```json { "slots": [ { "scope": "dataset", "slot": "nature", "value": { "nature": "observational" }, "evidence": { "reasoning": "This dataset records outcomes of Indian Premier League cricket matches from 2008-2026. The matches are sporting events that occur independently of any data collection process. The dataset observes and measures what happened in each match (scores, winners, officials) but does not control or operate the matches themselves." } }, { "scope": "dataset", "slot": "decisions_served", "value": { "decisions": [ "Which teams to draft or trade players with based on historical performance patterns", "Which venues or cities to schedule matches in based on historical attendance or outcomes", "Whether toss decisions (bat/field) correlate with winning for strategic planning", "Which players to award man-of-the-match honors to based on performance benchmarks", "How to allocate umpiring assignments based on match importance and official experience" ] }, "evidence": { "reasoning": "The dataset contains complete match records including team performance (runs, wickets), match outcomes, player awards, and officiating details. These support decisions about team strategy, tournament operations, player recognition, and resource allocation in cricket league management." } }, { "scope": "dataset", "slot": "levers", "value": { "levers": [] }, "evidence": { "reasoning": "This is observational sports data. No operator controls match outcomes, scores, or which team wins. The toss_decision is made by team captains, not data users. Officials (umpires, referees) are assigned but their presence doesn't change the fundamental match outcomes being measured. The data records what happened, not what was controlled." } }, { "scope": "dataset", "slot": "audience", "value": { "audience": [ "Cricket league administrators and tournament organizers", "Team management and coaching staff", "Sports analysts and statisticians", "Broadcasting and media personnel", "Fantasy cricket platform operators", "Sports betting analysts" ] }, "evidence": { "reasoning": "The comprehensive match data (teams, scores, venues, officials, outcomes) serves multiple stakeholders in the cricket ecosystem: administrators plan tournaments, teams analyze performance, analysts generate insights, media covers events, and fantasy/betting platforms use historical patterns." } }, { "scope": "table:IPL_Matches_Data_2008_2026", "slot": "role", "value": { "role": "fact" }, "evidence": { "reasoning": "The derived slot correctly identifies this as a fact table. It records measurable events (matches) with metrics (runs, wickets, win margins) and references to dimensions (teams, venues, officials, dates). Each row represents one match occurrence with its outcomes." } }, { "scope": "table:IPL_Matches_Data_2008_2026", "slot": "grain", "value": { "unit": "one row per IPL cricket match played", "key_columns": ["season", "match_number", "date"] }, "evidence": { "reasoning": "The classifier_primary_key identifies season+match_number as the composite key. The 'date' column has 947 unique values across 1243 rows (76% unique) and is tagged as primary_key, suggesting matches can occur on the same date. Together these columns uniquely identify each match within a season's sequence." } }, { "scope": "table:IPL_Matches_Data_2008_2026", "slot": "temporal_posture", "value": { "posture": "as-of snapshot with event time", "columns": ["date", "season", "_ingestion_timestamp"] }, "evidence": { "reasoning": "Each row captures a match as it occurred at a specific date (event time). The 'season' provides temporal context for the tournament year. The '_ingestion_timestamp' shows when this snapshot was loaded (2026-09-24), indicating this is a historical dataset captured at a point in time, not a continuously updating stream." } }, { "scope": "table:IPL_Matches_Data_2008_2026", "slot": "column_bindings", "value": { "bindings": [ {"column": "season", "binding": "temporal"}, {"column": "match_number", "binding": "identifier"}, {"column": "date", "binding": "temporal"}, {"column": "city", "binding": "category"}, {"column": "venue", "binding": "category"}, {"column": "team1", "binding": "category"}, {"column": "team2", "binding": "category"}, {"column": "toss_winner", "binding": "category"}, {"column": "toss_decision", "binding": "category"}, {"column": "team1_runs", "binding": "measure"}, {"column": "team1_wickets", "binding": "measure"}, {"column": "team2_runs", "binding": "measure"}, {"column": "team2_wickets", "binding": "measure"}, {"column": "winner", "binding": "category"}, {"column": "result_type", "binding": "category"}, {"column": "win_by_runs", "binding": "measure"}, {"column": "win_by_wickets", "binding": "measure"}, {"column": "player_of_match", "binding": "category"}, {"column": "match_referee", "binding": "category"}, {"column": "umpire1", "binding": "category"}, {"column": "umpire2", "binding": "category"}, {"column": "tv_umpire", "binding": "category"}, {"column": "reserve_umpire", "binding": "category"}, {"column": "team1_players", "binding": "identifier"}, {"column": "team2_players", "binding": "identifier"}, {"column": "_ingestion_timestamp", "binding": "temporal"} ] }, "evidence": { "reasoning": "Refined from derived bindings: match_number is better understood as an identifier (sequence number within season) rather than a measure. The constant-value columns (event_name, match_type, overs_limit, balls_per_over, gender, team_type) are metadata describing the dataset scope, not analytical dimensions, so excluded. Batch/source columns are technical lineage, not analytical bindings." } }, { "scope": "table:IPL_Matches_Data_2008_2026", "slot": "derived_measures", "value": { "measures": [ { "column": "win_by_runs", "derived_from": ["team1_runs", "team2_runs", "winner"], "rule": "When team batting first wins: their runs minus opponent's runs; otherwise 0" }, { "column": "win_by_wickets", "derived_from": ["team2_wickets", "winner"], "rule": "When team batting second wins: 10 minus wickets they lost; otherwise 0" } ] }, "evidence": { "reasoning": "In cricket, a match is won either by runs (team batting first scores more) or by wickets (team batting second reaches target with wickets remaining). The exponential distribution of both win_by columns and their mutual exclusivity (one is always 0 when the other isn't) indicates they are calculated outcomes, not independently measured." } } ] } ```