世界第一足球联赛:英超上座分析(世界顶级联赛英超上座率解析)
2026-01-14
Analyzing Premier League Attendance
I suspect the user wants an analysis on Premier League attendances since they wrote in Chinese about it. I’m considering various aspects, like attendance trends, average attendance by club, and capacities. It might not be necessary to fetch data since I can provide an overview. This includes comparisons with other leagues, recent developments like stadium expansions, and even ticket pricing. I should remember the knowledge cutoff is October 2024, which affects my data accuracy.Planning a Stadium Analysis
I’m considering Everton's new stadium, expected for 2025-26, and how I could include that in my analysis. I might outline metrics like Premier League average attendance, which was around 40,234 in 2022-23, and compare it with Bundesliga and La Liga. I want to mention occupancy rates and sell-out statistics, along with specific waitlists for clubs like Arsenal and Tottenham. The user seems to prefer an article format with bullet points, so I'll keep it concise and informative while highlighting key insights and metrics.Developing a Data-Backed Analysis
I’m thinking of how to approach this user's request for a data-backed analysis on the Premier League. I might suggest framing it by explaining why it's considered the world's top league. I could outline core metrics like average attendance, occupancy rates, and ticket pricing. Comparing trends over the last decade, noting stadium expansions and the impact of the pandemic, would also be crucial. I should include a proposal for graphs and charts. Plus, I can offer to scrape data for seasons from 2014 to 2024, if approved for network access.Planning for Network Use
In my environment, network access is enabled by default, but I need to be careful about getting user approval before proceeding. I should suggest next steps and see if the user wants a reproducible dataset. It’s important to be concise and structured while presenting insights, including approximate numbers with caution disclaimers. I’ll use the term "约" for approximations. I want to ensure I'm clear and avoid making claims that I’m uncertain about, so I’ll proceed thoughtfully.
英超上座分析(概览)
核心结论:英超并非“场均人数最高”的联赛(德甲通常更高),但在上座率(接近满座)、全球化需求、票价水平与产能紧张度的综合维度上长期领跑,且商业变现(每座位产出)显著高于同侪。
关键指标(近年常态,赛季间略有波动)

结构性驱动
俱乐部分层(容量×需求×占用)
与德甲/西甲对比
赛季内在英超的典型波动

建议监测的分析图表/指标
数据来源与可复现性
要不要我帮你拉一份近10季英超逐场上座数据(含容量、上座率、对阵、时段),输出成一个可复现的 notebook 和 CSV,并给出几张核心图?如果可以,我会: