Week 5 Expected Fantasy Points: Rushing and Receiving

Look at past posts for the methodology on how the expected fantasy points calculation was enhanced using historical trends for fantasy points based on air yards, yards after catch, yard line and touchdown ratios. Data was pulled using nflscrapR.

The first table is a shorter version with columns for expected fantasy points, actual fantasy points and the difference in total, for rushing and for receiving. The second table, which is much wider, includes all the individual components for the rushing and receiving calculations. Unfortunately, the data I have doesn’t differentiate between positions, so running backs, wide receivers and tight end are all in the same table. Continue reading “Week 5 Expected Fantasy Points: Rushing and Receiving”

Week 4 Expected Fantasy Points: Rushing and Receiving

Look at past posts for the methodology on how the expected fantasy points calculation was enhanced using historical trends for fantasy points based on air yards, yards after catch, yard line and touchdown ratios. Data was pulled using nflscrapR.

The first table is a shorter version with columns for expected fantasy points, actual fantasy points and the difference in total, for rushing and for receiving. The second table, which is much wider, includes all the individual components for the rushing and receiving calculations. Unfortunately, the data I have doesn’t differentiate between positions, so running backs, wide receivers and tight end are all in the same table. Continue reading “Week 4 Expected Fantasy Points: Rushing and Receiving”

Week 3 Expected Fantasy Points: Rushing and Receiving

Look at past posts for the methodology on how the expected fantasy points calculation was enhanced using historical trends for fantasy points based on air yards, yards after catch, yard line and touchdown ratios. Data was pulled using nflscrapR.

The first table is a shorter version with columns for expected fantasy points, actual fantasy points and the difference in total, for rushing and for receiving. The second table, which is much wider, includes all the individual components for the rushing and receiving calculations. Unfortunately, the data I have doesn’t differentiate between positions, so running backs, wide receivers and tight end are all in the same table. Continue reading “Week 3 Expected Fantasy Points: Rushing and Receiving”

Week 2 Expected Fantasy Points: Rushing and Receiving

Last week I put together an expected fantasy points calculation for receiving, using air yards data available from nflscrapR to enhance the typical calculation that only uses yard line. By using air yards, we were able to calculate more accurate expected catch rates, expected yards and expected touchdowns based upon how far the ball was thrown. For example, you’re more likely to catch a short pass, but a longer pass that would be caught near the end zone gives you a much higher chance at a touchdown.

This week I’m adding expected fantasy point from rushing to the calculation. I found that yards to go on a play has strong relationship to yards gained,1 and I used that relationship to calculate expected rushing yards for each play. Continue reading “Week 2 Expected Fantasy Points: Rushing and Receiving”

Using Air Yards to Enhance Expected Fantasy Points

I’ve spend a lot of time recently messing around with the excellent air yards data you can pull from the NFL.com API using the nflscrapR package in R. After the kickoff game last week, I used air yards to show that Alex Smith has, in fact, not morphed into a bomb throwing passer. But there are many more applications for air yards data. The most interesting being for receivers.

If we know where a player was targeted on the field, we build league-wide historical averages for anything from expected yards, touchdowns, and receptions. Then, we can compare those expected number to what was actually posted in the box score. The differences between expected and actual stats can help us identify receivers who may be under- or overvalued based on unsustainable levels of efficiency.

I’ll say this in bold letter: Receivers will not all regress to league-average numbers! I’m not foolish enough to think that equal opportunity will eventually lead to equal stats for Antonio Brown receiving passes from Ben Roethlisberger and an unheralded wide receiver playing with one of the most inefficient quarterbacks in the league.

That said, these numbers can give up an idea of receivers’ potential upside, or downside, if notoriously volatile efficiency moves in the other direction. Continue reading “Using Air Yards to Enhance Expected Fantasy Points”

Foreman, Fournette and Mixon Lead the 2017 RB Success Model

We have roughly a month until the 2017 NFL draft, when we will learn where our favorite (or not so favorite) prospects will land this coming season. While draft position and landing spot are huge factors for forecasting the success of any running back prospect, I’ve found that we can accurately predict whether a running back will be successful largely based on his production profile and athletic measurables.

We know that collegiate production isn’t everything for wide receivers, it’s the only thing. For running backs, the situation is wholly different. Production matters, but size-adjusted speed is king for determining which running backs will be successful in the NFL.

You can define success many ways, but I’m choosing to use a top-12 fantasy point season (PPR) for running backs. The model’s dependent variable for early NFL success is whether or not a player had such a season within his first three years in the NFL. Continue reading “Foreman, Fournette and Mixon Lead the 2017 RB Success Model”