Wide Receivers Who Should Have Scored More: Positive Touchdown Regression Candidates
Get a free NFL subscription for 3 days.
Due to the variance in wide receiver touchdowns year-to-year and other stats only weakly predicting next-season receiving TDs, regression can be used to identify wide receivers whose 2017 receiving touchdowns didn’t align with their expected touchdown total.
WR Touchdown Regression EquationYou can see my methodology behind this equation here. But the jist of it is:
Expected reTDS = 0.139 + (-0.015 * Total reRTGS) + (0.008 * Total reYDS)
- For positive touchdown regression: look for WRs with a lot of yards, but few touchdowns.
- For negative touchdown regression: look for WRs with more touchdowns than their total receiving yards would predict, even if they have a lot of targets.