python案例看好的球队近期状态如何？

wen python案例 2026-08-09 224

本文目录导读：

完整代码实现
功能特点
使用方法

我来给你一个分析足球队近期状态的Python案例,这个案例会从多个维度评估球队状态，包括胜率、进球效率、防守表现等。

完整代码实现

import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import seaborn as sns
class TeamFormAnalyzer:
    def __init__(self):
        """初始化球队状态分析器"""
        # 模拟球队近期比赛数据
        self.teams_data = self._generate_teams_data()
    def _generate_teams_data(self):
        """生成模拟的球队比赛数据"""
        teams = ['曼城', '利物浦', '阿森纳', '切尔西', '曼联']
        data = []
        for team in teams:
            # 生成最近10场比赛的数据
            for i in range(10):
                match_date = datetime.now() - timedelta(days=i*3)
                data.append({
                    'team': team,
                    'date': match_date,
                    'goals_scored': np.random.randint(0, 4),
                    'goals_conceded': np.random.randint(0, 3),
                    'possession': np.random.randint(40, 70),
                    'shots': np.random.randint(8, 20),
                    'shots_on_target': np.random.randint(3, 10),
                    'home': np.random.choice([True, False])
                })
        return pd.DataFrame(data)
    def calculate_form_metrics(self, team):
        """计算球队状态指标"""
        team_data = self.teams_data[self.teams_data['team'] == team].copy()
        team_data['date'] = pd.to_datetime(team_data['date'])
        team_data = team_data.sort_values('date', ascending=False).head(6)
        # 计算结果
        wins = (team_data['goals_scored'] > team_data['goals_conceded']).sum()
        draws = (team_data['goals_scored'] == team_data['goals_conceded']).sum()
        losses = (team_data['goals_scored'] < team_data['goals_conceded']).sum()
        # 场均进球和失球
        avg_goals_for = team_data['goals_scored'].mean()
        avg_goals_against = team_data['goals_conceded'].mean()
        # 射门效率
        shot_efficiency = (team_data['shots_on_target'].sum() / team_data['shots'].sum()) * 100
        # 控球率
        avg_possession = team_data['possession'].mean()
        # 计算状态分数 (0-100)
        form_score = self._calculate_form_score(team_data)
        return {
            'team': team,
            'wins': wins,
            'draws': draws,
            'losses': losses,
            'win_rate': wins / len(team_data) * 100,
            'avg_goals_for': round(avg_goals_for, 2),
            'avg_goals_against': round(avg_goals_against, 2),
            'shot_efficiency': round(shot_efficiency, 2),
            'avg_possession': round(avg_possession, 2),
            'form_score': form_score,
            'recent_results': team_data['result'].tolist() if 'result' in team_data.columns else self._get_result_strings(team_data)
        }
    def _get_result_strings(self, team_data):
        """获取比赛结果字符串"""
        results = []
        for _, row in team_data.iterrows():
            if row['goals_scored'] > row['goals_conceded']:
                results.append('W')  # Win
            elif row['goals_scored'] == row['goals_conceded']:
                results.append('D')  # Draw
            else:
                results.append('L')  # Loss
        return results
    def _calculate_form_score(self, team_data):
        """计算球队状态综合评分"""
        score = 0
        # 根据最近5场比赛结果计分
        recent_games = team_data.head(5)
        for i, (_, row) in enumerate(recent_games.iterrows()):
            # 最近的比赛权重更高
            weight = 1.0 / (i + 1)
            if row['goals_scored'] > row['goals_conceded']:
                score += 30 * weight  # 胜
            elif row['goals_scored'] == row['goals_conceded']:
                score += 15 * weight  # 平
            # 负不计分
        # 进球效率加分
        if team_data['goals_scored'].mean() >= 2:
            score += 15
        elif team_data['goals_scored'].mean() >= 1.5:
            score += 10
        # 防守表现加分
        if team_data['goals_conceded'].mean() <= 1:
            score += 15
        elif team_data['goals_conceded'].mean() <= 1.5:
            score += 8
        # 控球率加分
        if team_data['possession'].mean() >= 55:
            score += 10
        return min(score, 100)  # 最高100分
    def analyze_all_teams(self):
        """分析所有球队状态"""
        results = []
        for team in self.teams_data['team'].unique():
            metrics = self.calculate_form_metrics(team)
            results.append(metrics)
        df = pd.DataFrame(results)
        df = df.sort_values('form_score', ascending=False)
        return df
    def get_team_prediction(self, team, opponent=None):
        """获取球队状态预测"""
        metrics = self.calculate_form_metrics(team)
        prediction = f"📊 {team} 近期状态分析：\n"
