Concurrent programs are notoriously hard to write correctly, as scheduling nondeterminism introduces subtle errors that are both hard to detect and to reproduce. The most common concurrency errors are $\textit{(data) races}$, which occur when memory-conflicting actions are executed concurrently. Consequently, considerable effort has been made towards developing efficient techniques for race detection. The most common approach is $\textit{dynamic race prediction}$: given an observed, race-free trace $\sigma$ of a concurrent program, the task is to decide whether events of $\sigma$ can be correctly reordered to a trace $\sigma^$ that witnesses a race hidden in $\sigma$. In this work we introduce the notion of $\textit{sync(hronization)-preserving races}$. A sync-preserving race occurs in $\sigma$ when there is a witness $\sigma^$ in which synchronization operations (e.g., acquisition and release of locks) appear in the same order as in $\sigma$. This is a broad definition that $\textit{strictly subsumes}$ the famous notion of happens-before races. Our main results are as follows. First, we develop a sound and complete algorithm for predicting sync-preserving races. For moderate values of parameters like the number of threads, the algorithm runs in $\tilde{O}(\mathcal{N})$ time and space, where $\mathcal{N}$ is the length of the trace $\sigma$. Second, we show that the problem has a $\Omega(\mathcal{N}/\log^2 \mathcal{N})$ space lower bound, and thus our algorithm is essentially $\textit{time and space optimal}$. Third, we show that predicting races with $\textit{even just a single}$ reversal of two sync operations is $\mathsf{NP}$-complete and even $\mathsf{W}[1]$-hard when parameterized by the number of threads. Thus, sync-preservation characterizes $\textit{exactly}$ the tractability boundary of race prediction, and our algorithm is nearly $\textit{optimal}$ for the tractable side. Our experiments show that our algorithm is fast in practice, while sync-preservation characterizes races often missed by state-of-the-art methods.