Worldcup — R Package Fjelstul Data-csv

install.packages("worldcup") library(worldcup) If you prefer the directly (from the Fjelstul World Cup Database GitHub repo ), download the data-csv/ folder. 2. Database Schema (Main Tables) The package contains several tibbles. Key ones:

Here’s a for working with the worldcup R package (the Fjelstul World Cup database, usually accessed via the worldcup package or directly from the CSV data). worldcup r package fjelstul data-csv

data("matches") data("goals") data("cards") data("players") Use dplyr for easy manipulation. Example 1: Matches in 2018 World Cup library(dplyr) matches %>% filter(tournament_id == "WC-2018") %>% select(match_id, home_team, away_team, home_score, away_score) Example 2: Top goal scorers (all time) goals %>% group_by(player_id) %>% summarise(total_goals = n(), .groups = "drop") %>% arrange(desc(total_goals)) %>% left_join(players, by = "player_id") %>% select(player_name, total_goals) %>% slice_head(n = 10) Example 3: Most cards in a single match cards %>% group_by(match_id) %>% summarise(total_cards = n()) %>% arrange(desc(total_cards)) %>% left_join(matches, by = "match_id") %>% select(match_id, home_team, away_team, total_cards) Example 4: Goals by minute (including injury time) goals %>% filter(minute_regulation <= 90) %>% group_by(minute_regulation) %>% summarise(goals = n()) %>% arrange(minute_regulation) %>% plot(type = "h", xlab = "Minute", ylab = "Goals", main = "Goals by Minute") 4. Common Analysis Tasks Team performance over time matches %>% group_by(tournament_id, winner) %>% summarise(wins = n(), .groups = "drop") %>% arrange(tournament_id, desc(wins)) Player with most assists in a single tournament goals %>% filter(!is.na(assist_player_id)) %>% group_by(tournament_id, assist_player_id) %>% summarise(assists = n(), .groups = "drop") %>% slice_max(assists, by = tournament_id, n = 1) %>% left_join(players, by = c("assist_player_id" = "player_id")) 5. Working with CSV files directly If you downloaded the CSV files (e.g., from the GitHub repo): install

library(readr) library(dplyr) matches_csv <- read_csv("data-csv/matches.csv") goals_csv <- read_csv("data-csv/goals.csv") players_csv <- read_csv("data-csv/players.csv") Key ones: Here’s a for working with the