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Karmane
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nfl-anytime-touchdown-parlay-usage-trends

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Tabular Classification
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parquet
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10K - 100K
Tags:
nfl
parlay-research
anytime-touchdown
sports
sports-analytics
sports-betting-research
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Datasets
pandas
Polars
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xet
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NFL Anytime Touchdown Parlay Research Dataset for Player Usage and Team Total Trends

Question this dataset helps answer

Which NFL skill players historically clear anytime-touchdown parlay legs, and what pregame snap share, touch share, and implied team-total context was present before kickoff?

Short answer

This dataset helps sports researchers, fantasy analysts, and parlay model builders compare NFL anytime-touchdown leg context using pregame snap share, touch share, rest and market context, opponent-position allowance trends, and implied team totals.

What the public preview proves

  • Which players in the sample carry strong recent snap share, touch share, and implied team-total context before scoring or missing touchdown legs
  • Which columns are pregame usage and market features versus postgame touchdown, yardage, and reception outcomes
  • Which teams, players, positions, and seasons are represented before buying the full multi-season file

Public preview vs full dataset

  • Preview: 3932 rows and 126 columns
  • Full: 78641 rows and 126 columns

Full dataset access: https://thearticulated.gumroad.com/l/nfl-anytime-touchdown-trends

from datasets import load_dataset; ds = load_dataset("Karmane/nfl-anytime-touchdown-parlay-usage-trends-sample"); print(ds["train"].to_pandas().head())

This product is built around a specific recurring workflow problem. Plenty of public NFL stats exist, but the buyer question is not "where can I find touchdowns?" The real problem is that analysts who care about anytime-touchdown parlay research usually have to rebuild the same joins over and over again. They need the player-game history, snap exposure, basic usage volume, team scoring environment, a way to estimate whether the opponent has been allowing touchdown and scrimmage-yard outcomes to that position group, and a clean line between features that were knowable before kickoff and outcomes that only existed after the game finished. This dataset packages that structure directly.

Each row represents one offensive skill player in one completed NFL game where the player logged offensive snaps. The coverage spans the 2013 through 2024 seasons and includes 78641 player-game rows across 126 columns. That row volume matters. It is large enough for dashboard analysis, historical filtering, rolling hit-rate research, feature engineering, and exploratory modeling without reducing the product to a tiny case-study sample. Buyers can group by player, team, position, season, implied team-total bucket, favorite status, or opponent and still retain meaningful sample sizes for comparison.

The pregame side of the table is built around usage and scoring context. Key feature groups include offense_snaps, offense_snap_pct, rest_bucket, rest_advantage_days, team_moneyline_implied_prob, implied_team_total, implied_team_total_bucket, game_target_share, game_touch_share, and rolling fields such as rolling_offense_snap_pct_last_5, rolling_targets_last_5, rolling_scrimmage_yards_last_5, rolling_anytime_td_rate_last_5, rolling_touch_share_last_5, and season_to_date_anytime_td_rate. The dataset also includes opponent-position allowance features such as opponent_allowed_anytime_td_rate_to_position_last_5 and opponent_allowed_scrimmage_yards_to_position_last_5, which are designed to support the exact questions that come up in anytime-touchdown parlay research: whether the player's recent role is stable, whether the team environment supports scoring, and whether the matchup has recently allowed similar players to convert.

The postgame side of the table holds the actual leg outcomes. Those outcome columns include touchdowns, rushing and receiving production, receptions, scrimmage yards, target and carry shares within the completed game, team score, opponent score, and multiple common thresholds such as cleared_anytime_td, cleared_40_receiving_yards, cleared_5_receptions, and cleared_75_scrimmage_yards. That separation matters. A buyer can use the pregame fields as features and keep the postgame fields as targets, which makes the dataset usable for responsible historical modeling or descriptive analysis. It also makes the sample immediately interpretable for dashboard work because the logic of "known before kickoff" versus "observed after the game" is visible in the schema.

Closing spread, moneyline, and total context are also included where the public source supports them. Those columns are intentionally useful but not over-promised. Buyers who want purely usage-based analysis can ignore the market fields. Buyers who want to compare touchdown-leg outcomes against implied team totals, favorite status, or moneyline probability can keep them. That is a better product design than pretending every workflow needs the same surface area.

