Statistical physics does make assumptions about interactions: these are essential for establishing the thermodynamic equilibrium, but do not determine the actual form of this equilibrium. So the non-interacting ideal gas and other systems studied in statistical physics are not really non-interacting, but rather the interactions can be neglected. Note that this assumptions about equilibrium could be derived formally from BBGKY hierarchy of equations (see this answer for details and references), but the beauty of statistical physics is that we can arrive to the answer via rigorous reasoning (if one doesn't skip passages without formulas in textbooks ;)).
Thus, the non-interacting billiard balls would not come to thermal equilibrium. The pressure would not be constant - even in a thermal equilibrium there is shot noise originating from single balls hitting the walls of the container. The pressure calculations given in statistical physics books assume (sometimes without stating it explicitly) averaging over many collisions, i.e., over many balls hitting the wall. If the distribution is not an equilibrium one, then one cannot guarantee constant pressure even after averaging: e.g., if balls move in groups, we will have times when very few balls hit a specific wall, and others when there are many balls hitting the same wall.
Finally, studying balls dynamics in an arbitrary shape billiard is actually not an easy endeavor, since even behavior of a single ball may turn out to be chaotic! see Dynamical billiards Here is an article that discusses a somewhat simpler problem of one-dimensional motion - it is essentially a one-dimensional billiard, which one could solve exactly (it is not exactly solved in the article, but it can be done with a bit of effort and patience).
Appendix: 1D billiard
As I mentioned above, one could consider exactly a one-dimensional billiard: particles are confined between two walls, in interval $[-L/2, L/2]$, from which they scatter elastically and instantaneously. If we now consider a particle that starts at point $x_0$ with velocity $v_0>0$, it will travel back an fourth between teh two walls, hitting them at times
$$
t_n = \frac{L/2-x_0}{v_0}+\frac{(n-1)L}{v_0},
$$
where the odd $n$ correspond to hitting the right wall and the even ones to hitting the left wall. Let us consider only the collisions with the right wall, which take place at times
$$
t_{2k-1}=t_1 + \frac{2(k-1)L}{v_0},\\
t_1 = \frac{1}{v_0}\left[L-\left(x_0+\frac{L}{2}\right)\text{sign}(v_0)\right]
$$
(where I generalized the formula for $t_1$, so that it applies for negative values of $v_0$ as well.)
At every collision the particle transfers to the wall momentum $2mv_0$, so that the force produced by the collision at a specific time (e.g., $t_1$) can be written as
$$
f=\frac{dp}{dt}=2mv_0\delta(t_1-t).
$$
Here I assume that the collisions are instantaneous - if not, one could replace the delta-function by some appropriate shape, e.g., a Gaussian profile. Collision time is however the shortest one here.
More generally, the force as a function of time is written as
$$
f(t|x_0,v_0)=2mv_0\sum_{k=1}^{+\infty}\delta\left(t_{2k-1}-t\right)=\\
2mv_0\sum_{k=1}^{+\infty}\delta\left\{\frac{1}{v_0}\left[L-\left(x_0+\frac{L}{2}\right)\text{sign}(v_0)\right]+\frac{2(k-1)L}{v_0}-t\right\}=\\
2mv_0^2\sum_{k=1}^{+\infty}\delta\left[L-\left(x_0+\frac{L}{2}\right)\text{sign}(v_0)+2(k-1)L-v_0t\right]
$$
Assuming that we have $N$ particles with initial values $\{(x_i,p_i|i=1..N\}$ we can now write down the full force as
$$
F(t)=\sum_{i=1}^Nf(t|x_i,v_i).
$$
We could get a more general result by assuming that the particles are distributed according to a probability density $w(x,v)$. This reduces to the case of discrete particles, if we take
$$
w(x,v)=\sum_{i=1}^N\delta(x-x_i)\delta(v-v_i).
$$
However, in statistical physics we usually assume the procedure known as coarse graining, where the particles are distributed so densely, that we can treat them as a continuous medium. The result is then (after some algebra):
$$
F(t)=\int_{-L/2}^{L/2}dx\int_{-\infty}^{+\infty}dv f(t|x,v)w(x,v)=\\
2m\int_0^{+\infty}dvv^2\sum_{k=1}^{+\infty}w\left[L\left(2k-\frac{3}{2}\right)-vt,v\right]\theta\left[vt-L(2k-2)\right]\theta\left[L(2k-1)-vt\right] + \\
2m\int_0^{+\infty}dvv^2\sum_{k=1}^{+\infty}w\left[vt - L\left(2k-\frac{1}{2}\right),v\right]\theta\left(2kL - vt\right)\theta\left[vt-L(2k-1)\right],
$$
where the two terms come from the particles that were moving initially right and left.
Now, if we take a distribution function that is a) uniform in space, and b) symmetric in velocity:
$$
w(x,v)=\frac{w(v)}{L}=\frac{w(-v)}{L},
$$
then the above result can be collapsed into
$$
F(t)=\frac{4m}{L}\int_0^{+\infty}dv v^2w(v);
$$
which is a force constant in time (which corresponds to pressure, when divided by the wall surface).
We now see the approximations that needed to be made in order to arrive at this result:
- coarse graining - i.e., assuming a continuous particle distribution
- uniform distribution in space
- symmetric velocity distribution
Note however, that the velocity distribution does not have to be Maxwell, although the latter satisfies the above requirements.
Remark: There was an error in manipulating delta-function, which I have fixed. The result is now consistent with the ideal gas law, if we use $w(v)\propto\exp(-\frac{mv^2}{2})$... but for a factor of $2$. If somebody bothers to repeat this derivation and find where I lost it, please let me know.