Bayesian v. Frequentist

This debate is a century old, and is between people who believe what you believe going in should be accounted for (Bayesians) and those who think the only thing that matters is the data you observe (Frequentists).

Here's my position: Anything that fits Kolmogorov's axioms of probability can be treated probabilistically. That means all the usual things like the odds of a strait flush and somewhat amorphous things like what you think the odds are of a person bluffing on a given hand.

The biggest thing is the nature of probability and statistics. Yes, it is usually used to describe things we see and experience around us, but is usually formulated in a much more abstract setting. This means while the people who use it are thinking poker hands, the theory works equally well for predictions, etc. So long as what we want to talk about meets a few very broad requirements, the math will still work.

The irony is that Kolmogorov was a frequentists, but his theory (built on measure theory, set theory, and analysis) and his theory grounds both schools of thought.