  The winding angle probability distribution of a planar self-avoiding walk has
been known exactly since a long time: it has a gaussian shape with a variance
growing as $<\theta^2>\sim \ln L$. For the three-dimensional case of a walk
winding around a bar, the same scaling is suggested, based on a first-order
epsilon-expansion. We tested this three-dimensional case by means of Monte
Carlo simulations up to length $L\approx25\,000$ and using exact enumeration
data for sizes $L\le20$. We find that the variance of the winding angle scales
as $<\theta^2>\sim (\ln L)^{2\alpha}$, with $\alpha=0.75(1)$. The ratio $\gamma
= <\theta^4>/<\theta^2>^2=3.74(5)$ is incompatible with the gaussian value
$\gamma =3$, but consistent with the observation that the tail of the
probability distribution function $p(\theta)$ is found to decrease slower than
a gaussian function. These findings are at odds with the existing first-order
$\epsilon$-expansion results.