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 offensive skill player in one completed NFL game where the player logged offensive snaps.
  • Pregame features include snap exposure, rest context, home-away status, moneyline and spread fields, implied team totals, and rolling usage or touchdown-hit trends.
  • Postgame outcomes include touchdowns, receptions, rushing and receiving production, scrimmage yards, team score context, and multiple common leg-threshold flags.
  • The coverage window runs from the 2013 season through the 2024 season.
  • The full dataset contains 78641 rows, which is large enough for train-test splits by season, by calendar cutoff, or by player history depth.
  • A sensible modeling workflow would split by season or by game date rather than shuffling randomly, because the product is inherently time-ordered.
  • Opponent allowance features are built from prior games only, so they can be treated as pregame inputs rather than leaked outcomes.
  • The table starts from offensive-snap rows rather than only positive stat lines, which means the dataset keeps many zero-touchdown and zero-yardage outcomes that matter for realistic screening.
  • 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 core buyer task is real. A buyer can open the sample and immediately test whether the file contains the right player IDs, touchdown-leg outcomes, snap and touch context, implied team totals, opponent-allowance features, and threshold flags. They can verify which seasons are covered, which players appear, how the schema separates pregame context from postgame results, and whether the anytime-touchdown parlay workflow fits their notebook or dashboard plan. That is exactly what a public discovery asset should do: prove usefulness before the full purchase.

Source and build notes

The build uses public nflverse snap counts, player identifiers, weekly player stats, and schedules, then engineers rolling usage, touchdown-hit, and opponent-allowance features locally. The process is reproducible, versionable, and avoids paid touchdown-prop feeds. That keeps the dataset commercially useful without depending on a brittle or private source stack. The output is a single analysis-ready table rather than a collection of raw files that still need substantial cleaning and joins.

