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Six years ago, I took my first crack at analyzing field goal kickers. I have been meaning to update that article for each of the last three offseasons, and with the sun setting on the 2015 offseason, I didn’t want to let this slip yet again.

Ranking field goal kickers is not difficult conceptually, but it can be a bit challenging in practice. One thing I’ve yet to refine is the appropriate adjustments for playing surface, stadium, time of game, temperature, and wind. That’s a lot of adjustments to deal with, all on top of the most obvious adjustment: for era.

But as I understand it, Rome was not built in a day; further, I believe that a journey of a thousand miles begins with one step. As a result, I’m okay with only getting part of the way there for now, and punting (which is very, very different from kicking) the rest of this process to next offseason.

Let’s begin with the obvious: era adjustments are really, really, important.  To provide some examples, I looked at the field goal rates at four different increments: 22-24 yard kicks, 31-33 yard attempts, kicks from 40-42 yards away, and finally, field goal attempts from 49-51 yards.  In the graph below, I’ve plotted the success rate at those four distances for each year since 1960, along with a “best-fit” curve at each distance. Take a look:

fg curves

Here’s the mind-boggling fact: kickers are more successful from 49-51 yards today than they were from 22-24 yards in the early ’60s. Even with the introduction of Pete Gogolak and the soccer-style kick, the increases here were largely gradual.

I ran similar regressions for all distances, and well, take a look at the smoothed lines here:

fg curves2

From here, all we need to do to rank kickers is compare their actual performance for kicks at each distance, and compare how they did relative to league average. Check back tomorrow for that.

  • Dan

    Some of your best fit lines are starting to curve down in recent years, which is not a pattern that is visible in the raw data. It appears to be a side effect of using a quadratic best-fit line, which can’t fit asymptotes or trend lines that rise to a plateau and then go flat.

    There is also a weird pattern where sometimes longer kicks have a higher accuracy than shorter kicks.

    • Agree with you on the first point, Dan. Is there a simple solution in Excel? I wasn’t too bothered because we’re not talking significant numbers here, but it would be better to improve on that.

      On your next point, that’s a result of sample bias. Only the best long-distance kickers even attempt some of those very long distance kicks.

      • Dan

        For 22-24 yarders, if the year is in column A you could force the expected FG% to plateau at its max value with the equation:

        =-0.0002*MIN(43,A)^2+0.0172*MIN(43,A)+0.592

        (Where 43 is chosen because that is the x-value where the original polynomial takes on its maximum.)

        Although Excel is still choosing the best fit polynomial based on the whole curve, including the downward part. A more complicated thing I might try is a piecewise fit, where you only fit the curve to the time period until the FG% at that distance reached 90%. Then you fit another curve to the time period after it had reached 90%.

        On the other point, I’m looking at things like the way that the 28-30 and 31-33 lines cross twice. Those two lines also have somewhat unusual shapes compared to the others around them (one is more curved, the other less curved). I suspect that this is noise, and not sampling bias that occurred in the 1960s and 2010s.

        • Yeah…. as you can see, you can quickly spend a lot of time on this stuff. In the interest of keeping things simple, I’ve decided to just take the maximum value for each year at each distance between two choices: what the formula produced, or the rate in the prior season. That gets us pretty close, I think, and saves a lot of hassle.

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  • dbqp

    How about ranking kickers by total yards of kicks made? We don’t rank quarterbacks by completion percentage.

    If you want to get a percentage, then percentage of the maximum yards they could make would be interesting. You could take into account fourth down conversion attempts in the maximum, as the coach would try more long field goals with the perfect kicker.

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