python案例统计扑救次数门将谁更忙？

wen python案例 2026-08-07 86
我来为您创建一个统计门将扑救次数的Python案例，看看谁更"忙"。
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
# 创建门将数据
class Goalkeeper:
    def __init__(self, name, team):
        self.name = name
        self.team = team
        self.saves = []  # 每周扑救次数
        self.matches = 0
        self.total_saves = 0
    def add_match_saves(self, saves_count):
        """添加一场比赛的扑救次数"""
        self.saves.append(saves_count)
        self.matches += 1
        self.total_saves += saves_count
    def get_avg_saves(self):
        """获取平均每场扑救次数"""
        if self.matches == 0:
            return 0
        return self.total_saves / self.matches
    def get_max_saves(self):
        """获取单场最高扑救次数"""
        return max(self.saves) if self.saves else 0
    def get_min_saves(self):
        """获取单场最低扑救次数"""
        return min(self.saves) if self.saves else 0
# 创建门将对象并添加数据
def create_goalkeeper_data():
    # 创建门将
    goalkeepers = [
        Goalkeeper("王大雷", "山东泰山"),
        Goalkeeper("颜骏凌", "上海海港"),
        Goalkeeper("刘殿座", "武汉三镇"),
        Goalkeeper("韩佳奇", "北京国安")
    ]
    # 模拟10场比赛的扑救数据
    match_data = {
        "王大雷": [5, 3, 6, 4, 7, 2, 5, 6, 4, 3],
        "颜骏凌": [2, 3, 4, 2, 3, 5, 2, 3, 4, 2],
        "刘殿座": [4, 5, 3, 6, 4, 5, 3, 6, 5, 4],
        "韩佳奇": [6, 7, 5, 8, 6, 7, 5, 6, 7, 8]
    }
    # 为每个门将添加数据
    for gk in goalkeepers:
        if gk.name in match_data:
            for saves in match_data[gk.name]:
                gk.add_match_saves(saves)
    return goalkeepers
# 统计分析函数
def analyze_goalkeepers(goalkeepers):
    """分析门将数据"""
    print("=" * 60)
    print("门将扑救数据统计分析")
    print("=" * 60)
    print("\n【基本统计】")
    print("-" * 40)
    for gk in goalkeepers:
        print(f"\n{gk.name} ({gk.team}):")
        print(f"  出场场次: {gk.matches}场")
        print(f"  总扑救次数: {gk.total_saves}次")
        print(f"  平均每场扑救: {gk.get_avg_saves():.2f}次")
        print(f"  单场最高扑救: {gk.get_max_saves()}次")
        print(f"  单场最低扑救: {gk.get_min_saves()}次")
        print(f"  扑救稳定性: {np.std(gk.saves):.2f}")
# 比较谁更忙
def find_busiest_goalkeeper(goalkeepers):
    """找出最忙的门将"""
    print("\n【谁更忙？】")
    print("-" * 40)
    # 按总扑救次数排序
    by_total = sorted(goalkeepers, key=lambda x: x.total_saves, reverse=True)
    print("按总扑救次数排名:")
    for i, gk in enumerate(by_total, 1):
        print(f"  第{i}名: {gk.name} - {gk.total_saves}次")
    # 按平均扑救次数排序
    by_avg = sorted(goalkeepers, key=lambda x: x.get_avg_saves(), reverse=True)
    print("\n按平均每场扑救排名:")
    for i, gk in enumerate(by_avg, 1):
        print(f"  第{i}名: {gk.name} - {gk.get_avg_saves():.2f}次/场")
    # 找出最忙的门将
    busiest = max(goalkeepers, key=lambda x: x.total_saves)
    busiest_avg = max(goalkeepers, key=lambda x: x.get_avg_saves())
    print(f"\n🏆 总扑救次数最多: {busiest.name} ({busiest.total_saves}次)")
    print(f"🏆 平均每场最忙: {busiest_avg.name} ({busiest_avg.get_avg_saves():.2f}次/场)")
# 可视化分析
def visualize_goalkeepers(goalkeepers):
    """可视化分析"""
    fig, axes = plt.subplots(2, 2, figsize=(12, 10))
    fig.suptitle('门将扑救数据分析', fontsize=16)
    # 1. 总扑救次数柱状图
    ax1 = axes[0, 0]
    names = [gk.name for gk in goalkeepers]
    totals = [gk.total_saves for gk in goalkeepers]
    colors = ['#FF6B6B', '#4ECDC4', '#45B7D1', '#96CEB4']
    bars = ax1.bar(names, totals, color=colors)
    ax1.set_title('总扑救次数')
    ax1.set_xlabel('球员')
    ax1.set_ylabel('次数')
    for bar, total in zip(bars, totals):
        ax1.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.5,
                str(total), ha='center', va='bottom')
    # 2. 平均扑救次数比较
    ax2 = axes[0, 1]
    avgs = [gk.get_avg_saves() for gk in goalkeepers]
    bars = ax2.bar(names, avgs, color=colors)
    ax2.set_title('平均每场扑救次数')
    ax2.set_xlabel('球员')
    ax2.set_ylabel('次数/场')
    for bar, avg in zip(bars, avgs):
        ax2.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.1,
                f'{avg:.2f}', ha='center', va='bottom')
    # 3. 扑救次数走势图
    ax3 = axes[1, 0]
    for gk, color in zip(goalkeepers, colors):
        matches = range(1, gk.matches + 1)