Dataset Preview

record_id game_id season game_type week game_date weekday gametime is_playoff_game player_id player_name player_display_name player_short_name player_position player_position_group team opponent team_side is_home height weight rookie_season years_of_experience draft_round draft_pick offense_snaps offense_snap_pct st_snaps st_pct div_game rest_days opponent_rest_days rest_advantage_days rest_bucket is_short_week is_long_rest roof surface stadium temp wind team_moneyline opponent_moneyline team_moneyline_implied_prob opponent_moneyline_implied_prob team_spread_line closing_total_line team_favorite_flag pickem_flag has_closing_line_context implied_team_total implied_opponent_total implied_team_total_bucket completions attempts passing_yards passing_tds interceptions sacks carries rushing_yards rushing_tds rushing_first_downs rushing_epa receptions targets receiving_yards receiving_tds receiving_first_downs receiving_epa target_share air_yards_share wopr special_teams_tds fantasy_points fantasy_points_ppr scrimmage_yards rush_rec_tds total_tds touches team_skill_carries team_targets team_touches game_carry_share game_target_share game_touch_share prior_games_played season_to_date_games rolling_offense_snap_pct_last_3 rolling_offense_snap_pct_last_5 rolling_carries_last_3 rolling_targets_last_3 rolling_targets_last_5 rolling_receptions_last_5 rolling_rush_yards_last_5 rolling_receiving_yards_last_5 rolling_scrimmage_yards_last_5 rolling_total_tds_last_5 rolling_anytime_td_rate_last_5 season_to_date_anytime_td_rate rolling_target_share_last_5 rolling_carry_share_last_5 rolling_touch_share_last_5 season_to_date_touch_share_avg opponent_allowed_anytime_td_rate_to_position_last_5 opponent_allowed_scrimmage_yards_to_position_last_5 opponent_allowed_targets_to_position_last_5 opponent_allowed_receptions_to_position_last_5 team_score opponent_score team_margin won_game total_points cleared_anytime_td cleared_40_rush_yards cleared_60_rush_yards cleared_25_receiving_yards cleared_40_receiving_yards cleared_60_receiving_yards cleared_3_receptions cleared_5_receptions cleared_50_scrimmage_yards cleared_75_scrimmage_yards source_url source_domain last_collected_at
2013_01_ATL_NO_00-0006101 2013_01_ATL_NO 2013 REG 1 2013-09-08 00:00:00 Sunday 13:00 False 00-0006101 Tony Gonzalez Tony Gonzalez Tony Gonzalez TE TE ATL NO away False 77 247 1997 17 1 13 51 0.91 0 0 True 7 7 0 standard_rest False False dome sportturf Mercedes-Benz Superdome 166 -185 0.37594 0.649123 3.5 54.5 False False True 25.5 29 24_to_27_9 0 0 0 0 0 0 0 0 0 0 0 3 6 36 1 3 -0.790186 0.166667 0.213115 0.39918 0 9.6 12.6 36 1 1 6 14 36 50 0.0 0.166667 0.12 0 0 17 23 -6 False 40 True False False True False False True False False False https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet github.com, nflverse.com 2026-06-11 23:31:35.133156
2013_02_STL_ATL_00-0006101 2013_02_STL_ATL 2013 REG 2 2013-09-15 00:00:00 Sunday 13:00 False 00-0006101 Tony Gonzalez Tony Gonzalez Tony Gonzalez TE TE ATL STL home True 77 247 1997 17 1 13 62 0.97 0 0 False 7 7 0 standard_rest False False dome fieldturf Georgia Dome -204 183 0.671053 0.353357 -4 47.5 True False True 25.75 21.75 24_to_27_9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0.91 0.91 0.0 6.0 6.0 3.0 0.0 36.0 36.0 1.0 1.0 1.0 0.166667 0.0 0.12 0.12 0.0 0.0 0.0 0.0 31 24 7 True 55 False False False False False False False False False False https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet github.com, nflverse.com 2026-06-11 23:31:35.133156
2013_03_ATL_MIA_00-0006101 2013_03_ATL_MIA 2013 REG 3 2013-09-22 00:00:00 Sunday 16:05 False 00-0006101 Tony Gonzalez Tony Gonzalez Tony Gonzalez TE TE ATL MIA away False 77 247 1997 17 1 13 61 0.86 0 0 False 7 7 0 standard_rest False False outdoors grass Sun Life Stadium 89.0 8.0 127 -140 0.440529 0.583333 3 45.5 False False True 21.25 24.25 20_to_23_9 0 0 0 0 0 0 0 0 0 0 0 4 5 24 0 3 2.75705 0.135135 0.121951 0.288069 0 2.4 6.4 24 0 0 5 30 37 67 0.0 0.135135 0.074627 2 2 0.94 0.94 0.0 3.0 3.0 1.5 0.0 18.0 18.0 0.5 0.5 0.5 0.166667 0.0 0.12 0.12 0.5 49.75 6.0 3.75 23 27 -4 False 50 False False False False False False True False False False https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet github.com, nflverse.com 2026-06-11 23:31:35.133156
2013_04_NE_ATL_00-0006101 2013_04_NE_ATL 2013 REG 4 2013-09-29 00:00:00 Sunday 20:30 False 00-0006101 Tony Gonzalez Tony Gonzalez Tony Gonzalez TE TE ATL NE home True 77 247 1997 17 1 13 74 0.97 0 0 False 7 7 0 standard_rest False False dome fieldturf Georgia Dome -156 141 0.609375 0.414938 -3 49 True False True 26 23 24_to_27_9 0 0 0 0 0 0 0 0 0 0 0 12 14 149 2 8 11.266 0.264151 0.277273 0.590317 0 26.9 38.9 149 2 2 14 15 53 68 0.0 0.264151 0.205882 3 3 0.913333 0.913333 0.0 3.666667 3.666667 2.333333 0.0 20.0 20.0 0.333333 0.333333 0.333333 0.150901 0.0 0.097313 0.097313 0.0 10.5 2.5 1.5 23 30 -7 False 53 True False False True True True True True True True https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet github.com, nflverse.com 2026-06-11 23:31:35.133156
2013_05_NYJ_ATL_00-0006101 2013_05_NYJ_ATL 2013 REG 5 2013-10-07 00:00:00 Monday 20:30 False 00-0006101 Tony Gonzalez Tony Gonzalez Tony Gonzalez TE TE ATL NYJ home True 77 247 1997 17 1 13 73 0.96 0 0 False 8 8 0 mini_bye_range False True dome fieldturf Georgia Dome -467 398 0.823633 0.200803 -10 45 True False True 27.5 17.5 24_to_27_9 0 0 0 0 0 0 0 0 0 0 0 10 14 97 0 7 5.02336 0.311111 0.290625 0.670104 0 9.7 19.7 97 0 0 14 22 45 67 0.0 0.311111 0.208955 4 4 0.933333 0.9275 0.0 6.333333 6.25 4.75 0.0 52.25 52.25 0.75 0.5 0.5 0.188651 0.0 0.133503 0.133503 0.208333 11.125 1.291667 0.958333 28 30 -2 False 58 False False False True True True True True True True https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet github.com, nflverse.com 2026-06-11 23:31:35.133156

Access Requirements (Paid Dataset)

This dataset is behind manual gated access.

