Karmane/nba-back-to-back-player-trends-prop-research-sample

NBA Back-to-Back Player Trends Dataset for Prop Research

NBA Back-to-Back Player Trends Dataset for Prop Research

Question this dataset helps answer: Which NBA players historically hold or lose minutes, points, rebounds, assists, and PRA output when they enter back-to-backs, third games in four nights, and other low-rest schedule spots?

This dataset helps sports researchers, fantasy analysts, and player-prop model builders compare low-rest NBA player spots using pregame rest buckets, compressed-schedule flags, rolling player form, and archived spread-total context where available.

Use the public sample to check:

• Which players in the sample are entering true back-to-back games versus one-day-rest or longer-rest spots
• Which columns are pregame schedule or rolling-form features versus postgame stat outcomes
• Which teams, players, and seasons are represented before buying the full multi-season file

Preview vs full dataset:

• Preview: 10000 rows and 98 columns
• Full: 243065 rows and 98 columns

Full dataset: https://thearticulated.gumroad.com/l/nba-back-to-back-player-trends-prop-research

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.

What the public sample can already answer

1. Which players in the sample are on the second night of a back-to-back or another compressed-schedule spot?
2. Which rolling pregame features appear most useful for comparing minutes stability, scoring, rebounds, assists, and PRA output?
3. Which games include archived closing spread and total context, and where does that enrichment stop?

This is a free preview. Load it instantly, inspect the schema, and validate quality before purchasing the full dataset.

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What This Preview Proves

• Sample rows: 10,000 (full dataset: 243,065 rows)
• Columns: 98 fields, fully described below
• Format: parquet (loads in pandas, HF datasets, or any parquet reader)
• No authentication required to load this sample
• Schema and quality are identical to the paid full dataset

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Upgrade to Full Dataset

The full production dataset contains 243,065 rows across 98 columns.

Purchase here: full dataset

After purchase, provide your Hugging Face username and request access on the full dataset page.

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Use Cases

• Compare player PRA output on back-to-backs versus one-day-rest or longer-rest spots.
• Screen players by rolling minutes stability before entering compressed schedule windows.
• Build time-aware notebooks that keep pregame features separate from postgame results.
• Filter for games with archived line context and compare output by spread or total range.

