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MLB Weather and Ballpark Run Environment Dataset for Total Research

Question this dataset helps answer: Which MLB weather and ballpark contexts historically align with higher or lower run environments before building totals, DFS, or fantasy research workflows?

This dataset helps totals researchers, fantasy baseball analysts, and sportsbook-market researchers compare MLB run environments using first-pitch weather, ballpark dimensions, roof context, field-oriented wind components, local start time, and rolling team scoring context.

Use the public sample to check:

Which parks, roof types, and weather-station matches are represented in the preview
Which columns are pregame weather or rolling-context features versus postgame scoring outcomes
Which temperature, wind, and run-environment combinations appear in the sample before buying the full file

Preview vs full dataset:

Preview: 1200 rows and 84 columns
Full: 24005 rows and 84 columns

Full dataset: https://thearticulated.gumroad.com/l/ubegdh

This product is built around a recurring workflow problem that sits between sports betting research, fantasy baseball, and dashboard analysis. Daily MLB weather pages are widely used, but most of them are ephemeral. They help with today's slate, not with historical comparisons across seasons, parks, roof types, wind directions, and scoring environments. Buyers who want to answer questions about totals or run context usually have to rebuild the same stack from scratch: MLB schedules, venue metadata, roof status, local start times, weather observations, and team trend features. This dataset packages that structure directly into a single reproducible table.

Each row represents one completed MLB regular-season game. The coverage runs from April 3, 2016 through June 10, 2026 and includes 24005 game rows across 84 columns. That row count matters. It is large enough for filtering by team, park, month, roof type, first-pitch weather regime, and rolling team form while still retaining meaningful sample sizes. Buyers can use the file for historical dashboards, weather segmentation, park-level comparisons, or time-aware modeling without first spending hours rebuilding raw sources.

The pregame side of the table is built around the weather-and-context problem that buyers already care about. Key feature groups include venue identity, park dimensions, roof type, local start hour, nearest-station weather provenance, first-pitch temperature, humidity, precipitation, wind speed, wind gusts, wind direction, field-oriented wind-out and crosswind components, barometric pressure, cloud cover, team rest gaps, and rolling team offense or defense features. That combination is the unique angle. A generic baseball game log might show only teams and scores. This file adds the context buyers actually search for when they want to compare run environments across parks and weather setups.

The ballpark orientation piece makes the dataset more useful than a raw weather merge. Instead of stopping at wind direction alone, the build converts the weather-station wind reading into a park-aware component that estimates whether the wind was blowing out toward center field or across the field. That gives buyers a better research surface for questions like whether warm temperatures with outward wind at specific parks line up with higher scoring environments more often than cooler or inward-wind setups. It also makes the sample easier to understand because the park-and-wind relationship is explicit in the schema rather than hidden in a manual notebook transformation.

Rolling team features help separate short-term form from environment. The dataset includes pregame rolling averages for runs scored, runs allowed, total runs, hits, and win rate, plus season-to-date runs scored and allowed averages for both home and away teams. Those fields make the dataset useful beyond weather-only filtering. A buyer can study whether a high-scoring outcome came from a hot offense entering a favorable weather window, a struggling pitching environment, or a combination of both. That is closer to the real workflow than simply sorting games by temperature.

The postgame side of the table stores the actual results. Those result columns include home and away score, total runs, run differential, hits, errors, and home-team win outcome. That separation matters. It keeps the pre-event columns usable as responsible research features while preserving the actual game outcome as a target for comparison. The schema therefore supports both descriptive dashboard work and exploratory modeling workflows that need a clean line between information available before first pitch and information only known after the game ended.

Weather coverage is intentionally transparent rather than overstated. Hourly weather is matched through the nearest public station, and the dataset includes weather station identifiers, names, and approximate distance from the venue. That provenance matters when a buyer wants to assess the credibility of a historical weather match at a retractable roof park, a downtown stadium, or an international venue. Some rows may have missing weather because the nearest public station did not provide a clean hourly match at the exact rounded first-pitch time, but the row still retains useful park and team context. That is a better tradeoff than filling historical gaps with invented values.

