Just to add a bit to what has already been said in the comments above.
First I don't know if you have heard about a probability density function (pdf)? If not, you can read a bit about it on this Wikipedia page. A pdf is a non-negative function defined on the real numbers (lets just go with the real numbers here) satisfying that if we take the area under the graph of $f$ from $-\infty$ to $\infty$ we get $1$. We use $f$ to calculate the probabilities that an outcome is in a certain interval. So for example the probability that a outcome is any real number is $1$ because of the area condition from above. If I want to find the probability that an outcome is in an interval $[a,b]$ I would find the area under the graph from $x=a$ to $x = b$.
The the pdf $f$ tells us something about the likelihood of finding an outcome in a certain interval. If the function is constant on an interval and zero out side, like:
$ f(x) =\begin{cases} 0 & \text{if } x < a \\ \frac{1}{b-a} & \text{if } x \in [a,b] \\ 0 & \text{if } x > b \end{cases} $ then we say that the pdf is a uniform density function. This just means/assumes that the only possible outcomes are in the interval $[a,b]$. (So for example $b$ would be the maximum of the possible outcomes, i.e. $b = max$ in your case).
So in your case with $a = min$ and $b = max$ our expression:
$ \frac{max - x}{b - a} $
is exactly the area under the graph of the pdf from x to max. Hence it gives you the probability that an outcome (the number chosen) is in the interval $[x,max]$.
But this of course assumes that the outcomes are uniformly distributed. In that case you, in you specific example, indeed get (as mentioned in the comments):
$ \frac{15255 - 12910}{15255 - 8156} \simeq 0.3303 = 33.03 \% $