2023 Off-Season Mock Drafts: Mock Draft Simulator vs ADP

With two months of rookie mock draft data accumulated over the course of 20 mock drafts, I was curious how our very own Mock Draft Simulator Tool stacked up with the results we are seeing in the most recent DLF mock drafts.

I'll compare the March superflex rookie ADP results with the results of a five-round, superflex rookie draft using the Mock Draft Simulator Tool, where I was randomly assigned the sixth pick. I'm curious to see how close the mock draft tool is to the ADP, and if any player's ADPs seem misaligned, is their ADP being skewed by one or two outliers in the mocks? So, with the explanation and intentions out of the way, let's see how this plays out.

Round One

I was surprised to see CJ Stroud fall to 1.05 in my mock draft. According to the ADP data, he never fell below 1.03. Although Jahmyr Gibbs was taken with the third pick in my mock, ADP indicates that he will fall into the 5/6/7 range in actual drafts. I tend to lean towards the results of my mock draft, as running back scarcity often leads to some meteoric climbs in ADP once real drafts commence.

ADP and the mock draft both had the same top-nine selections, albeit in a different order. The mock draft tool had Michael Mayer, Zach Evans, and Kayshon Boutte drafted in the first, while ADP indicates that they're on the outside looking in at Zach Charbonnet, Zay Flowers, and Josh Downs. If Mayer gets first-round capital in the NFL draft, he will probably climb into the back end of the first in fantasy drafts. I also suspect Charbonnet squeezes into the tail-end of the first round in fantasy drafts following the NFL draft.

For the most part, the Mock Draft Simulator Tool was in line with what we see from the ADP. At 1.06, I went with Anthony Richardson, who arguably has the highest upside of any player in the entire draft not named Bijan Robinson. I was ecstatic to get him at 1.06, and I also thought Will Levis was a tremendous value at 1.09.

Round Two