Simple Football Predictor: Week 14 Predictions
By: Nathaniel Selevan
Tags: Logistic Regression, Linear Regression, Data Analytics, NFL, Predictive Analytics

Last week I considered myself quite lucky that there was no Thursday Night Football, as I completed this article at about 11:30 AM Monday. Unfortunately, this week I have no such luck, and I am writing this during the first quarter of tonight’s game. As I mentioned last week, the model does not incorporate current games and only uses historic data, so there is no bias in these predictions.

Week 14 Results:

Week 13 and Season Results

Last week I noted that the model predicted the home team to win 12 out of the 15 games. Unfortunately, nearly the opposite was true, the road team went 10–5. My model went 8–7, thanks to a strong performance from the super confident interval, and now rate at 66–49 on the season or 57.39%. Against the spread the model picked at 9–6, bringing its record on the season up to 38–33–2 for an accuracy of 53.42%.

PS — My bold prediction that the Jets would be tied at halftime prior to only gaining less than 100 2nd half yards turned out to be wrong on both those counts.

Week 14 Predictions

Predictions vs Spread (As of 8:48PM Thursday)

Rams(-5) vs Patriots: Patriots

Seahawks(-13.5) vs Jets: Jets

Bears(+2) vs Texans: Texans

Jaguars(+7.5) vs Titans: Jaguars

Panthers(unknown) vs Broncos: Panthers

Bengals(+3.5) vs Cowboys: Bengals

Dolphins(+7) vs Chiefs: Dolphins

Giants(+2.5) vs Cardinals: Giants

Buccaneers(-6.5) vs Vikings: Vikings

Raiders(+3) vs Colts: Raiders

Lions(+8) vs Packers: Lions

Chargers(+2.5) vs Falcons: Falcons

Eagles(+7) v Saints: Saints

49ers(-3.5) vs Washington: Washington

Bills(-2) vs Steelers: Steelers

Browns(+2) vs Ravens: Browns

Quick Observations:

I haven’t checked in on the intercepts and coefficients recently, but maybe I should. I can’t think of a valid reason why the Dolphins should be favored over the Chiefs. Here’s how they break down in stats used in this model.

Dolphins vs Chiefs Comparison

I get that the Dolphins have a slight edge in point differential, but Chiefs have a killer offense (the Jets on the hand have only topped 300 twice, and 325 once, last week). For now I assume it is related to a strong home bias in the model.

Since the spread model seems quite averse to predicting large victories, I noticed a phenomena where 5 point underdogs and above are almost always predicted to beat the spread. This led to a situation where the models without fail predicts the Jets and Jaguars to beat the spread every week. Of course, as the Eagles demonstrate this week, there are exceptions.

Speaking of the Jaguars, I noticed how consistent their defense was in terms of points allowed. Their last 5 games with the most recent first: 27, 27, 27, 24, 27. Six games ago they allowed 39, but the 5 games before that: 34, 30, 33, 31, 33. Will they allow 27 points again, or will they have an outlier after 5 games like the first time. In case you were wondering, besides the 39 points allowed 6 games ago, their only other outlier was 20 points allowed week 1. The average of 20 and 39 is 29.5, The average of the 2 sets of consistency…29.3 (26.4 and 32.2).

For the record there is now 4:30 left in the second quarter and Rams are up 17–0, so my prediction is holding up, just don’t look at the spread.

Finally, I submitted my final project for my Data Science course, so hockey fans, be on the lookout in a couple of weeks for a post on that sport.

I am currently enrolled in the Applied Data Science Professional Certificate program at the Thayer School of Engineering at Dartmouth College. Please reach out to met via LinkedIn (https://www.linkedin.com/in/nathanielselevan/) or comment below with all questions, comments, project suggestions, or to act as a mentor. All likes and comments will be well appreciated.