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爱游戏

本赛季当艾顿作为最近防守人时，对手命中率下降12.9%（本季艾顿作为最近防守者时，对手命中率被压低12.9%）

or

Clarifying response options

I need to make sure the user knows I'm here to help. Since they posted a statement, I could ask if they want me to verify the stat, provide a source, or create a visualization. It would be helpful to provide quick context about opponent FG% differential per NBA tracking, noting that values can fluctuate based on the season or sample size. I might ask if they want to check the data using NBA.com or StatMuse, or even show how to fetch it with nba_api in Python.Clarifying data requests

I want to be sure I understand what the user needs. Should I verify the data, find a source, or create a comparison? It’s good to note that the metric is about the differential FG% when opponents are closely defended, and that 12.9% is quite significant, possibly affected by sample size and matchups. If they want verification, I can quickly check and need to know the specific season and minimum shot attempts. I can also provide a Python code snippet using nba_api that shows how to retrieve this data.Verifying metrics for clarity

I need to check the details on nba.com. The defensive dashboard shows "Diff%" as "FG% - DFG%", meaning that positive numbers indicate the defender held opponents below their average by that amount. Some may describe it as "opponent FG% decreased by 12.9 percentage points," which is correct. I can offer to provide the current value for this season but also note that single-game samples can create extreme values. It may be helpful to filter for a minimum of 200 defended shot attempts for reliability. Let’s outline this clearly!

你是想让我核实这个数据、给出处，还是做个对比/可视化？

简单说明：

  • 这指的是NBA追踪数据里的“最近防守人时的对手命中率差值（Diff FG%）”，通常为对手平时FG%减去被他防时的DFG%，数值越大说明干扰越好。12.9个百分点非常高，容易受样本量影响。
  • 建议限定赛季和样本阈值（如总被防出手≥200）再看更稳的数。

ren

我可以立即帮你查。请确认：

  • 赛季：2024-25 还是 2023-24（常规赛/季后赛）？
  • 是否设最小样本阈值（例如被防出手≥150/200）？

如果你想自己复现，下面用 nba_api 的最小示例（返回表里含 DFG_PCT 和 FG_PCT_MINUS_DFG_PCT 即 Diff%）：

from nba_api.stats.endpoints import LeagueDashPtDefend

df = LeagueDashPtDefend(
    season='2024-25',  # 或 '2023-24'
    season_type_all_star='Regular Season',
    defense_category='Overall'  # 总体；可换 '3 Pointers', '2 Pointers', 'Less Than 6 Ft' 等
).get_data_frames()[0]

ayton = df[df['PLAYER_NAME'] == 'Deandre Ayton'][[
    'PLAYER_NAME','GP','DFGA','DFG_PCT','FG_PCT','FG_PCT_MINUS_DFG_PCT'
]]
print(ayton)

要我现在就帮你核对当前赛季的数值吗？