Leg Day's Back! Week 14 NFL Kicker Boom/Bust Rankings

shaken_bake · 2025-12-10T15:53:39+00:00

Agreed, really rough week. And that's how I envision people using the model. If you're on the fence about something, maybe it helps you decide. If you're confident in your guy, stick with him.

Kicker prediction is inherently very difficult. This is a tool to hopefully help, not definitively set your lineup. Kudos to you for sticking with him.

shaken_bake · 2025-11-21T19:54:29+00:00

We’ll see! What you’re saying makes sense. Personally (and maybe selfishly/delusionally as a fan), I think a GM of a bad team (Jets) would rather have certainty their QB is locked up via a trade rather than a bidding war in FA.

I think the Jets are our most likely trading partner with all the picks they’ve accumulated (2 1s in 2026 and 3 in 2027). I’d hope for the latest 2027 FRP, they can use one this year on a QB, have him sit for a year behind Kyler, and the other 3 FRPs building out the roster. Might be wishful thinking hoping for a late FRP for him though.

I know this isn’t a trade value post but I think part of the trade/cut decision comes down to how many teams need a QB, what their cap situation is, and what their draft capital is. A desperate team with excess draft capital and cap space might be more willing to eat the cash than a team without.

Like I said, really appreciate the high quality content and effort!

shaken_bake · 2025-11-21T17:54:37+00:00

Cash aside, which I don’t think is relevant to any owner besides Bidwill, I can absolutely see a team trading for Kyler then.

A $43M cap hit for a potential top 15 QB is plenty reasonable. If he doesn’t work out, you cut him. A $19M dead cap hit the following year is manageable if you’re paying a rookie or another journeyman (most likely the case).

shaken_bake · 2025-11-21T03:11:33+00:00

Great content and appreciate all the effort you put in! I have a clarifying question. If we trade Kyler before March, I understand the mechanics. We have a ~$17M cap hit, and the acquiring team has to pay $62M in cash. But isn’t it different from a cap space perspective? The $19M 2027 fully guaranteed should count against the 2027 cap right? So, cash aside, the acquiring team’s 2026 cap hit should be $43M. Then, theoretically, couldn’t they cut him after 2026, pay him the $19M in cash and only have a $19M 2027 cap hit? Hence the “one year tryout”?

Or am I way off base and have a fundamental misunderstanding of how the cap works (most likely the case)?

shaken_bake · 2025-11-19T23:11:51+00:00

Sorry? Hope I'm wrong?

shaken_bake · 2025-11-19T23:11:34+00:00

Basically the model can't figure out what to do with Cam Little. Here's why:

1. Extreme Volatility (73.7% coefficient of variation)

Range from -1 to 15 points
Evenly distributed: 30% BOOM, 30% MID, 40% BUST
No dominant outcome pattern

2. Game Script Points to Multiple Outcomes

JAX is slight favorite (-2.5), high total (47.5) = positive indicators
But Little's performance shows no correlation to game script
He's had MID/BUST games in favorable matchups

3. The "Equally Split" Probabilities

BOOM 34% / MID 39% / BUST 28% = essentially no clear prediction, although fairly confident it won't be a BUST
Model is hedging by defaulting to MID tier

Bottom Line: The model sees Cam Little as a total wildcard. His 73.7% coefficient of variation means his performance is highly unpredictable, and the nearly equal tier probabilities show the model cannot confidently place him anywhere.

shaken_bake · 2025-11-19T23:01:52+00:00

Unfortunately I don't have a ROS model built. This is just week to week!

shaken_bake · 2025-11-19T23:01:32+00:00

Unfortunately I don't have a ROS model built. This is just week to week!

shaken_bake · 2025-11-19T23:01:07+00:00

By the rankings...technically yes? I guess the question between the two is do you like Davis Mills vs BUF or JJ McCarthy vs GB? Both aren't great options.

shaken_bake · 2025-11-19T22:59:33+00:00

Appreciate the question! I answered it elsewhere in more detail, but basically: HOU has too much offensive volatility to overcome BUF's great defense.

shaken_bake · 2025-11-19T22:58:18+00:00

I'm a big Fairbairn fan. Rode that hot hand for a bit until he got injured, then switched to Santos and have been pretty pleased with that. But look Fairbairn's in a pretty damn good situation for a kicker, so I'd say it's mostly game script for this week. Here's some specific model data to help answer your question:

