Doinkalytics: Rethinking How We Grade NFL Kickers

Season-opener edition — it's been a while. Week 1 was a kicker's week: Harrison Butker hit a 59-yarder with no timeouts to end the first half; Andre Szmyt had a brutal debut in Cleveland, missing a field goal and an extra point in a one-point loss; Matt Prater — who apparently surprised the opposing defense just by being active — drilled a walk-off field goal for Buffalo. But the story I want to start with is the one that ended last week: Jake Moody's time in San Francisco.

1. Jake Moody's 2 Seasons + 1 Game: A Postmortem

(Note: you can skip this section entirely without losing anything — the research breakdown in Section 2 stands on its own.)

The 49ers released Moody the day after Week 1. Draft pick: third round, 99th overall, 2023. Time elapsed: two seasons and one game. The timing looks abrupt on paper, but honestly — it was overdue.

I went back through X to find where the mood shifted. Early in his 2023 rookie season, the tone was supportive — nothing unusual there. The turn came in the regular season finale against the Rams, when Moody missed a 38-yarder and an extra point in a one-point loss. Then the playoffs arrived and he missed in every single game — not 55-yarders, just ordinary kicks.

By the NFC Championship loss to the Lions, the grace period had clearly expired. Context that made it worse: his predecessor Robbie Gould was remarkably clutch in the postseason — not a Pro Bowler by any stretch, but a guy who seemed to save his best kicks for January. 49ers fans had a very specific postseason standard, and Moody wasn't clearing it.

To be fair: Moody's first-year field goal percentage was 84% (21/25) — low, but not disqualifying on its own. And he did show up when it mattered most: in the Super Bowl, he hit all three of his field goals, including a 55-yarder. The decision to bring him back for Year 2 wasn't unreasonable.

Year 2 was worse. He opened the season playing well, then got hurt. When he came back in November against Tampa Bay, he missed three field goals and Deebo Samuel had a visible meltdown on the sideline. The DET game on New Year's Eve (two missed FGs, a missed extra point, six-point loss) was emblematic of how things were going. Final 2024 line: 70.6% (24/33).

The 49ers had Moody compete with Greg Joseph in training camp — fans were briefly hopeful — and Moody won the job. Week 1: he doink'd a 27-yarder off the upright, then had a 38-yarder blocked. Kyle Shanahan's sideline reaction was something I hadn't seen from him before. The release came shortly after. Fans had been wondering why it hadn't happened sooner.

2. The Research: Can We Actually Measure Kicker Skill?

2.1. Is Field Goal Percentage Good Enough?

Long intro, I know — but it sets up the research nicely. I've written before about the difficulty of evaluating linebackers using conventional stats. Kickers have the same problem, maybe worse.

There's one award per conference at Pro Bowl, which means it's essentially a popularity contest. PFF has grades, but they're subjectively assigned and the methodology isn't disclosed. And the most common stat — field goal percentage — has a well-known flaw: it ignores how hard each kick was.

A kicker who converts 10 out of 10 twenty-yarders is not in the same category as one who converts 9 out of 10 fifty-yarders. And yet FG% treats them the same. Moody's replacement Pineiro was described this week as "the third-most accurate kicker in NFL history" — which is a textbook example of this bias at work.

You might say: fine, just adjust for distance. But even that's not enough, because of two issues the paper focuses on:

• The same distance can have wildly different difficulty depending on conditions — weather, wind, temperature, altitude, surface type, etc. Adam Vinatieri's 45-yarder in a blizzard during the Tuck Rule Game was not the same kick as a 45-yarder in a dome on a clear day.

• Made vs. missed is a binary, but kick quality is a spectrum. Justin Tucker's game-winning 43-yarder that split the uprights by 0.15 yards is not the same quality of kick as one that doinks in off the upright.

Same distance, wildly different difficulty or quality. FG% flattens all of this into one number. If you actually want to evaluate kicker skill — separating what a kicker controls from what is situational — you need something more granular.

2.2. Enter: Doinkalytics

Presented at the MIT Sloan Sports Analytics Conference in 2025, this paper introduces two new metrics:

• STUD+ (Split-The-Uprights Difficulty): A situational difficulty score — what's the probability that this specific kick gets made?
• Command+: A quality score — where did the kick pass through the uprights, and how consistently does this kicker hit that location?

Combined, they produce a two-dimensional kicker evaluation: how hard was the kick × how well was it executed. The paper calls the whole framework "Doinkalytics" — a portmanteau of "doink" (the crossbar sound that haunts every kicker's career) and "analytics."

3. The Metrics in Detail

3.1. STUD: What's the Probability This Kick Goes In?

The researchers trained a machine learning model on 7,635 outdoor field goal attempts from 2014–2024. The inputs: distance, wind speed, temperature, precipitation, surface type (grass/hybrid/turf), altitude, and whether the ground was frozen. The output: an estimated success probability for any given kick configuration.

[For the non-stats people — here's the intuition:]

Imagine you had data showing that FGs in clear weather succeed at 90% while FGs in rain succeed at 85%. You'd reasonably infer rain hurts by about 5%. Now expand that to all the variables above, feed everything into a model, and you get a formula that can estimate "given these exact conditions, what percentage of kicks at this distance would go through?"

