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  • GP: the 3rd Dimension is Terror

    GP: the 3rd Dimension is Terror

    You will want to read Pt. 1 and 2 before reading this article. 

    Aggregating the data from sources is a big PITA and so something has to go, and that is me summarizing too much. What I will say is that Pt. 1 looks at the high level deficit and see how many standard deviations we were off from other teams. Pt. 2 is looking at crews and seeing if all crews or some crews contributed to the Bears being bad. 

    Last article, I mentioned that Ben Johnson talked last camp (his 1st camp) about the culture and all the talk was how he was gonna be the Caleb whisperer, and for the most part, Caleb became a better QB under BJ. But that the teams’s OL woes kepts at him, and how he didn’t implement his full suite of tricks, formations and isolated mismatches. And that the Bears were, again, the lowest team in the league at getting flags thrown on their opponents. What we found was contra-examples of ref crews who seemed to be pro-Bears, but many krews called few penalties against Bears oppo. 

    My speculation is that for many years, Nagy and then Floose – Jussie back there – it was amazing to watch them even FIELD an offense. When a hobbled Darnell Mooney is your deep threat, and your OL has Jussie running for his life exactly 2 seconds after each snap, yeah, you ain’t getting a lot of DPI. You need a pocket to begin with to get roughing the passer. 

    I also stated that, organization wide, the Bears were a historically inept organization. Kevin Byard, on the Thanksgiving day meltdown, threw a water bottle at Floose’s head when he tried to address the team after the game. A bad analyst would state that Floose lost the team that day. A good analyst would state that Floose never had the team to begin with. Nobody bought in on that guy. Did you see Hard Knocks? Caleb is openly rolling his eyes having to listen to that guy, that Poles asked the HBO crew for shots of Floose looking thoughtfully at playbooks. As if. 

    So, to really bury this thing, we need some things. Bears against per game / crew non-Bears baseline:  1.00x
    Bears benefit per game / crew non-Bears baseline:  0.79x

    The Bears get penalized at exactly the league-average rate by these same crews. They draw 21% fewer flags on their opponents than those same crews call on other teams’ opponents. The “flag-prone Bears” hypothesis is dead. The deficit lives entirely on the benefit side.

    Per-crew breakdown — sorted by Ben/Base ratio (lowest = most asymmetric against Bears):

    Crew             BG  Crew_G  Baseline  Agst/g  Ben/g  Agst/x  Ben/x
    Scott Novak       5     66    46.06     56.40  21.00   1.22    0.46
    Ron Torbert       4     69    51.30     54.50  23.75   1.06    0.46
    Brad Rogers       6     65    53.36     46.17  29.17   0.87    0.55
    John Hussey       4     67    46.87     55.25  27.50   1.18    0.59
    Tra Blake         3     48    50.14     45.67  30.00   0.91    0.60
    Alex Kemp         2     69    51.28     90.50  32.00   1.76    0.62
    Shawn Hochuli     2     68    52.95     32.00  37.50   0.60    0.71
    Alex Moore        2     16    64.86     61.50  47.50   0.95    0.73
    Carl Cheffers     6     68    49.61     41.50  38.33   0.84    0.77
    Clete Blakeman    5     68    50.88     49.80  40.80   0.98    0.80
    Bill Vinovich     2     69    44.81     39.00  39.50   0.87    0.88
    Adrian Hill       7     65    52.91     37.29  48.71   0.70    0.92
    Clay Martin       5     68    48.10     60.00  45.80   1.25    0.95
    Shawn Smith       2     68    47.34     67.00  47.50   1.42    1.00
    Brad Allen        5     66    43.83     22.60  45.00   0.52    1.03
    Land Clark        4     66    46.73     55.25  49.50   1.18    1.06
    Alan Eck          3     48    45.01     79.00  48.00   1.76    1.07
    Craig Wrolstad    3     69    47.61     42.67  56.67   0.90    1.19

    Sign tests on the new metrics
    Bears Agst > crew baseline:  8 of 18 crews (p = 0.76)  ← right at chance
    Bears Ben < crew baseline:  13 of 18 crews (p = 0.048) ← directional

    This is the real finding. 

    What the test was supposed to distinguish:

    • Flag-prone Bears → Agst > 1, Ben ≈ 1 (both teams take normal flags from these crews; Bears just commit more)
    • Anti-Bears bias → Agst > 1 AND Ben < 1 (asymmetric on both sides)
    • Bears get fewer opponent flags specifically → Agst ≈ 1, Ben < 1 (asymmetric only on the benefit side)

    The data shows the third pattern, decisively. The Bears commit penalties at the same rate every other team does under these crews. The deficit is entirely about opponents not getting flagged when playing them. That kills the lazy “Bears just take a lot of flags” story — it’s empirically wrong.

