During the reproductive season, animals have to manage both their energetic and gametic budgets. In particular, for semelparous capital breeders with determinate fecundity and no parental care other than gametic investment, the depletion of energetic stock must match the depletion of gametic stock, so that individuals get exhausted just after their last egg is laid. Although these budgets are managed continuously, monitoring the dynamics of mating acts and energy expenditure at a fine temporal scale in the wild is challenging.This study aimed to quantify the individual dynamics of spawning acts and the concomitant energy expenditure of female Allis shad (Alosa alosa) throughout their mating season.Using eight individual-borne accelerometers for one month, we collected tri-axial acceleration, temperature, and pressure data that we analysed to i) detect the timing of spawning acts, ii) estimate energy expenditure from tail beat frequency and water temperature, and iii) monitor changes in body roundness from the position of the dorsally-mounted tag relative to the vertical.Female shad had a higher probability to spawn during warmer nights, and their spawning acts were synchronized within each active night. They underwent warmer temperature during the day, when they stayed deeper, and they swam faster at night, when they spent more energy. Over one month of spawning, they performed on average 15.75 spawning acts, spent on average 6 277 kJ and died with a significant portion of residual oocytes. The acceleration-based indicator of body roundness was correlated to condition coefficient measured at capture, and globally decreased through the spawning season, although the indicator was noisy and was not correlated to changes in estimated energy expenditure.Despite significant individual variability, our results indicate that female shad exhausted their energetic stock faster than their egg stock. Water warming might accentuate the mismatch between energetic and gametic stocks. Although perfectible, the three complimentary analyses of acceleration data are promising for in situ monitoring of energy expenditure related to specific behaviour.