Lokshtanov, Marx, and Saurabh SODA 2011 proved that there is no $(k-ε)^{\operatorname{pw}(G)}\operatorname{poly}(n)$ time algorithm for deciding if an $n$-vertex graph $G$ with pathwidth $\operatorname{pw}(G)$ admits a proper vertex coloring with $k$ colors unless the Strong Exponential Time Hypothesis (SETH) is false. We show here that nevertheless, when $k>\lfloor Δ/2 \rfloor + 1$, where $Δ$ is the maximum degree in the graph $G$, there is a better algorithm, at least when there are few colorings. We present a Monte Carlo algorithm that given a graph $G$ along with a path decomposition of $G$ with pathwidth $\operatorname{pw}(G)$ runs in $(\lfloor Δ/2 \rfloor + 1)^{\operatorname{pw}(G)}\operatorname{poly}(n)s$ time, that distinguishes between $k$-colorable graphs having at most $s$ proper $k$-colorings and non-$k$-colorable graphs. We also show how to obtain a $k$-coloring in the same asymptotic running time. Our algorithm avoids violating SETH for one since high degree vertices still cost too much and the mentioned hardness construction uses a lot of them. We exploit a new variation of the famous Alon--Tarsi theorem that has an algorithmic advantage over the original form. The original theorem shows a graph has an orientation with outdegree less than $k$ at every vertex, with a different number of odd and even Eulerian subgraphs only if the graph is $k$-colorable, but there is no known way of efficiently finding such an orientation. Our new form shows that if we instead count another difference of even and odd subgraphs meeting modular degree constraints at every vertex picked uniformly at random, we have a fair chance of getting a non-zero value if the graph has few $k$-colorings. Yet every non-$k$-colorable graph gives a zero difference, so a random set of constraints stands a good chance of being useful for separating the two cases.