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A new method of gathering statistics for Monte Carlo methods, Legendre polynomial weighted sampling (LPWS), is presented. LPWS requires only a minimum of particles to extract higher‐order derivative information about a particle’s distribution function. In this technique, when calculating a particle’s distribution function, higher‐order derivative information about the Monte Carlo particles is recorded along with just counting the number of particles in a bin. The distribution function is then constructed from this information. Specifically, in this paper, second‐order Legendre polynomial weighted sampling is employed. Legendre polynomial weighted sampling is demonstrated by calculating the electron energy distribution functions in an inductively coupled plasma reactor.