Update README.md

README.md

@@ -208,4 +208,208 @@ configs:
   data_files:
   - split: full
     path: data/full-*
+license: mit
+language:
+- en
 ---
+
+# NFL Wide Receiver Performance Dataset (2019)
+
+## Dataset Description
+
+This dataset contains comprehensive wide receiver performance statistics derived from NFL play-by-play data for the **2019**. It includes game-level metrics, situational targeting patterns, defensive adjustments, and advanced efficiency calculations.
+
+### Dataset Summary
+
+- **Season**: 2015
+- **Records**: ~4.31k player-game observations
+- **Features**: 100+ columns including:
+  - Core statistics (targets, receptions, yards, touchdowns)
+  - Quarter-by-quarter breakdowns
+  - Win probability bucketed performance
+  - Defensive strength adjustments
+  - Situational metrics (red zone, high leverage, down-and-distance)
+  - Team share metrics (target share, air yards share, WOPR)
+  - Efficiency metrics (aDOT, yards per target, catch rate)
+  - Weather and venue conditions
+
+### Supported Tasks
+
+- **Receiving Yards Prediction**: Predict receiving yards for upcoming games
+- **Target Share Analysis**: Model player opportunity distribution
+- **Performance Forecasting**: Project future player performance
+- **Matchup Analysis**: Evaluate player-defense matchups
+
+## Dataset Structure
+
+### Data Fields
+
+**Key Identifiers:**
+- `game_id`: Unique game identifier
+- `receiver_player_id`: NFL GSIS player ID
+- `receiver_player_name`: Player display name
+- `passer_player_id`: Quarterback player ID
+- `season`: NFL season year
+- `week`: Week number
+
+**Core Statistics:**
+- `targets`: Total pass attempts targeting the receiver
+- `receptions`: Completed receptions
+- `receiving_yards`: Total receiving yards
+- `tds`: Receiving touchdowns
+- `air_yards`: Total air yards on targets
+- `yac`: Yards after catch
+
+**Quarter Breakdowns:**
+- `yards_Q1`, `yards_Q2`, `yards_Q3`, `yards_Q4`: Yards by quarter
+- `receptions_Q1-4`: Receptions by quarter
+- `targets_Q1-4`: Targets by quarter
+
+**Win Probability Buckets:**
+- `yards_wp_<25`, `yards_wp_25_45`, etc.: Performance in different game situations
+- Similar breakdowns for receptions and targets
+
+**Share Metrics:**
+- `target_share`: Player's share of team targets
+- `air_yards_share`: Player's share of team air yards
+- `yard_share`: Player's share of team receiving yards
+- `reception_share`: Player's share of team receptions
+- `wopr`: Weighted Opportunity Rating (0.7 × target_share + 0.3 × air_yards_share)
+
+**Efficiency Metrics:**
+- `aDOT`: Average depth of target
+- `yards_per_target`: Receiving yards per target
+- `catch_rate`: Reception percentage
+- `yac_per_rec`: Yards after catch per reception
+- `explosive_rec_pct`: Percentage of receptions ≥15 yards
+- `first_down_pct`: Percentage of receptions resulting in first downs
+
+**Defensive Adjustments:**
+- `def_targets_dev`: Defense targets allowed vs league average
+- `def_receptions_dev`: Defense receptions allowed vs league average
+- `def_yards_dev`: Defense yards allowed vs league average
+- `def_tds_dev`: Defense TDs allowed vs league average
+- `def_epa_dev`: Defense EPA allowed vs league average
+- `adj_epa`: Defense-adjusted Expected Points Added
+- `adj_epa_per_target`: Defense-adjusted EPA per target
+
+**Situational Metrics:**
+- `red_zone_targets`: Targets inside the 20-yard line
+- `end_zone_targets`: Targets in the end zone
+- `third_down_targets`: Targets on 3rd down
+- `fourth_down_targets`: Targets on 4th down
+- `high_leverage_targets`: Targets in high-leverage situations (WP < 0.25 or > 0.75)
+- `red_zone_share`: Player's share of team red zone targets
+- `third_down_share`: Player's share of team 3rd down targets
+
+**Game Context:**
+- `posteam`: Player's team (encoded 1-32)
+- `defteam`: Opposing defense (encoded 1-32)
+- `home_team`: Home team (encoded 1-32)
+- `away_team`: Away team (encoded 1-32)
+- `home_flag`: 0 if home, 1 if away
+- `pregame_spread`: Betting line point spread
+- `pregame_total`: Betting line total points
+- `avg_score_diff`: Average score differential when targeted
+- `avg_quarter`: Average quarter when targeted