Responsible use note

This dataset is for research, analysis, dashboard building, educational use, and exploratory modeling. It does not provide betting advice, picks, guarantees, or predictions of future outcomes. It should not be marketed as a shortcut to guaranteed profit, and it should not be interpreted as proof that any single schedule angle automatically creates an edge.

Modeling notes

Each row represents one completed MLB regular-season game.
Pregame features include park geometry, roof type, local start hour, nearest-station hourly weather, rest gaps, and rolling team scoring context.
Postgame outcomes include runs, hits, errors, run differential, and home-team win result.
The coverage window runs from April 3, 2016 through June 10, 2026.
The full dataset contains 24005 rows, which is large enough for train-test splits by season, by month, by park, or by pregame weather regime.
A sensible modeling workflow would split by season or by date rather than shuffling randomly, because the product is time-ordered and season context changes.
Weather is station-based rather than stadium-sensor-based, so buyers should treat the station-distance fields as part of data-quality assessment.
Retractable-roof and dome parks remain useful analytical rows because the roof-type fields are explicit and filterable.
The dataset is descriptive infrastructure, not a finished predictive system.

Why the free sample matters

The public sample is not filler. It proves that the buyer task is real. A buyer can open the sample and immediately verify that the file contains first-pitch weather fields, park geometry, roof metadata, station provenance, rolling offense and defense context, and clear result columns. They can see whether the product answers the practical question they already have: how weather and ballpark context line up with historical scoring environments. That is exactly what a public discovery asset should do.

Source and build notes

The build uses public MLB Stats API schedule and venue metadata plus public Meteostat station data, then engineers park-aware wind components and rolling team run-environment features locally. The process is reproducible, versionable, and does not depend on a private odds feed. The output is a single analysis-ready table rather than a loose collection of raw weather and schedule files that still need substantial cleaning and joins.

Dataset Preview

record_id	game_pk	season	official_date	game_datetime_utc	game_month	game_weekday	game_local_start_hour	day_night	scheduled_innings	doubleheader_flag	games_in_series	series_game_number	series_description	venue_id	venue_name	venue_city	venue_state	venue_country	venue_timezone	venue_elevation_feet	field_azimuth_to_center_deg	roof_type	turf_type	left_line_feet	left_center_feet	center_field_feet	right_center_feet	right_line_feet	is_dome	