实用脚本看好的球队近期状态如何？

本文目录导读：

1. 如果你要接真实数据，推荐两种方式
2. 你可以告诉我以下信息，我帮你把脚本改成可直接运行的版本

我理解你想了解“看好球队的近期状态”，但需要先说明：我无法直接访问实时比赛数据或联网查询最新赛果（具体取决于你当前使用的产品是否开启联网搜索），我给你一个可复用的脚本框架，你可以把数据源接进来（football-data.org、API-Football、或你本地的 CSV）,就能自动输出球队近期状态。

下面是一个 Python 示例脚本,功能包括：

• 读取/拉取球队近期比赛数据
• 计算近 N 场战绩（胜平负）
• 计算进球、失球、净胜球
• 计算场均积分
• 输出“状态评级”（火热/稳定/低迷）

import pandas as pd
from datetime import datetime
# ===== 1. 数据输入 =====
# 方式A：本地CSV，列名建议：date, home_team, away_team, home_goals, away_goals
# df = pd.read_csv("matches.csv", parse_dates=["date"])
# 方式B：手动示例数据（替换成你的数据源）
data = [
    {"date": "2025-01-05", "home_team": "TeamA", "away_team": "TeamB", "home_goals": 2, "away_goals": 0},
    {"date": "2025-01-12", "home_team": "TeamC", "away_team": "TeamA", "home_goals": 1, "away_goals": 1},
    {"date": "2025-01-19", "home_team": "TeamA", "away_team": "TeamD", "home_goals": 3, "away_goals": 2},
    {"date": "2025-01-26", "home_team": "TeamE", "away_team": "TeamA", "home_goals": 0, "away_goals": 2},
    {"date": "2025-02-02", "home_team": "TeamA", "away_team": "TeamF", "home_goals": 0, "away_goals": 1},
]
df = pd.DataFrame(data)
df["date"] = pd.to_datetime(df["date"])
# ===== 2. 提取某支球队的近N场 =====
def team_recent_form(df, team, n=5):
    mask = (df["home_team"] == team) | (df["away_team"] == team)
    sub = df[mask].sort_values("date", ascending=False).head(n).copy()
    rows = []
    for _, r in sub.iterrows():
        if r["home_team"] == team:
            gf, ga = r["home_goals"], r["away_goals"]
            venue = "H"
        else:
            gf, ga = r["away_goals"], r["home_goals"]
            venue = "A"
        if gf > ga:
            result, pts = "W", 3
        elif gf == ga:
            result, pts = "D", 1
        else:
            result, pts = "L", 0
        rows.append({"date": r["date"], "venue": venue, "gf": gf, "ga": ga,
                     "result": result, "points": pts})
    form_df = pd.DataFrame(rows).sort_values("date")  # 按时间正序展示
    return form_df
def summarize_form(form_df, team):
    if form_df.empty:
        return f"{team}: 无近期比赛数据"
    wins = (form_df["result"] == "W").sum()
    draws = (form_df["result"] == "D").sum()
    losses = (form_df["result"] == "L").sum()
    gf = form_df["gf"].sum()
    ga = form_df["ga"].sum()
    pts = form_df["points"].sum()
    ppg = pts / len(form_df)
    # 状态评级（可按需调整阈值）
    if ppg >= 2.2:
        rating = "🔥 火热"
    elif ppg >= 1.5:
        rating = "✅ 稳定"
    elif ppg >= 1.0:
        rating = "⚠️ 一般"
    else:
        rating = "❄️ 低迷"
    form_str = "".join(form_df["result"].tolist())  # 如 WWDLW
    return (f"{team} 近{len(form_df)}场: {form_str} | "
            f"{wins}胜{draws}平{losses}负 | "
            f"进{gf}失{ga} 净{gf-ga:+d} | "
            f"场均积分 {ppg:.2f} | 状态: {rating}")
# ===== 3. 使用 =====
teams = ["TeamA"]
for t in teams:
    fdf = team_recent_form(df, t, n=5)
    print(summarize_form(fdf, t))
    print(fdf.to_string(index=False))
    print("-" * 60)

输出示例：

TeamA 近5场: WDLWW | 3胜1平1负 | 进8失4 净+4 | 场均积分 2.00 | 状态: ✅ 稳定

如果你要接真实数据，推荐两种方式

1. API-Football（RapidAPI）：有免费额度，可拉取球队近期赛果
2. football-data.org：免费层支持五大联赛，结构简单

接 API 时，只需把返回的 JSON 转成上面 df 的列格式（date, home_team, away_team, home_goals, away_goals）,后面的计算完全复用。

你可以告诉我以下信息，我帮你把脚本改成可直接运行的版本

1. 你关注的球队名称和联赛
2. 你是否有 API key（或希望用 CSV 手动导入）
3. 你想看的近 N 场（默认5场）和是否区分主客场
4. 你希望输出的形式（终端打印 / Excel / 图表）

如果你告诉我你用的数据源（或贴几行样例数据），我可以把脚本改成“复制即用”的版本。