Baselight

Dream 11 Fantasy Points Data Of IPL All Seasons

Fantasy Cricket Insights: Dream Teams with Captain Vice-Captain data

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons

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About this Dataset

Dream 11 Fantasy Points Data Of IPL All Seasons

Comprehensive Fantasy Cricket Dataset: Dream Team, Captains, and Vice-Captains

Welcome to this curated dataset designed for fantasy cricket enthusiasts and data scientists alike. Drawing on detailed match records from a variety of sources, this dataset has been meticulously cleaned and enhanced to provide a rich foundation for fantasy cricket analysis and dream team generation.

What's Included:

  1. Match Details: Comprehensive information on all matches, including updated names for teams and stadiums.
  2. Batting Data: Complete batting records, including runs, strike rates, and more.
  3. Bowling Data: Detailed bowling statistics, including wickets, economy rates, and types of dismissals extracted from wicket descriptions.
  4. Fielding Data: Fielding performances including catches, run-outs, and other contributions.
  5. Fantasy Points Calculation: Each player’s performance has been translated into fantasy points based on a detailed scoring system that mirrors popular platforms like Dream11. This includes points for batting, bowling, and fielding.
  6. Dream Teams with Captains and Vice-Captains: The dataset not only lists players but also identifies optimal dream teams for each match, including the captain and vice-captain selections, leveraging statistical analysis and fantasy scoring metrics.

Potential Uses:

  • Fantasy Team Optimization: Ideal for users looking to craft the perfect fantasy lineup.
  • Historical Analysis: Explore trends and performances across seasons.
  • Statistical Modeling: A great resource for predictive modeling and machine learning, aimed at predicting player performances, match outcomes, or optimal team selections.

Dataset Format:

The data is organized into separate CSV files for easy access and manipulation:

  • Match_details.csv for match specifics
  • Batting_data.csv for batting details
  • Bowling_data.csv for bowling figures
  • Fielding_data.csv for fielding performances
  • Final_Fantasy_data.csv for aggregated fantasy scores and team selections

Whether you're a data scientist, a fantasy cricket aficionado, or someone interested in sports analytics, this dataset provides a valuable toolkit for exploring the intricacies of cricket through a fantasy gaming lens.

Tables

Batting Data

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons.batting_data
  • 163.87 kB
  • 15,714 rows
  • 17 columns
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CREATE TABLE batting_data (
  "match_id" BIGINT,
  "season" BIGINT,
  "match_name" VARCHAR,
  "home_team" VARCHAR,
  "away_team" VARCHAR,
  "venue" VARCHAR,
  "bowling_team" VARCHAR,
  "batting_team" VARCHAR,
  "batting_innings" BIGINT,
  "fullname" VARCHAR,
  "batting_position" BIGINT,
  "runs" BIGINT,
  "balls" BIGINT,
  "fours" BIGINT,
  "sixes" BIGINT,
  "strike_rate" DOUBLE,
  "batting_fp" BIGINT
);

Bowling Data

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons.bowling_data
  • 183.74 kB
  • 12,111 rows
  • 27 columns
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CREATE TABLE bowling_data (
  "season" BIGINT,
  "match_id" BIGINT,
  "match_name" VARCHAR,
  "home_team" VARCHAR,
  "away_team" VARCHAR,
  "batting_team" VARCHAR,
  "bowling_team" VARCHAR,
  "venue" VARCHAR,
  "bowling_innings" BIGINT,
  "fullname" VARCHAR,
  "overs" DOUBLE,
  "total_balls" BIGINT,
  "dots" BIGINT,
  "maidens" BIGINT,
  "conceded" BIGINT,
  "foursconceded" BIGINT,
  "sixesconceded" BIGINT,
  "wickets" BIGINT,
  "economyrate" DOUBLE,
  "wides" BIGINT,
  "noballs" BIGINT,
  "lbw" BIGINT,
  "hitwicket" BIGINT,
  "caughtbowled" BIGINT,
  "bowled" BIGINT,
  "overs_bowled" VARCHAR,
  "bowling_fp" BIGINT
);

Fielding Data

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons.fielding_data
  • 69.15 kB
  • 7,272 rows
  • 15 columns
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CREATE TABLE fielding_data (
  "season" BIGINT,
  "match_id" BIGINT,
  "match_name" VARCHAR,
  "home_team" VARCHAR,
  "away_team" VARCHAR,
  "venue" VARCHAR,
  "batting_team" VARCHAR,
  "bowling_innings" BIGINT,
  "bowling_team" VARCHAR,
  "fullname" VARCHAR,
  "catching_fp" BIGINT,
  "stumping_fp" BIGINT,
  "direct_runout_fp" BIGINT,
  "indirect_runout_fp" BIGINT,
  "fielding_fp" BIGINT
);

Final Fantasy Data

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons.final_fantasy_data
  • 147.74 kB
  • 22,362 rows
  • 17 columns
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CREATE TABLE final_fantasy_data (
  "season" BIGINT,
  "match_id" BIGINT,
  "match_name" VARCHAR,
  "home_team" VARCHAR,
  "away_team" VARCHAR,
  "venue" VARCHAR,
  "batting_innings" BIGINT,
  "bowling_innings" BIGINT,
  "fullname" VARCHAR,
  "starting_11" BIGINT,
  "batting_fp" BIGINT,
  "bowling_fp" BIGINT,
  "fielding_fp" BIGINT,
  "total_fp" BIGINT,
  "dream_team" BIGINT,
  "captain" BIGINT,
  "vice_captain" BIGINT
);

Match Details

@kaggle.sukhdayaldhanday_dream_11_fantasy_points_of_ipl_all_seasons.match_details
  • 15.07 kB
  • 1,024 rows
  • 6 columns
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CREATE TABLE match_details (
  "match_id" BIGINT,
  "season" BIGINT,
  "match_name" VARCHAR,
  "venue" VARCHAR,
  "home_team" VARCHAR,
  "away_team" VARCHAR
);

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