Here is a description of our new visualization for kickers, which can enhance your decision making.

In very short:

• The curve in the tool shows, for each yard line, the expected number of occurrences of a drive stopping there, minus the league average at each point.

• Therefore, positive values mean “the drive will more likely stop at this yard line, compared to an average kicker matchup situation.”

• A further detail: the units of the y-axis are “number of extra occurrences” within a 10 yard span (± 5 yards from each point).

For further understanding, here is the background of what supports the tool’s usefulness

Football teams get to attempt several drives during a game.

The location where each drive stops will determine the opportunity for scoring.

Simplistically, this means either punting (no score), field goals, or touchdowns.

It is obviously impossible to forecast exactly where any particular drive will end. Each drive is seemingly random.

However, there is a probabilistic nature to the end point of drives. The average frequency of NFL drives that finish at each yard line looks approximately like the following curve:

As labeled in the picture— simplistically— some drives stop before mid-field, some drives end in field goal range, and some end in touchdowns. Notice that punting is the most common outcome, in general.

It is useful to understand how the curve different, for each specific team and matchup. While the above graph represents an average probability of distributions across the league, the actual shape will look different for each offense + defense combination. In other words, some teams (and opposing defenses) will more likely stop drives sooner, whereas other matchups are likelier to produce more scoring.

The Kicker Curve tool works by:

1. generating the most likely such curve, for the given team and opponent— for the game in the current week, and

2. calculating the difference between the curve that describes the current match and the “average” curve as shown above.

Therefore, each displayed curve in the tool shows, for each yard line, the expected number of occurrences of a drive stopping there, minus the league average at each point.

This provides a powerful way to estimate where kickers are likely to see more of their opportunities come from.

Some kickers will be more likely to kick from afar, due to their matchup and their own team characteristics. But these long-distance kicking opportunities are often presented with less certainty, making them a risky option. For good teams and good kickers, it is also a rewarding option because of the 5 fantasy points awarded to kickers for long kicks.

Meanwhile, other kickers will see more short-range opportunities. Often, but not always, the short-range kicks come with more certainty (higher volume), and they furthermore provide the kicker with a “floor” of PATs (extra points, after touchdowns). However, fewer fantasy points for kick.

It is up to you whether you want to choose a kicker with certainty and volume, or a kicker with high upside but more volatility. Either way, this Kicker Curve tool is meant to assist you in finding the kicking behavior (or rather the likely kicking behavior) that suits you.

As always, note that the curves are not just generated from simple “averaging” models, that only look at past kicks. The curves are more powerful than that, because they are based on statistical predictive models—and therefore they are tuned to the dependencies of many input factors, such as passing, turnovers, aggressiveness, etc.

/Subvertadown