For simplicity, let us fix definite start and end points to the hypothesis, so in words the hypothesis might be
"People traveling from point A to point B by roller blade arrive sooner than those who walk."
Probably the simplest way to express this hypothesis is to add the qualifier "... on average".
Then the hypothesis becomes a definite statement about the conditional expectation of the travel time, given the mode of transportation.
To proceed you would then introduce a symbol for the travel time, say $T$, and a symbol for the mode of travel. If we are assuming that all travelers either use roller blades or they walk, then we can represent the travel mode by a dummy variable such as
$$R=\begin{cases}1 & \text{if roller blade} \\
0 & \text{if walk} \end{cases}$$
Then the hypothesis becomes
$$\mathbb{E}[\,T\mid R=1\,] < \mathbb{E}[\,T\mid R=0\,]$$
where $\mathbb{E}[\,x\mid a\,]$ should be read as "the expected value of $x$, given $a$".
Usually the symbol $H_0$ that you use is reserved for the null hypothesis, which is typically the negation of the hypothesis of interest. So for example in this case, $H_0$ might be "roller blading is no faster than walking".
One last point: The hypothesis as expressed in the equation above is not actually empirically testable, because the theoretical expectations cannot be literally computed. So usually a next step is to use the theoretical hypothesis to generate predictions about what would be observed in a data-set (sample) of actually observed $(T,R)$ pairs.