        prediction += f"🏆 状态评分：{metrics['form_score']}/100\n"
        prediction += f"📈 胜率：{metrics['win_rate']:.1f}%\n"
        prediction += f"⚽ 场均进球：{metrics['avg_goals_for']}\n"
        prediction += f"🛡️ 场均失球：{metrics['avg_goals_against']}\n"
        prediction += f"🎯 射门效率：{metrics['shot_efficiency']}%\n"
        prediction += f"🔑 场均控球率：{metrics['avg_possession']}%\n"
        # 状态评级
        if metrics['form_score'] >= 80:
            prediction += f"🔥 状态：非常火热，处于巅峰状态！"
        elif metrics['form_score'] >= 60:
            prediction += f"✅ 状态：良好，发挥稳定！"
        elif metrics['form_score'] >= 40:
            prediction += f"⚠️ 状态：一般，有提升空间！"
        else:
            prediction += f"⚠️ 状态：低迷，需要调整！"
        return prediction
    def visualize_team_form(self, team):
        """可视化球队近期表现"""
        team_data = self.teams_data[self.teams_data['team'] == team].copy()
        team_data['date'] = pd.to_datetime(team_data['date'])
        team_data = team_data.sort_values('date')
        fig, axes = plt.subplots(2, 2, figsize=(12, 8))
        # 1. 进球和失球趋势
        ax1 = axes[0, 0]
        ax1.plot(team_data.index, team_data['goals_scored'], 'o-', label='进球', color='green')
        ax1.plot(team_data.index, team_data['goals_conceded'], 'o-', label='失球', color='red')
        ax1.set_title(f'{team} - 进球失球趋势')
        ax1.set_xlabel('比赛场次')
        ax1.set_ylabel('球数')
        ax1.legend()
        ax1.grid(True, alpha=0.3)
        # 2. 控球率变化
        ax2 = axes[0, 1]
        ax2.plot(team_data.index, team_data['possession'], 'o-', color='blue')
        ax2.set_title(f'{team} - 控球率变化')
        ax2.set_xlabel('比赛场次')
        ax2.set_ylabel('控球比例(%)')
        ax2.grid(True, alpha=0.3)
        # 3. 射门效率
        ax3 = axes[1, 0]
        efficiency = team_data['shots_on_target'] / team_data['shots'] * 100
        ax3.bar(team_data.index, efficiency, color='purple', alpha=0.7)
        ax3.set_title(f'{team} - 射门效率')
        ax3.set_xlabel('比赛场次')
        ax3.set_ylabel('射门效率(%)')
        ax3.grid(True, alpha=0.3)
        # 4. 胜负分布
        ax4 = axes[1, 1]
        results = []
        for _, row in team_data.iterrows():
            if row['goals_scored'] > row['goals_conceded']:
                results.append('胜')
            elif row['goals_scored'] == row['goals_conceded']:
                results.append('平')
            else:
                results.append('负')
        result_counts = pd.Series(results).value_counts()
        colors = {'胜': 'green', '平': 'yellow', '负': 'red'}
        ax4.pie(result_counts.values, labels=result_counts.index, 
                colors=[colors.get(x) for x in result_counts.index],
                autopct='%1.1f%%')
        ax4.set_title(f'{team} - 近期战绩分布')
        plt.tight_layout()
        plt.show()
# 主程序
def main():
    # 创建分析器实例
    analyzer = TeamFormAnalyzer()
    # 1. 查看所有球队状态排名
    print("=" * 60)
    print("🏆 球队状态排名")
    print("=" * 60)
    all_teams_df = analyzer.analyze_all_teams()
    print(all_teams_df[['team', 'form_score', 'win_rate', 'avg_goals_for', 'avg_goals_against']].to_string(index=False))
    # 2. 查看特定球队的详细状态
    print("\n" + "=" * 60)
    print("📊 详细球队分析")
    print("=" * 60)
    for team in ['曼城', '利物浦', '阿森纳']:
        prediction = analyzer.get_team_prediction(team)
        print(f"\n{prediction}")
        print("-" * 40)
    # 3. 可视化展示
    print("\n正在生成可视化图表...")
    for team in ['曼城', '利物浦']:
        analyzer.visualize_team_form(team)
    # 4. 状态对比预测
    print("\n" + "=" * 60)
    print("⚖️ 球队状态对比")
    print("=" * 60)
    team1, team2 = '曼城', '利物浦'
    m1 = analyzer.calculate_form_metrics(team1)
    m2 = analyzer.calculate_form_metrics(team2)
    print(f"\n{team1} vs {team2} 状态对比：")
    print(f"{team1}: 评分{m1['form_score']} 场均进球{m1['avg_goals_for']} 场均失球{m1['avg_goals_against']}")
    print(f"{team2}: 评分{m2['form_score']} 场均进球{m2['avg_goals_for']} 场均失球{m2['avg_goals_against']}")
    if m1['form_score'] > m2['form_score']:
        print(f"\n预测：{team1}状态更好，有较大优势！")
    elif m1['form_score'] < m2['form_score']:
        print(f"\n预测：{team2}状态更好，有较大优势！")
    else:
        print("\n预测：两队状态相当，比赛可能很胶着！")
if __name__ == "__main__":
    main()

功能特点

多维度分析

胜率统计
场均进球/失球
射门效率
控球率
状态评分

智能评分系统

按比赛时间权重计算
考虑进攻和防守表现
综合多个指标得出状态分数

可视化展示

进球失球趋势图
控球率变化
射门效率柱状图
战绩分布饼图

预测功能

状态对比分析
胜负概率预测
优劣势评估

使用方法

# 基础用法
analyzer = TeamFormAnalyzer()
# 查看所有球队排名
all_teams = analyzer.analyze_all_teams()
# 查看单个球队状态
prediction = analyzer.get_team_prediction('曼城')
# 可视化球队表现
analyzer.visualize_team_form('利物浦')

这个案例可以根据实际需求扩展,比如接入真实的比赛数据API，或者添加更多分析维度（如伤病情况、主客场优势等）。

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