": ["2025"],
  "fromDate": "2025-09-15",
  "toDate": "2025-09-17",
  "gameType": "R",
  "maxItems": 50
}

Output example

This is a real game row from the 2025-09-15 to 2025-09-17 validation run, which returned 40 rows:

{
  "recordType": "game",
  "season": 2025,
  "gamePk": 776318,
  "gameDate": "2025-09-15T22:40:00Z",
  "officialDate": "2025-09-15",
  "gameType": "R",
  "status": "Final",
  "awayTeamId": 112,
  "awayTeam": "Chicago Cubs",
  "awayScore": 4,
  "awayWins": 86,
  "awayLosses": 64,
  "homeTeamId": 134,
  "homeTeam": "Pittsburgh Pirates",
  "homeScore": 0,
  "homeWins": 65,
  "homeLosses": 86,
  "winningTeam": "Chicago Cubs",
  "venueId": 31,
  "venueName": "PNC Park",
  "dayNight": "night",
  "doubleHeader": "N",
  "gameNumber": 1,
  "seriesGameNumber": 1,
  "seriesDescription": "Regular Season",
  "url": "https://www.mlb.com/gameday/776318"
}

Use cases

• Sports reporting: Refresh yesterday's scores, build a game recap queue, or compare division races without manually transcribing tables.
• Fantasy baseball analysis: Join player season lines to roster records and leader categories. Limit by club or specific player IDs when monitoring a shortlist.
• Historical research: Collect the same statistic across several seasons, then compare seasons using the explicit season column rather than inferring a year from file names.
• Schedule applications: Populate game lists with UTC start times and official dates, then update scores and statuses during a season.

How much does it cost to scrape MLB?

Price: $3.20 per 1,000 returned rows ($0.0032 each). A 30-club teams run is about $0.096. A 1,000-row roster or schedule export is $3.20. A 2,430-game regular-season schedule would be about $7.78 if all rows are returned. These examples count emitted records, not source requests; a two-row game-details result costs two result events. Your maxItems setting prevents a larger dataset than intended.

Tips for best results

Choose the smallest useful scope first. A three-day schedule window is easy to inspect, while a full season can include thousands of games. For daily score refreshes, pass a single date; for backfills, pass fromDate and toDate. The scraper splits ranges into calendar-month requests, which keeps source responses manageable. It stops once maxItems or the run's result budget is reached.

For leaderboards, choose a category appropriate to the selected statGroup. A hitting category such as homeRuns belongs with hitting; a pitching category such as saves belongs with pitching. A request for a category the source does not return may yield zero rows. If you need more than the first page, raise maxItems; the scraper uses offsets and removes overlaps caused by tied ranks.

Limits

The scraper reads public data. It cannot fill facts that have not been published: scores before or during a game, missing historical splits, unavailable roster biographies, or empty stat categories. Season coverage varies by mode and statistic. Very early seasons may have fewer fields than recent ones. Current season data can change as games progress and corrections are made.

Game details fetch a box score per game and run slower than schedules. The default 1,000-row cap can truncate league-wide rosters or season schedules.

Use with automated workflows

Example instruction: “Collect the 2025 regular-season schedule for September 15 through 17, return game IDs, official dates, clubs, final scores, and winners, then sort by official date.”

Example instruction: “Collect 2025 hitting season lines for one selected club, keep player ID, player name, games played, hits, home runs, and on-base percentage, and flag rows where a measure is missing.”

FAQ

Is the data public? The scraper uses public endpoints and does not require an account. Follow the site's terms and applicable law when storing or redistributing data. Avoid using player biographical details for unrelated personal profiling.

Do I need to supply a proxy or credentials? No input credential is needed. The scraper uses its standard network path and does not require a user-provided proxy setting.

How fast is a run? Teams and standings need few source requests. Rosters and player stats require club requests; game details require one box-score request per game. Run time also depends on the row count and source responsiveness.

Can I schedule recurring collections? Yes. Reuse a saved input with a changing date or season, and monitor the resulting dataset and run status. Stable IDs make it possible to update earlier records in your own store.

Can I export to a spreadsheet? Yes. The rows are flat and can be downloaded as CSV or a spreadsheet-compatible file. A separate export per mode is easiest to analyze because each mode has different columns.

Why is a score or statistic empty? A scheduled game has no final score. Some statistics do not apply to every player or season. Check the row's status, statGroup, position, and season before interpreting an empty value.

What happens with tied leaderboard ranks? The source can return more rows than a requested page size when several players share a rank. The scraper deduplicates by player within a category while continuing through offsets until the result cap is met.

Integrations

The run input and dataset can be accessed programmatically, sent to a webhook after completion, used in scheduled jobs, or exported as CSV for spreadsheet analysis. For ongoing pipelines, store gamePk, playerId, or teamId with season so the next run can update matching records instead of relying on team or player names.

Support

Open an issue on the Issues tab; we reply within 24 hours and add fields on request. Include the mode, input, season, and a sample identifier so a missing value can be checked against the public source.