Exploring performance stats

I can either ask for clarification or provide a template, but if I don't have real-time stats, I might need the user to provide specific data. I know the user wants to discuss a comparison between the Thunder and the 2015-16 Warriors regarding point differentials and three-pointers. I remember that the Warriors started with a strong record of 24-0. So we could explore this conceptually while considering the Thunder's performance, which likely doesn't match the Warriors' early streak.Analyzing net ratings
The claim about the Thunder having a better net rating seems unlikely, especially since the 2015-16 Warriors had a full-season net rating of around +10.8. Their point differential during the first 21 games might have been about +14. I’ll need to be cautious here; I can't assert current-season stats without verification. If we compare the first 21 games, we should consider factors like pace, opponent strength, and three-point accuracy. It might be worth asking the user if they’d like a visualization or a comparison based on stats.Considering data fetching options
It looks like the network is likely enabled, but I need to confirm the approvals mode. Since I wasn't told otherwise, I'll assume it's enabled, with approvals on failure. I know we have the 'shell' tool available, which means I could potentially use curl to fetch data. However, since NBA stats usually require tokens and Basketball-Reference consists of static pages, extracting data might not be straightforward. I should propose a couple of options without changing code, keeping it focused on sports analysis.Structuring the response
I want to craft a clear and concise answer regarding the Thunder's three-point performance compared to the 2015-16 Warriors. First, I can confirm that the Thunder may have a higher three-point volume and net rating early in the season, influenced by factors like schedule and blowout games.
I should mention critical nuances like sample size, opponent strength, and potential shooting variance. If the user wants specific numbers, I'll need to clarify details about the season and metrics they prefer, and offer to create a table and chart if they approve data pulling. Keeping the response structured with bullet points is key!
这个结论有可能成立,但需要把“口径”说清楚才有意义。前21场对比,建议统一用每百回合口径并做时代校正,否则容易被节奏和联盟环境误导。
建议的对比口径
Net Rating(非垃圾时间更好),其次才是场均分差3PA rate(三分占比)、3PM(命中数/百回合)、3P%(命中率),三者分开看ORtg / DRtg、eFG%、失误率、进攻篮板率Pace、对手强度(如 SRS 或对手 ORtg/DRtg),尽量剔除垃圾时间解读要点
如果你要精确数字

请确认:
确认后我就拉数据并贴出对比表。