On behalf of my coauthors I am excited to share our new publication, out today in Animal Biotelemetry: Cole, M.R., McHuron, E.A., Costa, D.P., Ponganis P.J., and McDonald B.I*.* Acceleration metrics predict propulsive power at within-dive temporal scales in California sea lions. *Anim Biotelemetry* 13, 32 (2025). https://doi.org/10.1186/s40317-025-00428-y *Abstract*: *Background* Locomotion can drive variation in an animal’s energy expenditure, but the energetic cost of movement is difficult to measure at fine time scales in free-living animals. The 3 axis acceleration metrics Dynamic Body Acceleration (DBA) and Minimum Specific Acceleration (MSA) are commonly used in biologging studies as a proxy for activity or energy expenditure. These metrics hold potential for relatively simple and affordable estimates of movement-based energy expenditure, but have not been validated for use at fine temporal scales (e.g., within dives) due to logistical limitations of metabolic measurement techniques. Here, we use rates of propulsive power (W kg−1) recently calculated at 5 s intervals in diving California sea lions to test whether DBA and MSA can predict propulsive power at two within-dive temporal scales. *Results* Mean DBA and MSA predicted mean propulsive power in both 5 s intervals and dive phases (descent or ascent). All relationships were linear and significant. For all data types, likelihood ratio tests indicated that full linear mixed-effects models including random effects of individual (slope and intercept) had the best fit. Filtering and smoothing raw DBA and MSA data improved linear mixed models, though models with raw data were also strong. Using fixed-effects models on individual animals, both DBA and MSA successfully detected a known trend of increasing power use in deeper dives. *Conclusions* When applied appropriately, DBA and MSA can be easily calculated proxies for propulsive power, even at fine temporal scales, in all circumstances we tested. We show that this is true even while avoiding the “Time Trap”; i.e., using mean rather than summed data. While this study focused on California sea lions, we expect these metrics will also predict relative power in other species that swim with similar mechanics. However, as inter-individual slope was important to model fit, and as the scope of our validation was limited by the circumstances that allowed propulsive power calculation, we reiterate the need for care when inferring energetic cost from acceleration metrics like DBA or MSA. Please email me at marcole@ucsc.edu if you have any questions. Cheers, Mason