is_retractable_roof	is_open_air	home_team_id	home_team_name	away_team_id	away_team_name	weather_station_id	weather_station_name	weather_station_distance_m	temperature_f	relative_humidity_pct	precipitation_mm	wind_speed_mph	wind_direction_from_deg	wind_out_to_center_mph	crosswind_mph	barometric_pressure_hpa	cloud_cover_pct	home_score	away_score	total_runs	run_differential	home_team_won	home_hits	away_hits	total_hits	home_errors	away_errors	total_errors	source_url	source_domain	last_collected_at
446877	446877	2016	2016-04-03 00:00:00	2016-04-03 17:05:00	4	Sunday	13	day	9	False	3	1	Regular Season	31	PNC Park	Pittsburgh	PA	USA	America/New_York	780	116	Open	Grass	325	410	399	375	320	False	False	True	134	Pittsburgh Pirates	138	St. Louis Cardinals	72520	Greater Pittsburgh International	6554.6	35.06	42	0.0	13.857	270.0	12.454	-6.074	1018.5		4	1	5	3	True	9	5	14	1	0	1	https://statsapi.mlb.com/api/v1.1/game/446877/feed/live	statsapi.mlb.com, meteostat.net	2026-06-11 19:41:03
446911	446911	2016	2016-04-03 00:00:00	2016-04-03 20:05:00	4	Sunday	16	day	9	False	4	1	Regular Season	12	Tropicana Field	St. Petersburg	FL	USA	America/New_York	15	359	Dome	Artificial Turf	315	410	404	404	322	True	False	False	139	Tampa Bay Rays	141	Toronto Blue Jays	KSPG0	Saint Petersburg	2526.6	71.96	33	0.0	6.959	120.0	3.584	-5.965	1017.2	0.0	3	5	8	-2	False	7	7	14	1	2	3	https://statsapi.mlb.com/api/v1.1/game/446911/feed/live	statsapi.mlb.com, meteostat.net	2026-06-11 19:41:03
446873	446873	2016	2016-04-03 00:00:00	2016-04-04 00:37:00	4	Sunday	19	night	9	False	2	1	Regular Season	7	Kauffman Stadium	Kansas City	MO	USA	America/Chicago	856	46	Open	Grass	330	385	410	385	330	False	False	True	118	Kansas City Royals	121	New York Mets	KMKC0	Kansas City / Harlem	12546.5	75.02	18	0.0	12.738	210.0	12.245	-3.511	1008.2	0.0	4	3	7	1	True	9	7	16	0	1	1	https://statsapi.mlb.com/api/v1.1/game/446873/feed/live	statsapi.mlb.com, meteostat.net	2026-06-11 19:41:03
446875	446875	2016	2016-04-04 00:00:00	2016-04-04 18:10:00	4	Monday	13	day	9	False	3	1	Regular Season	32	Miller Park	Milwaukee	WI	USA	America/Chicago	597	129	Retractable	Grass	344	371	400	374	345	False	True	False	158	Milwaukee Brewers	137	San Francisco Giants	72640	Gen Mitchell International Airport	9793.4	33.98	56		17.212	20.0	5.604	16.274	1023.8	6.0	3	12	15	-9	False	8	15	23	1	0	1	https://statsapi.mlb.com/api/v1.1/game/446875/feed/live	statsapi.mlb.com, meteostat.net	2026-06-11 19:41:03
446872	446872	2016	2016-04-04 00:00:00	2016-04-04 19:05:00	4	Monday	15	day	9	False	3	1	Regular Season	2	Oriole Park at Camden Yards	Baltimore	MD	USA	America/New_York	33	31	Open	Grass	333	410	400	373	318	False	False	True	110	Baltimore Orioles	142	Minnesota Twins	KDMH0	Baltimore	432.8	71.06	26	0.0					1007.2		3	2	5	1	True	10	7	17	0	0	0	https://statsapi.mlb.com/api/v1.1/game/446872/feed/live	statsapi.mlb.com, meteostat.net	2026-06-11 19:41:03

