Underdog Status Rarely Impacts Fourth Down Aggressiveness

By Kurt Bullard

On Saturday, the Houston Texans entered Gillette Stadium as massive underdogs. As 16-point ā€˜dogs, the Texans were the fourth-biggest underdogs in NFL playoff history. Every trend and stat suggested that the Patriots were an unconquerable behemoth, from the rather simple ā€œThe Patriots are 9-1 in the Divisional Round with Tom Bradyā€ to the more complex, Aaron Schatzā€™ level of the Patriots being the best team per DVOA, with the Texans between Jaguars and Niners at sixth-worst in the NFL. That, and the fact that Brock Osweiler was a historically bad quarterback who averaged 5.8 yards per attemptā€”last in the league among QBs with 300 attempts by 0.43 yards per attempt.

Yet, to an unaware observer of the gameā€”although, Iā€™m not sure how long it would take someone who hasnā€™t watched football before to figure out Brock is an awful quarterbackā€”it didnā€™t seem as if the Texans thought themselves underdogs. As Bill Barnwell puts forth very eloquently in his Sunday column, Bill Oā€™Brien had many chances to take a shot on fourth down and try to squeeze the most out of the field position they had. They kicked a FG on 4th-and-4 on the NE 15, 4th-and-4 on the NE 28, and on 4th-and-3 on the NE 9, and punted three times in New England territory. Houston seemed like a team content to play a low-risk strategy and hope that Tom Brady would make mistakes at home. Iā€™m not an NFL coach by any stretch of the imagination, but Iā€™ve watched enough football to know that strategy doesnā€™t bear fruit very often.

In March Madness, itā€™s pretty accepted that teams who are underdogs alter their strategy somewhat to increase their odds of beating a Goliath. Between slowing down the tempo to limit the amount of possessions and thus increase variance in the outcome of the game, to shooting more three-pointers to do the same, NCAAB underdogs often realize that they are such. Yet, despite having been blown out by Jacoby Brissett in Week 3 by 27 points, Bill Oā€™Brien acted as if he was the favorite in this gameā€”no altering of strategy and no special teams trickery.

But as much fun as it is to pin blame on Bill Oā€™Brienā€”like how he stayed in Waltham for the Week 3 matchup despite knowing that Patriotsā€™ pre-game traffic is god-awfulā€”this is a plight of all NFL coaches. Rarely do they admit that they donā€™t expect to win, and rarely do they act like an underdog. Another example of this is Ben McAdooā€™s coaching last week. Coming in as 5-point underdogs, McAdoo chose to kick a FG on 4th-and-3 on the GB 8 in the first to open the scoring for both teams, and on 4th-and-4 on the GB 22 up 3-0 in the second quarter. Early leads often cloud the minds of coaches, while the Giants probably should have been aggressive in those situations or just looked over at the other sideline and seen Aaron Rodgers there and thought, ā€œHey, we might not win this game 12-7.ā€

As a side-note, I think the one coach good at admitting that his team is the underdog is Mike Tomlin. As I mentioned in an interview with the Pittsburgh Post-Gazette, despite being up 6-0 and 12-0 to the Cowboys in November, Tomlin went for two in both of those situations against the NFC regular-season champions, not letting early success in a game lead to overconfidence. However, not going for a touchdown on 4th-and-1 on the KC 4 yesterday was slightly questionable.

I wanted to see if a teamā€™s status as underdog influenced play-calling early in the game before the game situation starts to dictate all calls. So, I looked at all fourth-down decisions in the first three quarters of the 2015 season (since I had line data for 2015) with the hope of creating models that would predict a teamā€™s decision on fourth down. I split the data into two separate framesā€”all plays from OWN 30 to OPP 45 and calls from OPP 30 to OPP 0. I did this to make two separate models to predict whether a team would a) go for it or punt, and b) go for it or kick a FG. I ignored plays from the OPP 45 to OPP 30 because play-calling there is conflated with kicker strength and weather, data which I was not able to compile.

Field Goal or Go For It?

The variables I considered in this model were field position, yards to go to a first down, time remaining in the game, the score differential, and the betting line as a proxy for relative team strength. I tried two different models: an additive model (stepwise logistic regression) and a non-additive one (decision tree).

The logistic regression yielded the following coefficients:

As you can see, line was not a significant predictor of a teamā€™s aggressiveness in play-calling when choosing whether or not to kick a FG.

The decision tree (after pruning based on cross-validation error) yielded the following classification system:

The only distinction the tree was able to make (after pruning) was that it would predict teamā€™s would go for it on 4th-and-1, and kick a FG otherwise. As you can here as well, the line didnā€™t seem to add any predictive power to modeling fourth down play-calling.

Punt or Go For It?

Here is the logistic regression model, which as you can see, does not include the line as a predictor after stepwise reduction.

Here is the decision tree after pruning, which also does not include the line as a predictor.

Itā€™s pretty apparent that a teamā€™s relative standing to the other team does not factor into play-calling on the whole across the NFL early in NFL contests.

Thereā€™s a popular mantra that ā€œthe odds are 50-50, it either happens or it doesnā€™t,ā€ and, besides Tomlin, it doesn’t seem like many other coaches are willing to question traditional knowledge.

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