Kevin Cole's 2018 NFL Betting Model: Wild Card Round

This article was originally scheduled for publish for last week, ahead of the NFL Wild Card round.

Along with working extensively on NFL projections this season, I’m also putting the data to use projecting game outcomes.

Last week, we introduced a new model for side bets only and the model’s picks will only be posted on Thursday/Friday. The first version of the model is what I will call 1.0, and this model is the results of a lot of work during the season to develop a power-ranking system based on play-by-play data.

The data I’m using also has advanced metrics, including expected points added (EPA) and success rates based on EPA.

I will continue track total record for the year, along with what the results are of the new model.

Methodology

The betting model is based on a combination of offense and defensive play-by-play stats, including success rate, or how often a play has positive EPA, yards per play, and EPA per play. The offensive and defense metrics are calculated for every team on a weekly basis and those trailing results are the basis for projecting team strength in upcoming matchups.

Week 17 Review

Last week the model was 2-1 for plays, while leans were 2-1.

For full disclosure, here are the numbers for the new and old model that has been discontinued.

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Wild Card Power Grades

The power grades here are the expected point differential for each team against an average team on a neutral field. The offensive and defensive ranks are based on 2018, the total power rank also incorporates offensive and defensive stats going back to 2017.

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Week Wild Card

Picks as of Thursday at roughly 6 p.m. ET

These picks are based on the power rankings above, with adjustments for home field advantage, and additional/fewer days of rest. The darker green/red plays are the plays for home/away team on the week. The lighter green/red cells are the leans of the week.

Plays:
None

Leans:
Chargers +3

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About the Author

colekev
Kevin Cole (colekev)

Kevin Cole previously worked on Wall Street as an equity and credit analyst before transitioning to data-related sports analysis. For a number of years, Kevin has specialized in creating predictive sports models that includes published work at Pro Football Focus, Rotoworld, numberFire, and RotoViz. He is now the Director of Data and Analytics at RotoGrinders.