Athlete Performance Profile Analysis

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(741)

# Athlete performance metrics
n_athletes = 120

speed = np.random.normal(28, 3, n_athletes)  # km/h
endurance = np.random.normal(70, 15, n_athletes)  # VO2max
strength = np.random.normal(150, 30, n_athletes)  # kg

# Position classification
positions = np.random.choice(['Forward', 'Midfielder', 'Defender', 'Goalkeeper'], n_athletes)
pos_colors = {'Forward': '#F5276C', 'Midfielder': '#27D3F5', 'Defender': '#6CF527', 'Goalkeeper': '#F5B027'}
colors = [pos_colors[p] for p in positions]

fig = plt.figure(figsize=(10, 8), facecolor='#ffffff')
ax = fig.add_subplot(111, projection='3d', facecolor='#ffffff')

ax.scatter(speed, endurance, strength, c=colors, s=60, 
           alpha=0.7, edgecolors='#374151', linewidths=0.3)

ax.set_xlabel('Speed (km/h)', color='#1f2937', fontsize=10)
ax.set_ylabel('Endurance (VO₂max)', color='#1f2937', fontsize=10)
ax.set_zlabel('Strength (kg)', color='#1f2937', fontsize=10)
ax.set_title('Athlete Performance Profile Analysis', color='#1f2937', fontsize=14, fontweight='bold', pad=20)

ax.tick_params(colors='#6b7280', labelsize=8)
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor('#e5e7eb')
ax.yaxis.pane.set_edgecolor('#e5e7eb')
ax.zaxis.pane.set_edgecolor('#e5e7eb')

ax.view_init(elev=20, azim=45)
plt.tight_layout()
plt.show()