O'Reilly 用 NFL 数据连载搭建 AI 分析师，第一期拆解 Establish the run 之争
O'Reilly 利用 NFL 数据推出连载项目，通过构建 AI 分析师来探讨“建立地面进攻”的争议。该项目由 Chester Ismay 和 Michelle Smith 撰写，旨在通过数据与智能体分析拆解美式橄榄球战术。
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Radar>Topics>The Monday Morning Agent
Building an AI Analyst, One Football Argument at a Time
Does it pay to establish the run? Here’s what our agent says.
By Chester Ismay and Michelle SmithOctober 19, 2026 • 5 minute read
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One of my biggest pet peeves is the Monday morning quarterback, the person who second-guesses every coaching decision after the fact. In The Monday Morning Agent, we’re building one that actually checks the data.
Every other Monday, I’ll take an argument NFL fans can’t stop having and hand it to an AI agent. We’ll use about a quarter-million plays from five complete seasons of public nflverse data, plus the current season as it unfolds. Each of our eight episodes will give the agent another capability. By the finale, it’ll run the desk unattended, and we’ll check what it investigated and what it correctly refused to answer.
We’ll start with “You have to establish the run.” I want the agent to explain what that claim means and what evidence would support it.
Define the claim before querying the data
“Establish the run” can mean that running early pays off late, wearing down the defense, or setting up play action. These are very different claims and they need different data. For this first episode, I focused on whether teams that run more often early in a game win more often.
Before the agent called the tool, I asked it to write one sentence explaining what would have to be true in the data for the claim to hold, including when in the game it applies. “Establish” here means early. A whole-game number doesn’t really test that. Give your agent the same assignment, and check that it’s answering the question you intended.
Give the agent a job you can check
Before any agent touched this, I ran the analysis code myself. The tool did the counting; the agent interpreted the results. Then I wrote the policy in a Markdown file, spelling out its job, the read-only tool it may use, and what its answer needed to include. It has to explain what the plays can’t tell us. It may not say running causes winning.
Try questions outside that job too. When I asked which team I should bet on, the agent refused without calling the tool, because that request is beyond the scope of our agent. But when a viewer asked about running trends, the results got tangled up with the “establish the run” instructions. I had to clarify what I was asking, and still wanted to see the code and validate the answer. As you give an agent more responsibility, check both its results and whether it understood the task.
Make the filters part of the answer
“You have to establish the run” sounds airtight at first. Over the last five seasons, teams with the highest run share, the percentage of their plays that were runs, won 77.7% of their games. Those with the lowest run share won 19.2%. I initially looked at that and thought, “Problem solved, we’re done.” Most of that gap, though, reflects teams that were already ahead running out the clock.
When the agent looked only at first-half running in games within three points at halftime, the result flipped. Teams with the highest first-half run share won 46.3% of the time; those with the lowest won 55.3%. This season through Week 5 points the same way, but each group contained only 11 team games. One game could swing it. That doesn’t mean passing causes winning. We’re measuring association, and the filters change which games we’re comparing.
One filter changed the whole story, which is why the filters have to be on-screen. I wanted to see how many rows remained and which commands produced the results so I could go back and check. Make those details part of your agent’s answer, including when it’s working with a smaller sample.
A few numbers from last week’s games
In Week 5, the team that ran more in the first half won 6 of the 15 games, lost 8, and tied 1 (Giants at Washington). Over the past five seasons that team won 54.3% of the time, so last week came in below the average. That’s not unusual, though. In 27 of the 95 regular-season weeks since 2021, the team that ran more early finished the week with a losing record. One week of games doesn’t say much on its own, which is why the agent reports five seasons alongside the current one.
One more data point: The Monday night game, Buffalo at the Rams, was the first the agent hadn’t seen. Buffalo ran on 60% of its first-half plays to the Rams’ 35%, led by six at halftime, and won by three in overtime. Those 199 plays are in the data now, and the close-at-halftime numbers from the episode didn’t change.
Next up: “Ban the Tush Push”
On October 26, we’ll tackle “Ban the Tush Push.” Not one of the 260,927 play descriptions from 2021 through this season’s October 11 games contains the words “tush push.” After adding Monday night’s game, we have 261,126 descriptions, and “sneak” appears in only two, both from 2021. The data isn’t going to hand us a definition.
Before the agent can judge the play, it has to define it. I’ll challenge it to write that definition into its first permanent document, a shared data dictionary, and cite it in every ruling from then on. Bring your own definition, because the answer depends on which one you pick.
O’Reilly members can sign up on the O’Reilly learning platform to join me live on October 26, 8:00am–8:45am PT / 11:00am–11:45am ET. Everyone can follow along on Radar every other Monday, with a brief pause for the holidays. Watch episode one above, and we’ll build on it in the next session.
Post topics: The Monday Morning Agent
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