This dataset is from an experiment in which nine female Allis shad (Alosa alosa) were tagged with loggers (WACU, Atesys-Montoux) which recorded tri-axial acceleration (8g, 50Hz), temperature (1Hz) and pressure (1Hz) during the 2017 spawning season in the Nivelle river. A characteristic acceleration pattern was used to detect spawning acts. Acceleration on the lateral axis was used to compute tail beat frequency, which coupled with temperature, was fed in a bioenergetic model to compute energy expenditure and mass loss. Pressure was coupled with pressure recorded near the river to compute depth. The static component of acceleration was used to compute the angle of the dorsally attached logger with the vertical. The dataset is composed of four files containing: 1) The exact timing of each spawning act of each shad. 2) The number of spawning acts performed by each shad on each night of the season, with water temperature during the night. 3) For each shad and each 8h period of the spawning season, the angle between the logger and the vertical (°), the angle shift to the next period (°), the mean temperature (°C), the mean pressure (hPa), the mean depth (cm), the mean tail beat frequency (beat/s), the cumulated energy expenditure (kJ) according to the bioenergetic model, the mass (kg) according to the bioenergetic model, an indicator variable whether the fish had been tagged for less (1) or more (0) than three days. 4) For each shad, biometric measures (length, mass at initial capture and at death, ovary mass at death), timing of capture and death, as well as variables computed from acceleration data (number of spawning acts, number of nights with at least one spawning act, total energy spent, predicted mass at death, angle of the logger at initial capture and at death). The dataset is accompanied by a Rmd script of the analyses performed on the dataset for the article found here: https://doi.org/10.1101/436295 (2020-06-08)