The model was trained on 75% of the data and validated on the remaining 25% — checking whether kicks it predicted would land at, say, 60% probability actually succeeded at roughly that rate.

The result is the chart below — x-axis is distance, y-axis is predicted success probability, with red representing a dome and blue representing the worst outdoor conditions.

Predicted FG success probability by distance and conditions. Red = dome; blue = worst outdoor conditions (from paper)

The vertical read: in the worst conditions, a 40-yard kick that goes in at ~90% in a dome drops to around 70%. The horizontal read: "a 49-yarder in 12+ MPH winds and –4°C is equivalent in difficulty to a 58-yard dome kick" — which is the actual example the paper uses, referring to a Greg Zuerlein miss in the 2023 season finale.

3.2. From STUD to EPA: Measuring Kicker Contribution

Once you have a success probability for every kick, you can compute something very useful:

EP (Expected Points) = sum of (success probability × 3 points) across all of a kicker's attempts in a season — i.e., the points a league-average kicker would have scored facing the exact same set of kicks.

AP (Actual Points) = field goals made × 3.

EPA (Expected Points Added) = AP – EP = how many more points did this kicker contribute compared to expectation?

Dividing by the number of attempts gives EPA/kick — a per-kick measure of kicker value that adjusts for both opportunity and difficulty.

(This is the same EPA framework used for QBs, where EPA/attempt is a common benchmark. If you follow advanced stats at all, you've seen this before.)

Here's how 2022–2023 kickers plot out, with AP/kick on the y-axis and EP/kick on the x-axis:

AP/kick vs EP/kick for 2022–2023 kickers. FG% only tells you about the y-axis — the x-axis context changes the picture completely (from paper)

A few things jump out (with my obvious 49ers bias):

• Jake Moody was below average even in his better 2023 season
• Robbie Gould was only attempting easy kicks (far right on x-axis), but outperforming even those — legitimately good
• Pineiro (Moody's replacement) looks excellent over this two-year stretch
• Matt Prater and Greg Zuerlein sit on the left side of the x-axis — they were tasked with very hard kicks, and their raw FG% undersells how well they performed
• Chad Ryland (now with the Cardinals) would require you to extend the chart downward significantly

Evaluating kickers by FG% alone means looking only at the vertical axis while ignoring the horizontal. That's how you end up underrating McManus and Boswell, or cutting a kicker who was just unlucky enough to attempt a lot of tough field goals.

3.3. Command+: Where Did It Go, and How Consistently?

The second metric — Command+ — measures kick quality independently of outcome. It has two components:

• Location: where did the ball pass through the uprights horizontally? Closer to center = higher score.
• Consistency: how reliably does the kicker hit the same location across attempts? Less variance = higher score.

The combined Command+ score runs 0–100, with higher values reflecting kickers who split the uprights more accurately and more repeatably.

Command+ scatter plot — Location vs. Consistency for 2022–2023 kickers (from paper)

3.4. Kicker Grade: Putting STUD+ and Command+ Together

The final piece: plot every kicker on a two-dimensional grid with STUD+ on the y-axis and Command+ on the x-axis, then compute a blended Kicker Score — normalized to a 0–100 Kicker Grade.

STUD+ vs Command+ scatter plot. Upper right = elite kickers (from paper)

The correlation between the two dimensions is strong — kickers who are accurate tend to be consistent, and vice versa. But there are interesting outliers: Zuerlein posts a high STUD+ despite low Command+ (maybe especially effective on the hardest kicks?), and Mason Crosby shows the reverse.

The 2022–2023 Kicker Grade rankings:

Kicker Grade rankings 2022–2023. Moody is 4th-worst even in his better season (from paper)

Moody ranks 4th-worst in 2023 — his better season. His Command+ is the main drag. Greg Joseph, who Moody beat out in training camp this summer, is in the worst five. Cairo Santos, who you might remember missing a key kick on Monday Night Football, also makes an appearance.

4. Side Notes

Standard sections in this type of sports analytics paper: proposed applications, limitations, and directions for future work. All of which are present here, and all reasonable.

One note of mild frustration: this methodology hasn't gotten much traction. The authors are primarily NBA-side researchers, which may partly explain the limited NFL pickup. There was a FieldGoalBot account posting live STUD calculations for kicks throughout 2024 — presumably author-run — but it's gone quiet. Would be great to see this kind of framework replace PFF's opaque kicker grading. Unfortunately, that's not where things stand right now.

5. Conclusion

By every measure — the eye test, the conventional stats, the advanced paper, the new metrics — Jake Moody was a bust.

That said, I do understand why Shanahan held on longer than the fan base wanted. What struck me while pulling all this data together is how volatile kicker performance is year to year. Brandon Aubrey, who was a clear All-Pro in 2023, dipped in 2024. Chad Ryland and Blake Grupe (who both ranked in the bottom five as rookies in the paper's dataset) are still on rosters and have improved meaningfully. The logic behind giving Moody a longer runway wasn't crazy.

He was genuinely accurate at Michigan. Something — mental, physical, situational — never quite transferred. Hopefully a new environment helps.

Thanks for reading another long one.

Reference Tweets

Butker's ridiculous 59-yarder to end the first half

The legendary 45-yarder in a blizzard (Adam Vinatieri, Tuck Rule Game, 2002)

Tucker splitting the uprights by 0.15 yards (2022)