To obtain access:

  1. Full dataset access:
    https://thearticulated.gumroad.com/l/nfl-anytime-touchdown-trends

  2. Provide your Hugging Face username at checkout.

  3. Return to this Hugging Face page and click:
    "Request Access"

  4. 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: 78,641

Total columns: 126

Splits

  • data: 78,641 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 string Text column. Stable row identifier built from the nflverse game id and the mapped player id.
game_id str string Text column. Original nflverse game identifier.
season Int64 integer Whole-number numeric column. NFL season year.
game_type str string Text column. Game type from the public schedule source such as REG, WC, DIV, CON, or SB.
week Int64 integer Whole-number numeric column. Week number within the NFL season and playoff calendar.
game_date datetime64[us] datetime Date or timestamp column. Date of the game.
weekday str string Text column. Weekday label from the schedule source.
gametime str datetime-like string Stored as text, but values appear to represent dates or timestamps. Scheduled kickoff time string from the source schedule.
is_playoff_game bool boolean True/false column. Boolean flag showing whether the row came from a playoff game.
player_id str string Text column. Stable nflverse player identifier.
player_name str string Text column. Player name from the snap-count source.
player_display_name str string Text column. Display name from the nflverse player table.
player_short_name str string Text column. Short display name from the nflverse player table.
player_position str string Text column. Position code for the player in the snap-count source.
player_position_group str string Text column. Position group from the nflverse player table.
team str string Text column. Player team abbreviation.
opponent str string Text column. Opponent team abbreviation.
team_side str string Text column. Home or away from the player-team perspective.
is_home bool boolean True/false column. Boolean flag showing whether the player team was at home.
height Int64 integer Whole-number numeric column. Player height from the nflverse player table.
weight Int64 integer Whole-number numeric column. Player weight from the nflverse player table.
rookie_season Int64 integer Whole-number numeric column. Player rookie season from the nflverse player table when available.
years_of_experience Int64 integer Whole-number numeric column. Player years of experience when available.
draft_round Int64 integer Whole-number numeric column. Draft round from the player table when available.
draft_pick Int64 integer Whole-number numeric column. Draft pick number from the player table when available.
offense_snaps Int64 integer Whole-number numeric column. Number of offensive snaps played in the game.
offense_snap_pct float64 float Decimal numeric column. Share of offensive snaps played in the game.
st_snaps Int64 integer Whole-number numeric column. Special-teams snaps played in the game.
st_pct float64 float Decimal numeric column. Share of special-teams snaps played in the game.
div_game bool boolean True/false column. Boolean flag for divisional matchups.
rest_days Int64 integer Whole-number numeric column. Days of rest for the player team entering the game.
opponent_rest_days Int64 integer Whole-number numeric column. Days of rest for the opponent entering the game.
rest_advantage_days Int64 integer Whole-number numeric column. Team rest days minus opponent rest days.
rest_bucket str string Text column. Categorical rest bucket derived from team rest days.
is_short_week bool boolean True/false column. Boolean flag for rest buckets of four days or less.
is_long_rest bool boolean True/false column. Boolean flag for rest buckets of eight days or more.
roof str string Text column. Roof type from the public schedule source.
surface str string Text column. Playing surface from the public schedule source.
stadium str string Text column. Venue name from the public schedule source.
temp float64 float Decimal numeric column. Game-temperature field from the public schedule source when available.
wind float64 float Decimal numeric column. Wind-speed field from the public schedule source when available.
team_moneyline Int64 integer Whole-number numeric column. Closing moneyline for the player team when available.
opponent_moneyline Int64 integer Whole-number numeric column. Closing moneyline for the opponent when available.
team_moneyline_implied_prob float64 float Decimal numeric column. Implied win probability derived from the player-team moneyline.
opponent_moneyline_implied_prob float64 float Decimal numeric column. Implied win probability derived from the opponent moneyline.
team_spread_line float64 float Decimal numeric column. Closing spread from the player-team perspective. Negative values indicate the team was favored.