Access Requirements (Paid Dataset)

This dataset is behind manual gated access.

To obtain access:

Full dataset access:
https://thearticulated.gumroad.com/l/ubegdh
Provide your Hugging Face username at checkout.
Return to this Hugging Face page and click:
"Request Access"
Your access will be approved within 1-12 hours.

Once approved, you can use the Python snippet at the bottom of this README to load the dataset.

Dataset Structure

Total rows: 24,005

Total columns: 84

Splits

data: 24,005 rows

Data Files

data: data/data.parquet

Data Dictionary

The table below describes the columns included in this dataset.

column	pandas_dtype	dataset_type	description
record_id	str	integer-like string	Stored as text, but values appear to represent whole numbers. Stable unique identifier for one completed MLB game row.
game_pk	str	integer-like string	Stored as text, but values appear to represent whole numbers. MLB Stats API game identifier stored as text.
season	Int64	integer	Whole-number numeric column. MLB season year attached to the regular-season game.
official_date	datetime64[us]	datetime	Date or timestamp column. Official calendar date of the game.
game_datetime_utc	datetime64[us]	datetime	Date or timestamp column. Scheduled game start time in UTC.
game_month	Int64	integer	Whole-number numeric column. Calendar month of the game date.
game_weekday	str	string	Text column. Weekday label for the official game date.
game_local_start_hour	Int64	integer	Whole-number numeric column. Local scheduled start hour at the venue timezone.
day_night	str	string	Text column. Source label for day or night start context.
scheduled_innings	Int64	integer	Whole-number numeric column. Scheduled innings count from the game metadata.
doubleheader_flag	bool	boolean	True/false column. Boolean flag showing whether the game was part of a doubleheader sequence.
games_in_series	Int64	integer	Whole-number numeric column. Number of games in the series when provided by the source.
series_game_number	Int64	integer	Whole-number numeric column. Sequence number of the game within its series when provided by the source.
series_description	str	string	Text column. Series descriptor such as regular season or opening series.
venue_id	Int64	integer	Whole-number numeric column. Venue identifier from the public MLB source.
venue_name	str	string	Text column. Venue name for the game.
venue_city	str	string	Text column. Venue city from the public source.
venue_state	str	string	Text column. Venue state or province abbreviation when available.
venue_country	str	string	Text column. Venue country from the public source.
venue_timezone	str	string	Text column. IANA timezone name for the venue.
venue_elevation_feet	float64	float	Decimal numeric column. Venue elevation from the public source metadata, generally reported in feet.
field_azimuth_to_center_deg	float64	float	Decimal numeric column. Field azimuth angle toward center field used to derive wind-out and crosswind components.
roof_type	str	string	Text column. Roof type from venue metadata, such as Open, Dome, or Retractable.
turf_type	str	string	Text column. Playing surface or turf type from venue metadata.
left_line_feet	Int64	integer	Whole-number numeric column. Listed distance down the left-field line.
left_center_feet	Int64	integer	Whole-number numeric column. Listed distance to left-center field.
center_field_feet	Int64	integer	Whole-number numeric column. Listed distance to straightaway center field.
right_center_feet	Int64	integer	Whole-number numeric column. Listed distance to right-center field.
right_line_feet	Int64	integer	Whole-number numeric column. Listed distance down the right-field line.
is_dome	bool	boolean	True/false column. Boolean flag for dome roof types.
is_retractable_roof	bool	boolean	True/false column. Boolean flag for retractable-roof venues.
is_open_air	bool	boolean	True/false column. Boolean flag for open-air venues where outside weather is more directly relevant.
home_team_id	Int64	integer	Whole-number numeric column. Home team identifier from the MLB source.
home_team_abbreviation	str	string	Text column. Home team abbreviation.
home_team_name	str	string	Text column. Home team full display name.
away_team_id	Int64	integer	Whole-number numeric column. Away team identifier from the MLB source.
away_team_abbreviation	str	string	Text column. Away team abbreviation.
away_team_name	str	string	Text column. Away team full display name.
weather_station_id	str	string	Text column. Nearest Meteostat station identifier used to source hourly weather for the venue.
weather_station_name	str	string	Text column. Nearest Meteostat station name used for the weather match.
weather_station_distance_m	float64	float	Decimal numeric column. Approximate straight-line distance in meters from the venue to the matched weather station.
temperature_f	float64	float	Decimal numeric column. Archived hourly air temperature near first pitch converted to degrees Fahrenheit.
relative_humidity_pct	float64	float	Decimal numeric column. Archived hourly relative humidity percentage near first pitch.
precipitation_mm	float64	float	Decimal numeric column. Archived hourly precipitation amount near first pitch in millimeters.
wind_speed_mph	float64	float	Decimal numeric column. Archived hourly wind speed near first pitch converted to miles per hour.
wind_gust_mph	float64	float	Decimal numeric column. Archived hourly peak wind gust near first pitch converted to miles per hour when available.
wind_direction_from_deg	float64	float	Decimal numeric column. Archived hourly meteorological wind direction in degrees, representing where the wind came from.
