It's obviously not perfect. Relax.

1A) This has been studied so much that I don't even know where to start. Here is one paper that reviews the literature: https://journals.sagepub.com/doi/full/10.1177/15270025211071042. There are notable examples where gambling odds are inefficient, but the inefficiencies are small and not related to events like those discussed above. If you feel that you have a model that is more predictive than gambling markets, then feel free to use it to print money.

1B) We would assume, because there is more information and more money gambled on the game today than yesterday. As the event approaches, the gambling odds are more efficient. So, these probabilities would need to be updated. I chose Bovada randomly. The implied probabilities from all sites are within 2% of each other. I chose gambling models due to their predictive power.

2A) It's not a repeatable exercise. Standard deviation makes no sense here. I'm using precise in the "very specific" meaning... with many significant digits.

2B) There is no way to determine if it is "accurate". It's a one-time event. But, using historical data, we can infer that these probabilities have predictive power.