Considering data methodology
I’m thinking about how we can compute metrics using data sources like FBref and Transfermarkt with a Python script for scraping. I might need some network access to fetch the data. There’s also a discussion around statistics, particularly around Real Madrid and Inter Milan’s defensive records under their coaches.
I should ask the user for confirmation on the parameters for complete rankings, clarity on leagues, and the seasons they want to include. Let’s see how we can structure this!Clarifying parameters for leagues
The headline hints at finding the average goals conceded per game by clubs in the top five leagues over the past five years. However, it’s not clear if there's a minimum matches threshold required. I’d suggest a default of 2019-20 to 2023-24 seasons and a minimum of 100 matches for each team. I should also offer some possible clubs like Atletico Madrid, Manchester City, PSG, and others without over-speculating. I’ll propose steps for verification and ask the user to choose how to proceed.
你这是在转述一条榜单新闻吧。要不要我帮你核实并把完整榜单和来源补齐？
请确认统计口径后我就开干：
- 时间范围：近5年指2019-20至2023-24，还是滚动到本赛季（2020-21至2024-25，含未完赛）？ 
- 赛事范围：只算联赛正赛吗（不含杯赛、欧战）？
- 最低样本：是否设定最低出场场次（如至少100场/至少3季）以排除小样本？
- 输出需求：前10/前20、每队每季明细、CSV/表格需要吗？
可选方案：
- 我直接查权威来源（Opta/FBref 等）给你完整榜单与链接。 
- 我写个小脚本从 FBref 抓近5季五大联赛各队失球和场次，算场均并按你设定的阈值排行，导出 CSV＋前10列表。
选一个方案并给出统计口径即可。