Corner Kicks and Free Kicks Analysis

# Overview Evaluate set-piece effectiveness through statistical analysis of corner kicks, free kicks, and scoring patterns. ## Python Implementation ```python import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt # Load set-piece data set_pieces = pd.read_csv('set_pieces.csv') # Analyze corner kick outcomes corner_analysis = set_pieces[set_pieces['type'] == 'corner'].groupby('delivery_zone').agg({ 'shot_created': 'sum', 'goal': 'sum', 'event_id': 'count' }).rename(columns={'event_id': 'total_corners'}) corner_analysis['conversion_rate'] = (corner_analysis['goal'] / corner_analysis['total_corners']) * 100 corner_analysis['shot_rate'] = (corner_analysis['shot_created'] / corner_analysis['total_corners']) * 100 print("Corner Kick Analysis by Delivery Zone:") print(corner_analysis) # Free kick distance vs success rate free_kicks = set_pieces[set_pieces['type'] == 'free_kick'] free_kicks['distance_bin'] = pd.cut(free_kicks['distance'], bins=[0, 20, 25, 30, 35, 50], labels=['0-20m', '20-25m', '25-30m', '30-35m', '35m+']) fk_success = free_kicks.groupby('distance_bin').agg({ 'on_target': 'sum', 'goal': 'sum', 'event_id': 'count' }).rename(columns={'event_id': 'total_attempts'}) fk_success['accuracy_rate'] = (fk_success['on_target'] / fk_success['total_attempts']) * 100 fk_success['conversion_rate'] = (fk_success['goal'] / fk_success['total_attempts']) * 100 # Visualize plt.figure(figsize=(10, 6)) fk_success[['accuracy_rate', 'conversion_rate']].plot(kind='bar') plt.title('Free Kick Performance by Distance') plt.ylabel('Percentage (%)') plt.xlabel('Distance Range') plt.legend(['Accuracy Rate', 'Conversion Rate']) plt.xticks(rotation=45) plt.tight_layout() plt.show() ``` ## R Implementation ```r library(dplyr) library(ggplot2) library(tidyr) # Load set-piece data set_pieces <- read.csv("set_pieces.csv") # Corner kick analysis corner_analysis <- set_pieces %>% filter(type == "corner") %>% group_by(delivery_zone) %>% summarise( total_corners = n(), shots_created = sum(shot_created), goals = sum(goal), conversion_rate = (goals / total_corners) * 100, shot_rate = (shots_created / total_corners) * 100, .groups = "drop" ) print("Corner Kick Analysis by Delivery Zone:") print(corner_analysis) # Free kick analysis by distance free_kicks <- set_pieces %>% filter(type == "free_kick") %>% mutate(distance_bin = cut(distance, breaks = c(0, 20, 25, 30, 35, 50), labels = c("0-20m", "20-25m", "25-30m", "30-35m", "35m+"))) fk_success <- free_kicks %>% group_by(distance_bin) %>% summarise( total_attempts = n(), on_target = sum(on_target), goals = sum(goal), accuracy_rate = (on_target / total_attempts) * 100, conversion_rate = (goals / total_attempts) * 100, .groups = "drop" ) # Visualize fk_success %>% select(distance_bin, accuracy_rate, conversion_rate) %>% pivot_longer(cols = c(accuracy_rate, conversion_rate), names_to = "metric", values_to = "percentage") %>% ggplot(aes(x = distance_bin, y = percentage, fill = metric)) + geom_bar(stat = "identity", position = "dodge") + labs( title = "Free Kick Performance by Distance", x = "Distance Range", y = "Percentage (%)" ) + theme_minimal() ```