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Column Descriptions

• record_id: Stable unique identifier for one player in one completed NBA game.
• game_id: SportsDataverse and ESPN-derived game identifier.
• season_end_year: Ending year of the NBA season, such as 2026 for the 2025-26 season.
• season_label: Human-readable season label such as 2025-26.
• season_type_label: Regular-season or playoff label for the game.
• game_date: Calendar date of the completed game.
• player_id: Player identifier from the public source feed stored as text.
• player_name: Player full display name.
• player_short_name: Short display name from the source feed.
• player_position: Position label from the source feed.
• player_position_abbreviation: Position abbreviation from the source feed.
• team_id: Team identifier for the player row.
• team_abbreviation: Team abbreviation for the player row.
• team_display_name: Team display name for the player row.
• opponent_team_id: Opponent team identifier.
• opponent_team_abbreviation: Opponent team abbreviation.
• opponent_team_display_name: Opponent team display name.
• home_away: Home or away label for the player row.
• is_home: Boolean flag showing whether the player was on the home team.
• starter_flag: Boolean flag showing whether the player started the game.
• is_playoff_game: Boolean flag for playoff rows.
• venue_full_name: Venue name from the public schedule feed.
• venue_address_city: Venue city from the public schedule feed.
• venue_address_state: Venue state or province from the public schedule feed.
• venue_indoor: Boolean flag for indoor venue status.
• days_since_prev_game: Calendar-day gap between the team's previous completed game and this game.
• rest_bucket: Bucketed rest label derived from days_since_prev_game.
• is_back_to_back: Boolean flag for the second night of a back-to-back or zero-rest spot.
• games_in_last_4_days_including_today: Count of team games within the current 4-day window including this game.
• is_third_game_in_four_nights: Boolean flag showing whether the team reached a three-games-in-four-nights spot.
• games_in_last_6_days_including_today: Count of team games within the current 6-day window including this game.
• is_fourth_game_in_six_nights: Boolean flag showing whether the team reached a four-games-in-six-nights spot.
• opponent_days_since_prev_game: Calendar-day gap for the opponent team entering the same game.
• opponent_is_back_to_back: Boolean flag showing whether the opponent was also on a back-to-back.
• rest_advantage_days: Team rest gap minus opponent rest gap.
• is_rest_advantage: Boolean flag for positive rest_advantage_days.
• is_rest_disadvantage: Boolean flag for negative rest_advantage_days.
• has_archived_closing_line_context: Boolean flag showing whether archived spread and total context was available for the game.
• closing_spread_line: Team-side archived closing spread line when available. Negative values indicate the player's team was favored.
• closing_total_line: Archived closing game total line when available.
• team_favorite_flag: Boolean flag for games where the player's team closed as the favorite when archived lines were available.
• pickem_flag: Boolean flag for games with an effectively even archived spread line.
• team_implied_total: Approximate team implied total derived from the archived spread and total lines when available.
• opponent_implied_total: Approximate opponent implied total derived from the archived spread and total lines when available.
• minutes: Minutes played by the player in the game.
• field_goals_made: Field goals made by the player.
• field_goals_attempted: Field goals attempted by the player.
• three_point_field_goals_made: Three-point field goals made by the player.
• three_point_field_goals_attempted: Three-point field goals attempted by the player.
• free_throws_made: Free throws made by the player.
• free_throws_attempted: Free throws attempted by the player.
• offensive_rebounds: Offensive rebounds by the player.
• defensive_rebounds: Defensive rebounds by the player.
• rebounds: Total rebounds by the player.
• assists: Assists by the player.
• steals: Steals by the player.
• blocks: Blocks by the player.
• turnovers: Turnovers by the player.
• fouls: Personal fouls by the player.
• plus_minus: Plus-minus from the public box score.
• points: Points scored by the player.
• team_score: Final points scored by the player's team.
• opponent_team_score: Final points scored by the opponent team.
• team_margin: Final point differential from the player-team perspective.
• won_game: Boolean flag showing whether the player's team won.
• total_points: Combined final points in the game.
• points_rebounds_assists: Sum of player points, rebounds, and assists.
• points_rebounds: Sum of player points and rebounds.
• points_assists: Sum of player points and assists.
• rebounds_assists: Sum of player rebounds and assists.
• stocks: Sum of player steals and blocks.
• simple_fantasy_points: Simple fantasy-style scoring proxy derived from points, rebounds, assists, steals, blocks, and turnovers.
• points_per_minute: Points scored per minute played.
• rebounds_per_minute: Rebounds per minute played.
• assists_per_minute: Assists per minute played.
• three_point_attempt_rate: Three-point attempts per minute played.
• free_throw_attempt_rate: Free-throw attempts per minute played.
• prior_games_played: Count of prior recorded games for the same player before this row.
• season_to_date_games: Count of prior same-season games for the same player before this row.
• rolling_minutes_last_3: Pregame rolling average of minutes across the previous 3 recorded games.
• rolling_minutes_last_5: Pregame rolling average of minutes across the previous 5 recorded games.
• rolling_points_last_3: Pregame rolling average of points across the previous 3 recorded games.
• rolling_points_last_5: Pregame rolling average of points across the previous 5 recorded games.
• rolling_rebounds_last_5: Pregame rolling average of rebounds across the previous 5 recorded games.
• rolling_assists_last_5: Pregame rolling average of assists across the previous 5 recorded games.
• rolling_pra_last_5: Pregame rolling average of PRA across the previous 5 recorded games.
• rolling_three_pa_last_5: Pregame rolling average of three-point attempts across the previous 5 recorded games.
• rolling_fantasy_points_last_5: Pregame rolling average of simple fantasy points across the previous 5 recorded games.
• season_to_date_minutes_avg: Pregame same-season average minutes before this game.
• season_to_date_points_avg: Pregame same-season average points before this game.
• season_to_date_rebounds_avg: Pregame same-season average rebounds before this game.
• season_to_date_assists_avg: Pregame same-season average assists before this game.
• home_points_avg_before_game: Pregame average points in prior home games for the same player.
• away_points_avg_before_game: Pregame average points in prior away games for the same player.
• same_rest_bucket_points_avg_before_game: Pregame average points in prior games that shared the same rest_bucket for the same player.
• source_url: Game-level JSON URL from the public SportsDataverse schedule source.
• source_domain: Source domain summary for this dataset row.
• last_collected_at: UTC timestamp when this dataset build collected and transformed the row.

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Dataset Structure

• Rows: 10,000
• Columns: 98
• Split: data
• File: data/data.parquet

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Full Dataset Access

	Sample (this repo)	Full Dataset
Rows	10,000	243,065
Columns	98	98
Auth required	No	Yes (after purchase)
Price	Free	See pricing

Final CTA

Get the full dataset: https://thearticulated.gumroad.com/l/vguxg?utm_source=hf_sample_readme&utm_medium=referral&utm_campaign=nba-back-to-back-player-trends-prop-research

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Karmane. (2025). NBA Back-to-Back Player Trends Dataset for Prop Research (Free Sample). Hugging Face. https://huggingface.co/datasets/Karmane/nba-back-to-back-player-trends-prop-research-sample