I think the "orthodox" answer is that your method wouldn't work, because if Alice picks 10 and 20 and opens 10 first then you have a 0% chance of winning. Instead (they say) you should pick your number at random, so that it has at least some probability of being any given integer. For example you could pick the number n with probability 2^|n|/3. That way no matter which two numbers Alice picks there's always some probability your number will be between them.

Now personally I think this is silly. You know nothing about what Alice is going to do, so your own choice of number can't possibly matter. You might as well always pick zero rather than randomizing. The reason the orthodoxy disagree is because the problem they're answering is something like "Find a strategy such that if you knew which numbers Alice had picked, but hadn't yet chosen your own random numbers, then you would always anticipate a >50% chance of winning."

This resembles the definition of a 95% confidence interval: "A procedure for generating intervals from data, such that if you knew the true value of the parameter, but not the data, you would assign a 95% probability that the true value lies in the interval". Of course Bayesians turn it around and define a credence interval where you know the data but not the true value (which I think is better, because this actually is your state of knowledge).