python案例统计犯规战术阻止反击几次？

wen python案例 2026-08-19 152

本文目录导读：

场景设定
代码实现
功能说明
使用建议

我来为你设计一个Python案例,用于统计比赛中犯规战术阻止反击的次数。

场景设定

假设我们有一个足球比赛的数据流，包含比赛中的事件，我们需要识别"犯规战术阻止反击"的情况。

代码实现

import pandas as pd
from datetime import datetime, timedelta
import random
class CounterAttackAnalyzer:
    def __init__(self):
        # 犯规战术特征阈值
        self.time_threshold = 30  # 秒，距反击开始的时间窗口
        self.field_position_weight = 0.3  # 场地位置权重
        self.time_weight = 0.4  # 时间权重
        self.situation_weight = 0.3  # 比赛情况权重
    def calculate_tactical_foul_score(self, event, game_context):
        """
        计算犯规战术的可能性得分
        """
        score = 0
        # 1. 时间因素：犯规发生在反击开始后多久
        if event['time_since_counter'] <= self.time_threshold:
            time_score = 1 - (event['time_since_counter'] / self.time_threshold)
            score += time_score * self.time_weight
        # 2. 场地位置因素
        if 'attack_zone' in event:
            if event['attack_zone'] in ['final_third', 'middle_third_adv']:
                score += (1 - event['distance_to_goal'] / 100) * self.field_position_weight
        # 3. 比赛情况因素
        if event['was_possession_gaining']:  # 是否阻止了得分机会
            score += self.situation_weight * 0.7
        elif event['was_dangerous_attack']:  # 是否是危险进攻
            score += self.situation_weight * 0.9
        # 4. 犯规严重程度
        if event['foul_type'] == 'professional_foul':
            score += 0.5
        elif event['foul_type'] == 'stopping_counter':
            score += 0.8
        return min(score, 1.0)  # 确保不超过1
    def is_counter_attack_foul(self, event, game_context):
        """
        判断是否为犯规战术阻止反击
        """
        # 基本条件检查
        if not event['is_foul']:
            return False
        # 检查是否在反击过程中
        if not event['in_counter_attack']:
            return False
        # 计算犯规战术得分
        foul_score = self.calculate_tactical_foul_score(event, game_context)
        # 判断是否为战术犯规
        return foul_score >= 0.6  # 阈值设定
    def analyze_match(self, events_data):
        """
        分析整场比赛中的犯规战术阻止反击次数
        """
        counter_attack_fouls = []
        normal_fouls = []
        # 构建比赛上下文
        game_context = self._build_game_context(events_data)
        for event in events_data:
            if event['is_foul']:
                if self.is_counter_attack_foul(event, game_context):
                    counter_attack_fouls.append(event)
                    # 如果阻止了明显得分机会，可能加罚
                    if event['blocked_clear_chance']:
                        event['additional_punishment'] = True
                else:
                    normal_fouls.append(event)
        return {
            'total_fouls': len(events_data[events_data['is_foul']]),
            'counter_attack_fouls': len(counter_attack_fouls),
            'normal_fouls': len(normal_fouls),
            'blocked_clear_chances': sum(1 for e in counter_attack_fouls if e['blocked_clear_chance']),
            'details': counter_attack_fouls
        }
    def _build_game_context(self, events):
        """构建比赛上下文"""
        context = {
            'score_difference': events.iloc[-1]['home_score'] - events.iloc[-1]['away_score'],
            'home_team': events.iloc[0]['home_team'],
            'away_team': events.iloc[0]['away_team'],
            'match_time': events.iloc[-1]['game_time']
        }
        # 分析比赛阶段
        if context['match_time'] < 45:
            context['match_stage'] = 'first_half'
        elif context['match_time'] < 90:
            context['match_stage'] = 'second_half'
        else:
            context['match_stage'] = 'extra_time'
        return context
    def visualize_analysis(self, analysis_result):
        """可视化分析结果"""
        import matplotlib.pyplot as plt
        labels = ['战术犯规', '普通犯规']
        sizes = [analysis_result['counter_attack_fouls'], 
                analysis_result['normal_fouls']]
        colors = ['#FF6B6B', '#4ECDC4']
        plt.figure(figsize=(10, 6))
        plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', 
                startangle=90, explode=(0.05, 0))
        plt.title(f'犯规类型分布 - {analysis_result.get("match", "比赛")}')
        plt.axis('equal')
        plt.show()
        # 打印摘要
        print("="*50)
        print("犯规战术阻止反击分析报告")
        print("="*50)
        print(f"总犯规次数: {analysis_result['total_fouls']}")
        print(f"战术犯规阻止反击: {analysis_result['counter_attack_fouls']}次")
        print(f"  其中阻止明显得分机会: {analysis_result['blocked_clear_chances']}次")
        print(f"普通犯规: {analysis_result['normal_fouls']}次")
# 示例数据生成器
def generate_sample_match_events():
    """生成模拟比赛数据"""
    events = []
    match_time = []
    # 模拟90分钟的比赛事件
    for minute in range(1, 91):
        # 每2-5分钟可能有一次事件
        if random.random() < 0.3:
            event = {
                'minute': minute,
                'is_foul': False,
                'in_counter_attack': False,
                'time_since_counter': 0,
                'attack_zone': 'defensive_third',
                'distance_to_goal': random.randint(0, 100),
                'was_possession_gaining': False,
                'was_dangerous_attack': False,
                'foul_type': 'none',
                'blocked_clear_chance': False,
                'home_score': random.randint(0, 1),
                'away_score': random.randint(0, 1)
            }
            # 随机生成事件类型
            event_type = random.random()
            if event_type < 0.15:  # 15%概率为犯规
                event['is_foul'] = True
                event['foul_type'] = random.choice(['regular', 'professional_foul', 'stopping_counter'])
                event['in_counter_attack'] = random.random() < 0.4
                if event['in_counter_attack']:
                    event['time_since_counter'] = random.randint(1, 30)
                    event['attack_zone'] = random.choice(['middle_third_adv', 'final_third'])
                    event['was_dangerous_attack'] = random.random() < 0.5
                    event['was_possession_gaining'] = random.random() < 0.4
                    event['blocked_clear_chance'] = random.random() < 0.3
            elif event_type < 0.25:  # 10%概率为射门
                event['attack_zone'] = 'final_third'
                event['was_dangerous_attack'] = True
            # 更新比分
            if random.random() < 0.01:  # 1%概率进球
                if random.random() < 0.5:
                    event['home_score'] += 1
                else:
                    event['away_score'] += 1
            events.append(event)
    return events
# 主程序
def main():
    # 生成模拟数据
    print("生成模拟比赛数据...")
    match_events = generate_sample_match_events()
    # 转换为DataFrame
    import pandas as pd
    df = pd.DataFrame(match_events)
    # 创建分析器
    analyzer = CounterAttackAnalyzer()
    # 进行比赛分析
    print("开始分析比赛...")
    result = analyzer.analyze_match(df)
    # 输出结果
    analyzer.visualize_analysis(result)
    # 详细输出
    print("\n战术犯规详情：")
    for i, foul in enumerate(result['details'], 1):
        if 'additional_punishment' in foul and foul['additional_punishment']:
            punishment_note = " [可能加罚]"
        else:
            punishment_note = ""
        print(f"{i}. 第{foul['minute']}分钟 - 犯规类型: {foul['foul_type']}"
              f" - 位置: {foul['attack_zone']}"
              f" - 时间窗口: {foul['time_since_counter']}秒"
              f"{punishment_note}")
    return result
if __name__ == "__main__":
    result = main()