After analyzing the attributes of more than half a million songs released over a period of 30 years, a computer algorithm was able to sort the successful songs from also-rans with an accuracy of up to 86%.

A team of mathematicians from UC Irvine described how — and why — it accomplished this feat in a study published in Wednesday’s edition of the journal Royal Society Open Science.

“There is something magical about music,” wrote the team, which was led by students Myra Interiano, Kamyar Kazemi and Lijia Wang. “Scientists have been trying to disentangle the magic and explain what it is that makes us love some music, hate other music and just listen to music.”