closing_total_line float64 float Decimal numeric column. Closing game total line when available.
team_favorite_flag bool boolean True/false column. Boolean flag for games where the player team closed as the favorite.
pickem_flag bool boolean True/false column. Boolean flag for near-pickem spread lines.
has_closing_line_context bool boolean True/false column. Boolean flag showing whether spread and total fields were available.
implied_team_total float64 float Decimal numeric column. Approximate implied total derived from the closing spread and total.
implied_opponent_total float64 float Decimal numeric column. Approximate opponent implied total derived from the closing spread and total.
implied_team_total_bucket str string Text column. Bucketed version of the implied team total.
completions Int64 integer Whole-number numeric column. Player completions from the public weekly stats file.
attempts Int64 integer Whole-number numeric column. Player pass attempts from the public weekly stats file.
passing_yards Int64 integer Whole-number numeric column. Player passing yards from the public weekly stats file.
passing_tds Int64 integer Whole-number numeric column. Player passing touchdowns from the public weekly stats file.
interceptions Int64 integer Whole-number numeric column. Player interceptions thrown from the public weekly stats file.
sacks Int64 integer Whole-number numeric column. Sacks taken by the player from the public weekly stats file.
carries Int64 integer Whole-number numeric column. Player rushing attempts.
rushing_yards Int64 integer Whole-number numeric column. Player rushing yards.
rushing_tds Int64 integer Whole-number numeric column. Player rushing touchdowns.
rushing_first_downs Int64 integer Whole-number numeric column. Player rushing first downs.
rushing_epa float64 float Decimal numeric column. Player rushing EPA from the public weekly stats file.
receptions Int64 integer Whole-number numeric column. Player receptions.
targets Int64 integer Whole-number numeric column. Player targets.
receiving_yards Int64 integer Whole-number numeric column. Player receiving yards.
receiving_tds Int64 integer Whole-number numeric column. Player receiving touchdowns.
receiving_first_downs Int64 integer Whole-number numeric column. Player receiving first downs.
receiving_epa float64 float Decimal numeric column. Player receiving EPA from the public weekly stats file.
target_share float64 float Decimal numeric column. Public source target share when available.
air_yards_share float64 float Decimal numeric column. Public source air-yards share when available.
wopr float64 float Decimal numeric column. Public source WOPR metric when available.
special_teams_tds Int64 integer Whole-number numeric column. Special-teams touchdowns from the public weekly stats file.
fantasy_points float64 float Decimal numeric column. Fantasy points from the public weekly stats file.
fantasy_points_ppr float64 float Decimal numeric column. PPR fantasy points from the public weekly stats file.
scrimmage_yards Int64 integer Whole-number numeric column. Sum of rushing and receiving yards.
rush_rec_tds Int64 integer Whole-number numeric column. Sum of rushing and receiving touchdowns.
total_tds Int64 integer Whole-number numeric column. Sum of rushing, receiving, and special-teams touchdowns.
touches Int64 integer Whole-number numeric column. Sum of carries and targets used as a simple usage proxy.
team_skill_carries Int64 integer Whole-number numeric column. Total carries logged by skill-position rows for the same team-game in this dataset.
team_targets Int64 integer Whole-number numeric column. Total targets logged by skill-position rows for the same team-game in this dataset.
team_touches Int64 integer Whole-number numeric column. Total touches logged by skill-position rows for the same team-game in this dataset.
game_carry_share float64 float Decimal numeric column. Player carry share within the team-game among rows in this dataset.
game_target_share float64 float Decimal numeric column. Player target share within the team-game among rows in this dataset.
game_touch_share float64 float Decimal numeric column. Player touch share within the team-game among rows in this dataset.
prior_games_played Int64 integer Whole-number numeric column. Number of prior player rows in the full history before this game.
season_to_date_games Int64 integer Whole-number numeric column. Number of prior same-season player rows before this game.
rolling_offense_snap_pct_last_3 float64 float Decimal numeric column. Pregame rolling average offensive snap share over the previous 3 games.
rolling_offense_snap_pct_last_5 float64 float Decimal numeric column. Pregame rolling average offensive snap share over the previous 5 games.
