A rival team has an ambitious but craven assistant coach who, with a regime change, could be better controlled towards our interests.

Another team's key player couldn't be replaced on short notice, were they to be removed from the board, in a deniable 'gang-related' incident in front of the nightclub they frequent.

The roster of a favored team could be boosted with secret financial incentives to candidates, funded off-the-books by new gambling and prostitution operations.

I grew up with a kid whose dad worked in security for the St. Louis Rams NFL team. I was shocked when he told me how many attempts there are to blackmail or otherwise extort money from players.

Small potatoes- more realistic: Les Wexner pumped tens of millions into the university to whitewash his reputation; keep them perennial favorites but grease some SEC refs as necessary to keep our guy out of the limelight

The radio station chief is a con artist rainmaking the agency, he will cut us in if we squeeze him hard enough.

In this model the probabilities were measured by an ensemble of LLM's. We give them context and ask them to follow a specific methodology for making a forecast, and then aggregate their forecasts into a "crowd" forecast. We can get input from humans as well to compare/combine them further, but in this particular instance I just used our AI Forecaster.

You're right that a human analyst - especially a very experienced one - is going to be able to still do a better job of analysis most of the time, but the AI is useful for having loops to re-examine the question, consume and curate new information, etc. We've built the system with that assumption: let humans do what they're best at, let AI do what it's best at...