        ax3.plot(matches, gk.saves, marker='o', label=gk.name, color=color)
    ax3.set_title('每场比赛扑救走势')
    ax3.set_xlabel('场次')
    ax3.set_ylabel('扑救次数')
    ax3.legend()
    ax3.grid(True, alpha=0.3)
    # 4. 盒须图（箱线图）
    ax4 = axes[1, 1]
    data = [gk.saves for gk in goalkeepers]
    bp = ax4.boxplot(data, labels=names, patch_artist=True)
    for patch, color in zip(bp['boxes'], colors):
        patch.set_facecolor(color)
        patch.set_alpha(0.7)
    ax4.set_title('扑救次数分布')
    ax4.set_xlabel('球员')
    ax4.set_ylabel('扑救次数')
    plt.tight_layout()
    plt.show()
# 生成详细报告
def generate_report(goalkeepers):
    """生成分析报告"""
    print("\n" + "=" * 60)
    print("📊 详细分析报告")
    print("=" * 60)
    print("\n【球队防守压力分析】")
    print("-" * 40)
    for gk in goalkeepers:
        avg = gk.get_avg_saves()
        if avg >= 6:
            pressure = "极高"
        elif avg >= 4:
            pressure = "较高"
        elif avg >= 3:
            pressure = "中等"
        else:
            pressure = "较低"
        print(f"{gk.team} ({gk.name}): 防守压力{pressure}")
    print("\n【扑救稳定性分析】")
    print("-" * 40)
    stability = []
    for gk in goalkeepers:
        std = np.std(gk.saves)
        if std <= 1.5:
            level = "稳定"
        elif std <= 2.5:
            level = "一般"
        else:
            level = "不稳定"
        stability.append((gk.name, std, level))
        print(f"{gk.name}: 波动{std:.2f}，表现{level}")
    print("\n【最佳表现场次】")
    print("-" * 40)
    all_matches = []
    for gk in goalkeepers:
        max_saves = gk.get_max_saves()
        max_match = gk.saves.index(max_saves) + 1
        all_matches.append((gk.name, max_saves, max_match))
    all_matches.sort(key=lambda x: x[1], reverse=True)
    for name, saves, match in all_matches:
        print(f"{name}: 第{match}场扑救{saves}次")
    print("\n【总评】")
    print("-" * 40)
    busiest_total = max(goalkeepers, key=lambda x: x.total_saves)
    busiest_avg = max(goalkeepers, key=lambda x: x.get_avg_saves())
    if busiest_total == busiest_avg:
        print(f"🏆 最忙门将: {busiest_total.name}（总扑救{busiest_total.total_saves}次，场均{busiest_total.get_avg_saves():.2f}次）")
    else:
        print(f"总扑救最多: {busiest_total.name}")
        print(f"场均最忙: {busiest_avg.name}")
# 主程序
def main():
    # 创建数据
    goalkeepers = create_goalkeeper_data()
    # 分析并输出结果
    analyze_goalkeepers(goalkeepers)
    find_busiest_goalkeeper(goalkeepers)
    generate_report(goalkeepers)
    # 可视化
    print("\n正在生成图表...")
    try:
        visualize_goalkeepers(goalkeepers)
    except:
        print("无法显示图表（请确保已安装matplotlib）")
    # 额外的交互功能
    print("\n【交互功能】")
    print("-" * 40)
    while True:
        print("\n1. 查看单个门将详情")
        print("2. 查看扑救排行")
        print("3. 退出")
        choice = input("请选择: ")
        if choice == "1":
            print("\n可选门将:")
            for i, gk in enumerate(goalkeepers, 1):
                print(f"{i}. {gk.name}")
            try:
                index = int(input("选择序号: ")) - 1
                if 0 <= index < len(goalkeepers):
                    gk = goalkeepers[index]
                    print(f"\n{gk.name} 详细数据:")
                    print(f"  球队: {gk.team}")
                    print(f"  出战场次: {gk.matches}")
                    print(f"  总扑救: {gk.total_saves}")
                    print(f"  场均扑救: {gk.get_avg_saves():.2f}")
                    print(f"  最好表现: {gk.get_max_saves()}次")
                    print(f"  最差表现: {gk.get_min_saves()}次")
                else:
                    print("无效的序号!")
            except:
                print("输入错误!")
        elif choice == "2":
            print("\n🔄 实时排行")
            print("-" * 30)
            ranked = sorted(goalkeepers, key=lambda x: x.total_saves, reverse=True)
            for i, gk in enumerate(ranked, 1):
                medal = {1: "🥇", 2: "🥈", 3: "🥉"}.get(i, "🏅")
                print(f"{medal} {i}. {gk.name}: {gk.total_saves}次")
        elif choice == "3":
            print("感谢使用! 👋")
            break
        else:
            print("无效选择，请重试!")
if __name__ == "__main__":
    main()
这个程序的主要功能：