Related to: Can Counterfactuals Be True?, Newcomb's Problem and Regret of Rationality.
Imagine that one day, Omega comes to you and says that it has just tossed a fair coin, and given that the coin came up tails, it decided to ask you to give it $100. Whatever you do in this situation, nothing else will happen differently in reality as a result. Naturally you don't want to give up your $100. But see, Omega tells you that if the coin came up heads instead of tails, it'd give you $10000, but only if you'd agree to give it $100 if the coin came up tails.
Omega can predict your decision in case it asked you to give it $100, even if that hasn't actually happened, it can compute the counterfactual truth. Omega is also known to be absolutely honest and trustworthy, no word-twisting, so the facts are really as it says, it really tossed a coin and really would've given you $10000.
From your current position, it seems absurd to give up your $100. Nothing good happens if you do that, the coin has already landed tails up, you'll never see the counterfactual $10000. But look at this situation from your point of view before Omega tossed the coin. There, you have two possible branches ahead of you, of equal probability. On one branch, you are asked to part with $100, and on the other branch, you are conditionally given $10000. If you decide to keep $100, the expected gain from this decision is $0: there is no exchange of money, you don't give Omega anything on the first branch, and as a result Omega doesn't give you anything on the second branch. If you decide to give $100 on the first branch, then Omega gives you $10000 on the second branch, so the expected gain from this decision is
-$100 * 0.5 + $10000 * 0.5 = $4950
So, this straightforward calculation tells that you ought to give up your $100. It looks like a good idea before the coin toss, but it starts to look like a bad idea after the coin came up tails. Had you known about the deal in advance, one possible course of action would be to set up a precommitment. You contract a third party, agreeing that you'll lose $1000 if you don't give $100 to Omega, in case it asks for that. In this case, you leave yourself no other choice.
But in this game, explicit precommitment is not an option: you didn't know about Omega's little game until the coin was already tossed and the outcome of the toss was given to you. The only thing that stands between Omega and your 100$ is your ritual of cognition. And so I ask you all: is the decision to give up $100 when you have no real benefit from it, only counterfactual benefit, an example of winning?
P.S. Let's assume that the coin is deterministic, that in the overwhelming measure of the MWI worlds it gives the same outcome. You don't care about a fraction that sees a different result, in all reality the result is that Omega won't even consider giving you $10000, it only asks for your $100. Also, the deal is unique, you won't see Omega ever again.
Arguments like these remind me of students' mistakes from Algorithms and Data Structures 101 - statements like that are very intuitive, absolutely wrong, and once you figure out why this reasoning doesn't work it's easy to forget that most people didn't go through this ever.
What is required is Omega predicting better than chance in the worst case. Predicting correctly with ridiculously tiny chance of error against "average" person is worthless.
To avoid Omega and causality silliness, and just demonstrate this intuition - let's take a slightly modified version of Boolean satisfiability - but instead of one formula we have three formulas of the same length. If all three are identical, return true or false depending on its satisfiability, if they're different return true if number of one bits in problem is odd (or some other trivial property).
It is obviously NP-complete, as any satisfiability problem reduces to it by concatenating it three times. If we use exponential brute force to solve the hard case, average running time is O(n) for scanning the string plus O(2^(n/3)) for brute forcing but only 2^-(2n/3) of the time, that is O(1). So we can solve NP-complete problems in average linear time.
What happened? We were led astray by intuition, and assumed that problems that are difficult in worst case cannot be trivial on average. But this equal weighting is an artifact - if you tried reducing any other NP problem into this, you'd be getting very difficult ones nearly all the time, as if by magic.
Back to Omega - even if Omega predicts normal people very well, as long as there are any thinking being who is cannot predict - Omega must break causality. And such being are not just hypothetical - people who decide based on a coin toss are exactly like that. Silly rules about disallowing chance merely make counterexamples more complicated, Omega and Newcomb are still as much based on sloppy thinking as ever.
I don't know any reason why a coin toss would be the best choice in Newcomb's paradox. If you decide based on reason, and don't decide to flip a coin, and Omega knows you well, he can predict your action above chance. The paradox stands.