rolling_carries_last_3 float64 float Decimal numeric column. Pregame rolling average carries over the previous 3 games.
rolling_targets_last_3 float64 float Decimal numeric column. Pregame rolling average targets over the previous 3 games.
rolling_targets_last_5 float64 float Decimal numeric column. Pregame rolling average targets over the previous 5 games.
rolling_receptions_last_5 float64 float Decimal numeric column. Pregame rolling average receptions over the previous 5 games.
rolling_rush_yards_last_5 float64 float Decimal numeric column. Pregame rolling average rushing yards over the previous 5 games.
rolling_receiving_yards_last_5 float64 float Decimal numeric column. Pregame rolling average receiving yards over the previous 5 games.
rolling_scrimmage_yards_last_5 float64 float Decimal numeric column. Pregame rolling average scrimmage yards over the previous 5 games.
rolling_total_tds_last_5 float64 float Decimal numeric column. Pregame rolling average total touchdowns over the previous 5 games.
rolling_anytime_td_rate_last_5 float64 float Decimal numeric column. Pregame rolling anytime-touchdown hit rate over the previous 5 games.
season_to_date_anytime_td_rate float64 float Decimal numeric column. Pregame season-to-date anytime-touchdown hit rate before this game.
rolling_target_share_last_5 float64 float Decimal numeric column. Pregame rolling average target share over the previous 5 games.
rolling_carry_share_last_5 float64 float Decimal numeric column. Pregame rolling average carry share over the previous 5 games.
rolling_touch_share_last_5 float64 float Decimal numeric column. Pregame rolling average touch share over the previous 5 games.
season_to_date_touch_share_avg float64 float Decimal numeric column. Pregame season-to-date average touch share before this game.
opponent_allowed_anytime_td_rate_to_position_last_5 float64 float Decimal numeric column. Pregame rolling rate at which the opponent allowed anytime-touchdown hits to this position group over its previous 5 games.
opponent_allowed_scrimmage_yards_to_position_last_5 float64 float Decimal numeric column. Pregame rolling average scrimmage yards allowed by the opponent to this position group over its previous 5 games.
opponent_allowed_targets_to_position_last_5 float64 float Decimal numeric column. Pregame rolling average targets allowed by the opponent to this position group over its previous 5 games.
opponent_allowed_receptions_to_position_last_5 float64 float Decimal numeric column. Pregame rolling average receptions allowed by the opponent to this position group over its previous 5 games.
team_score Int64 integer Whole-number numeric column. Final points scored by the player team.
opponent_score Int64 integer Whole-number numeric column. Final points scored by the opponent team.
team_margin Int64 integer Whole-number numeric column. Final score margin from the player-team perspective.
won_game bool boolean True/false column. Boolean flag showing whether the player team won.
total_points Int64 integer Whole-number numeric column. Combined final points in the game.
cleared_anytime_td bool boolean True/false column. Boolean flag showing whether the player scored any touchdown in the game.
cleared_40_rush_yards bool boolean True/false column. Boolean flag for rushing-yard outcome of at least 40.
cleared_60_rush_yards bool boolean True/false column. Boolean flag for rushing-yard outcome of at least 60.
cleared_25_receiving_yards bool boolean True/false column. Boolean flag for receiving-yard outcome of at least 25.
cleared_40_receiving_yards bool boolean True/false column. Boolean flag for receiving-yard outcome of at least 40.
cleared_60_receiving_yards bool boolean True/false column. Boolean flag for receiving-yard outcome of at least 60.
cleared_3_receptions bool boolean True/false column. Boolean flag for reception outcome of at least 3.
cleared_5_receptions bool boolean True/false column. Boolean flag for reception outcome of at least 5.
cleared_50_scrimmage_yards bool boolean True/false column. Boolean flag for scrimmage-yard outcome of at least 50.
cleared_75_scrimmage_yards bool boolean True/false column. Boolean flag for scrimmage-yard outcome of at least 75.
source_url str string Text column. Primary public source URL used for the build.
source_domain str string Text column. Source domain summary for the row.
last_collected_at datetime64[us] datetime Date or timestamp column. UTC timestamp when the row was collected and transformed.

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/nfl-anytime-touchdown-parlay-usage-trends",
    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). NFL Anytime Touchdown Parlay Research Dataset for Player Usage and Team Total Trends. Hugging Face. https://huggingface.co/datasets/Karmane/nfl-anytime-touchdown-parlay-usage-trends
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