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Still 2-1 mid third. Mazzone with 4 k's through 2 but command has been an issue. Let's see of she dials it in here.

Fuck. Fsu up 2-0 with no outs in the 2nd. Third passed ball on our catcher allows the second run. Mazzarone struggling with command.
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Ladies up 1-0 after one. Mazzone with a strikeout to end the inning with runners on 2nd and 3rd.

Ive said this before but baseball is the easiest to solve eith metrics because there isnt a ton of same time actions that affect a play vs basketball vs football. In addition, the number of games is a huge advantage for metrics as there is more data to support outcomes.

Now AI can easily help with the first because it can easily look at 11(22) different factors at one time, but it only has around 1000 plays to do that in a season for the NFL and less in college.

in Big12 championship news, Arizona St. is about to give Texas Tech a big black eye before the NCAA tournament, up 4-0 right now in the bottom of the 7th.

OK, so this is the college equivalent the postseason tournament my kids 0-8 10U lacrosse team is about to play in. Got it.

But the question in not whether it will snow this year; but how much will it snow. And unfortunately, the answer is expressed in feet.

Could you elaborate on what is staggering about the nats 2026 results? I don't really know anything about how the nats are using AI but the 2026 MLB season is pretty early on. Seems way too early to draw any conclusions. And at the time im writing this, the nats have a losing record. Are there some advanced metrics in which theyre doing really well that they weren't last season?

I agree with your thoughts. AI is great at picking up on signals that humans are not able to sense, or AI is able to do it more quickly. AI is changing how we diagnose issues in all fields.

AI is also really good at assessing all permutations based on the input. I can imagine a world in which head coaches make smarter decisions on the sideline because he uses AI. We all know Pry could have used some AI on the sidelines.

AI can better assess how allocate funds and optimize roster building.

AI is also not a static program. It's an arm-race of sorts of determining how to best build models, which input data to use, and how to use that input data.

If atheletic teams are not looking to implement AI as a tool intelligently, and if they are not hiring AI-focused staff, they'll eventually get passed by someone that does.

I imagine a few people on here are Nats baseball fans. 2025 was pre-AI implementation and 2026 is AI-driven, and the results thus far are staggering. And they haven't yet significantly spent money on free agency. So, everything done thus far is essentially doing it with less money spent than what they had in 2025 (and way less than pre-2022 days). Once they decide to spend, they'll be bona fide contenders again.

Agreed on 1999...

Yea, they say 2000 zero-zero party over. Oops! out of time.

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