What can machine learning and statistics do for fantasy football? It turns out, quite a bit.

In this model, I apply a clustering algorithm called the Gaussian mixture model to an aggregation of expert ranking data provided by Fantasypros.com. The algorithm finds natural tiers and clusters within the data. The charts that result visualize the tiers and help you decide your starting lineup each week.

The intuition behind both this model and the Fantasypros model is that a panel of a hundred experts can provide more accurate predictions than any one single expert can. Each expert uses his or her own sources and analysis to generate player rankings each week according to matchups. When you combine them, you get the Fantasypros’ E.C.R., or Expert Consensus Rankings.

But all ranked lists share a flaw. They imply a strict monotonic ordering and do not illustrate the true distance between players. A list implies QB1 > QB2 > QB3, whereas the reality might be QB1 >> QB2 = QB3.

The Gaussian mixture model addresses this, and the results are clear in the charts that are generated.