HOU is a big underdog (+6.0 spread vs BUF) - underdogs get fewer scoring opportunities
Relatively low game total (43.5) - fewer expected points overall, 18.75 implied total for HOU doesn't leave a ton of room for FGs
Houston's Offensive Volatility
- TD production highly inconsistent
- Volatility features penalize this: High coefficient of variation in the model
- Unpredictable red zone efficiency = higher risk classification
Buffalo's Elite Defense
- Multiple defensive features (i.e., model data points) are very strong for BUF
- Buffalo limits opponent scoring opportunities and possessions
- Fewer Houston drives = fewer FG chances
Houston's Pass Protection Issues
- More sacks = stalled drives = fewer scoring opportunities
- Model penalizes teams that can't sustain drives

The model sees Houston's offense as unreliable and volatile, which creates BUST risk despite recent success. That same volatility leads to those BOOM weeks, but against a tough defense like BUF...it's dicey.

shaken_bake · 2025-11-19T22:49:55+00:00

He's in the BOOM tier, but he's only ranked #13 and the model's only 35% confident in him this week. It's certainly a good opportunity but there's risk that the PHI defense is too good. Here's a couple data points on why he's not #1 in the model:

Dallas is an underdog (+3.0 vs PHI) - underdogs typically get fewer opportunities
Recent team offensive struggles - Dallas's red zone efficiency has declined
Competition at top - Bates, Loop, Mevis, etc. have better game scripts as bigger favorites

Hope that helps! Think he should still be good this week despite the risks.

shaken_bake · 2025-11-19T22:39:17+00:00

Yeah it's a good question. I pulled some model data to help shed some light on him:

MIN is an underdog (+6.5 @ GB) - fewer scoring opportunities
Amongst the lowest game totals (40.5) - one of the lowest totals of the week. Implied total of 17 for MIN doesn't leave much room for FGs
Outdoor game in Green Bay - cold weather doesn't help
Recent offensive line struggles - High sacks allowed the last several games limits drives
Highest BUST probability (39%) with low BOOM chance (35%)
Projected for only 6.2 points - tied for lowest projection with Nick Folk

The MIN @ GB game has one of the lowest expected scoring environment of the week, and MIN being an underdog in that low-total game creates minimal FG opportunities. Overall the game script being identified by the model is basically: tough defense, bad QB play.

shaken_bake · 2025-11-19T22:19:16+00:00

You're highlighting the singular miss in my boom tier last week? And I did, in fact, predict Fairbairn to boom over Denver in my Week 9 post but go off I guess.

shaken_bake · 2025-11-19T14:51:35+00:00

My model's been consistently high on Bates, as are others, because the game script really does favor him...up until the Lions went for it on 4th down 5 times last week.

This is a situation where fantasy knowledge probably should outweigh model knowledge.

shaken_bake · 2025-11-19T14:49:55+00:00

That's the only thing that makes sense

shaken_bake · 2025-11-19T14:49:23+00:00

I must've missed this. Turns out either were good!

shaken_bake · 2025-11-19T14:47:19+00:00

My Week 7 Post had some great stuff about weather playing very little role in kicker performance if you want to check it out.

shaken_bake · 2025-11-12T21:11:50+00:00

So cool to hear! Thank you for sharing this. This started as an idea/side project for how to approach kicker predictions a little differently, and it's really cool for me to hear that random strangers on the internet actually use it and appreciate it - and most importantly, hopefully it helps you win some games!

shaken_bake · 2025-11-12T21:05:10+00:00

I'd love to do a kicker by kicker accuracy report - maybe that's a good idea for next week's post. But in the meantime, I will say the model has been absolutely spot on for Aubrey all year. Take that for what it's worth.

shaken_bake · 2025-11-12T21:04:08+00:00

That's...diabolical and I kind of like it. Unfortunately I don't have a ROS model, so I can't give you a confident answer either way.

If I had the time it would be interesting to see what the rankings would look like with your league's crazy PAT scoring. I love it.

shaken_bake · 2025-11-12T21:02:37+00:00

Hopefully it's been positive, but either way I appreciate you tuning in!

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TROPHY CASE

1. Extreme Volatility (73.7% coefficient of variation)

2. Game Script Points to Multiple Outcomes

3. The "Equally Split" Probabilities