wind_out_to_center_mph	float64	float	Decimal numeric column. Derived wind component in miles per hour toward center field. Positive values imply wind blowing out, negative values imply wind blowing in.
crosswind_mph	float64	float	Decimal numeric column. Derived cross-field wind component in miles per hour based on venue orientation.
barometric_pressure_hpa	float64	float	Decimal numeric column. Archived hourly mean sea level pressure near first pitch in hectopascals.
cloud_cover_pct	float64	float	Decimal numeric column. Archived hourly cloud-cover percentage near first pitch when available.
home_prior_games_played	Int64	integer	Whole-number numeric column. Number of prior completed games for the home team before this game.
away_prior_games_played	Int64	integer	Whole-number numeric column. Number of prior completed games for the away team before this game.
home_days_since_prev_game	Int64	integer	Whole-number numeric column. Calendar days since the home team's prior completed game.
away_days_since_prev_game	Int64	integer	Whole-number numeric column. Calendar days since the away team's prior completed game.
rest_advantage_days	Int64	integer	Whole-number numeric column. Home-team rest gap minus away-team rest gap.
home_rolling_runs_scored_last_5	float64	float	Decimal numeric column. Pregame rolling average runs scored across the home team's previous five completed games.
away_rolling_runs_scored_last_5	float64	float	Decimal numeric column. Pregame rolling average runs scored across the away team's previous five completed games.
home_rolling_runs_allowed_last_5	float64	float	Decimal numeric column. Pregame rolling average runs allowed across the home team's previous five completed games.
away_rolling_runs_allowed_last_5	float64	float	Decimal numeric column. Pregame rolling average runs allowed across the away team's previous five completed games.
home_rolling_total_runs_last_5	float64	float	Decimal numeric column. Pregame rolling average total runs across the home team's previous five completed games.
away_rolling_total_runs_last_5	float64	float	Decimal numeric column. Pregame rolling average total runs across the away team's previous five completed games.
home_rolling_hits_last_5	float64	float	Decimal numeric column. Pregame rolling average hits recorded by the home team across its previous five completed games.
away_rolling_hits_last_5	float64	float	Decimal numeric column. Pregame rolling average hits recorded by the away team across its previous five completed games.
home_rolling_win_pct_last_5	float64	float	Decimal numeric column. Pregame rolling win percentage across the home team's previous five completed games.
away_rolling_win_pct_last_5	float64	float	Decimal numeric column. Pregame rolling win percentage across the away team's previous five completed games.
home_season_to_date_runs_scored_avg	float64	float	Decimal numeric column. Pregame season-to-date average runs scored by the home team before this game.
away_season_to_date_runs_scored_avg	float64	float	Decimal numeric column. Pregame season-to-date average runs scored by the away team before this game.
home_season_to_date_runs_allowed_avg	float64	float	Decimal numeric column. Pregame season-to-date average runs allowed by the home team before this game.
away_season_to_date_runs_allowed_avg	float64	float	Decimal numeric column. Pregame season-to-date average runs allowed by the away team before this game.
home_score	Int64	integer	Whole-number numeric column. Final runs scored by the home team.
away_score	Int64	integer	Whole-number numeric column. Final runs scored by the away team.
total_runs	Int64	integer	Whole-number numeric column. Combined final runs scored in the game.
run_differential	Int64	integer	Whole-number numeric column. Home-team run differential for the game.
home_team_won	bool	boolean	True/false column. Boolean flag showing whether the home team won the game.
home_hits	Int64	integer	Whole-number numeric column. Final hits recorded by the home team.
away_hits	Int64	integer	Whole-number numeric column. Final hits recorded by the away team.
total_hits	Int64	integer	Whole-number numeric column. Combined final hits recorded by both teams.
home_errors	Int64	integer	Whole-number numeric column. Final errors charged to the home team.
away_errors	Int64	integer	Whole-number numeric column. Final errors charged to the away team.
total_errors	Int64	integer	Whole-number numeric column. Combined final errors charged to both teams.
source_url	str	string	Text column. Game endpoint URL from the public MLB Stats API.
source_domain	str	string	Text column. Source domain summary for the dataset row.
last_collected_at	datetime64[us]	datetime	Date or timestamp column. UTC timestamp when this dataset build collected and transformed the row.

Intended Use

This dataset is intended for research, experimentation, analysis, and model prototyping.

Loading the Dataset


import os
from datasets import load_dataset

HUGGINGFACE_API_KEY_KARMANE = os.environ.get("HUGGINGFACE_API_KEY_KARMANE")

dataset = load_dataset(
    "Karmane/mlb-weather-run-environment-research",
    token=HUGGINGFACE_API_KEY_KARMANE,
)

print(dataset)
print(dataset[list(dataset.keys())[0]][0])

# getting the DataFrame itself
# df = dataset[list(dataset.keys())[0]].to_pandas()

Karmane. (2025). MLB Weather and Ballpark Run Environment Dataset for Total Research. Hugging Face. /datasets/Karmane/mlb-weather-run-environment-research

Downloads last month: 16

Total file size:

2.24 MB