+- `trailing_pct`: Percentage of targets while trailing
+- `leading_pct`: Percentage of targets while leading
+
+**Weather & Venue:**
+- `surface`: Playing surface type (encoded 0-6)
+- `is_dome`: 1 if indoor, 0 if outdoor
+- `is_rain`: 1 if rainy conditions
+- `is_snow`: 1 if snowy conditions
+- `is_clear`: 1 if clear conditions
+- `temp_f`: Temperature in Fahrenheit
+- `humidity_pct`: Humidity percentage
+- `wind_mph`: Wind speed in miles per hour
+
+**QB Context:**
+- `qb_completions`: Quarterback's completions that game
+- `qb_attempts`: Quarterback's attempts that game
+- `qb_comp_pct`: Quarterback's completion percentage
+- `qb_air_yards`: Quarterback's average air yards
+- `qb_cpoe`: Quarterback's completion percentage over expected
+
+**Advanced Metrics:**
+- `epa`: Expected Points Added
+- `wpa`: Win Probability Added
+- `success_rate`: Percentage of successful plays (EPA > 0 or YPT > 0.5)
+- `big_play_rate`: Percentage of plays ≥20 yards
+- `explosive_plays`: Count of plays ≥20 yards
+- `first_downs`: First downs generated
+- `consistency_score`: mean_adj_epa / std_adj_epa
+- `inverse_volatility`: 1 / std_adj_epa
+- `season_adj_epa_per_target`: Season-level defense-adjusted EPA per target
+- `wp_var`: Variance in win probability across targets
+- `target_share_std`: Standard deviation of target share across games
+
+### Data Splits
+
+This dataset does not include pre-defined splits. Users should create their own train/validation/test splits based on their use case:
+- **Time-based split**: Use early weeks for training, later weeks for validation/testing
+- **Cross-validation**: K-fold cross-validation across games
+- **Season holdout**: Train on this season, test on future seasons
+
+### Dataset Creation
+
+#### Source Data
+
+Raw play-by-play data sourced from [nflverse](https://github.com/nflverse/nflverse-data/releases/tag/pbp), which aggregates official NFL data with additional features.
+
+#### Data Processing
+
+The dataset was created through two complementary processing pipelines:
+
+1. **Pipeline A (Defensive Adjustments)**: 
+   - Calculates defense-adjusted performance metrics
+   - Adds situational targeting patterns
+   - Includes QB context and team-level statistics
+   - Incorporates weather and venue conditions
+
+2. **Pipeline B (Temporal & Situational)**: 
+   - Generates quarter-by-quarter breakdowns
+   - Creates win probability bucketed statistics
+   - Computes team share metrics and WOPR
+   - Calculates season-level consistency metrics
+
+Both pipelines were merged to create a comprehensive feature set.
+
+## Considerations for Using the Data
+
+### Social Impact
+
+This dataset is intended for:
+- Sports analytics and research
+- Fantasy football decision-making
+- Educational purposes in machine learning and sports statistics
+
+**Not intended for:**
+- Real-money gambling (use responsibly)
+- Player evaluation for contract negotiations
+- Any decision-making that could impact player careers
+
+### Discussion of Biases
+
+- **Opportunity bias**: Statistics heavily dependent on team offensive scheme and QB quality
+- **Injury data**: Dataset does not account for injuries that may affect performance
+- **Sample size**: Players with limited playing time have less reliable statistics
+- **Game script**: Performance metrics influenced by whether team is winning/losing
+- **Strength of schedule**: Not all defensive matchups are equal, though some adjustment is included
+
+### Limitations
+
+- **Historical data only**: Does not predict future performance definitively
+- **Missing context**: Does not include play design, route running, or other qualitative factors
+- **Weather parsing**: Temperature/wind/humidity may be missing or inaccurate for some games
+- **Roster changes**: Does not account for mid-season team changes or trades
+- **Playoff games**: May or may not include playoff data depending on the year
+
+## Additional Information
+
+### Acknowledgments
+
+- **Data Source**: [nflverse/nflverse-data](https://github.com/nflverse/nflverse-data/releases/tag/pbp)
+- **AI Assistance**: Code development assisted by Claude (Anthropic)
+- **Course**: CMU 24-679: Designing and Deploying AI/ML Systems