    Crews where the asymmetry is strongest (sample size matters):

    • Scott Novak (5 games): 0.46x benefit. His non-Bears games average 46 yds against per team; his Bears games give Chicago 21 yds of opponent calls per game.
    • Brad Rogers (6 games): 0.55x benefit. Calls fewer opponent penalties on Bears’ opponents than on others’ opponents.
    • John Hussey (4 games): 0.59x benefit, 1.18x against — the only crew showing the textbook two-sided pattern at meaningful sample size.
    • Adrian Hill (7 games): 0.92x benefit but only 0.70x against — actually treats Bears slightly favorably on the benefit side, and unusually leniently on the penalty side.
    • Brad Allen (5 games, retired after ’23): 1.03x benefit, 0.52x against — he was actively the most pro-Bears crew in the league before he left.

    What this means for the bias hypothesis. 

    With the flag-prone-team alternative now empirically dead, the surviving non-bias explanations are scheme/personnel:

    1. Bears defense doesn’t induce opponent penalties — Bears don’t pressure QBs in ways that trigger holding/false-start rates from opposing OLs. Possible – if you have a quiet front seven. Did the Bears have a poor front seven these years? Ask Waffle.
    2. Bears offense doesn’t draw DPI — fewer deep shots or contested catches, so opposing DBs aren’t put in flag-drawing situations. Plausible for Fields/Bagent/Caleb-rookie eras; harder to credit for Ben Johnson’s 2025 attack.
    3. Bears don’t play teams that commit a lot of penalties — schedule effect. Plausible but the NFC North includes Minnesota, the most-flagged opponent in the league. So let’s toss that one. 

    Can you give a bitch a break?

    Sure. The 0.79x aggregate is striking enough that some combination of those factors has to be doing real work, OR there’s a genuine officiating tilt. Updated Bayesian: with prior 5%, P(asymmetric pattern | bias) ≈ 0.6, P(asymmetric pattern | scheme effects) ≈ 0.20:

    Posterior = (0.6 × 0.05) / (0.6 × 0.05 + 0.20 × 0.95)
              = 0.03 / 0.22 = 0.136

    You have names now, you can hold onto  “the Bears specifically don’t draw flags on their opponents when these particular crews are calling the game,” and that’s a much more salty question. But what you cannot do is show it’s anything more than those crews having a bias towards their back judges, and looking for DPI. We know that the NFL keeps changing what it wants with regards to DPI and how each crew is choosing to implement that across all games is probably the story. Not that the Bears get fucked. 

    Did we sink the Orca? Fuck no. What would the NFL be without third rate journos chumming the water for cheap engagement? Making wild claims that analysis does not support?

    Roughly 14% on bias — modest update, because scheme effects remain a credible explanation for opponents-only deficits. And that’s where I fall. I fall on the team having a shit OL, an anemic DL; the swing is not across all crews. A WIDE variation exists, but when you put in the fix, maybe Goodell only bribes a few crews. If you want to hang on to the anti-Bears argument with your fingernails, you have enough data to die on that hill. But I don’t think so. 

    The next test, which I am not doing because now this is getting to be real work, would be against-side breakdowns by penalty type. If Bears’ deficit in opponent DPI calls specifically tracks with their offensive air-yards profile, scheme wins. If it doesn’t track — if Bears get short-changed on garden-variety opponent holding and false starts that aren’t scheme-dependent — then bias gets harder to explain away. I am pretty certain that were I to dig further into that hole, I would not find that. 

    Well, analysis done. Nothing stands out, esp. when you compare the crews to how they behave across the league. There is no there there. Would it be fun if there was? Maybe. 

    But I prefer the narrative that George is just a massive bonehead and good coaches just didn’t want to come here until Poles realized he was on his way out unless he convinced them to open the checkbook for a Ben Johnson. Which he did. He used Warren to tie to the move. It was savvy politics. Bears need to be a playoff team to help the case w. the Illinois legislature. Being an inept doormat had run it’s course. If they were competent they would have hired real head coaches instead of Trestman and Nagy. And now Ben Johnson is working towards a team that CAN draw DPI and false starts. Well, more on the DPI, not investing anything in the front seven is going to do nothing for drawing false starts. 

    Conclusion: 

    I made my arguments, showed that there is a statistical residual effect that crap journos can point to, but there are many other contradictory truths here that are more suggestive of a deeper problem that NFL officating has, which is that krews are not consistently applying standards to DPI. Is this news, really? Because any true football fan has known this for years. Let me wrap up the findings then, with the risk-reward ratio. If that does not dispel the story then nothing will and you may want to join Irish at breaking into Area 51 because conspiracy is just your groove dude, get a Q-Anon tshirt. 

    Here is what you have to believe to think this is a real directive: The NFL risk – if any of these krews,made up of SEVEN men plus a dedicated reply official tied to that crew in New York – if any of those guys get a hankering to talk to the Guardian or Intercept about this, you blow the league up. Goodell better have a Deadpool class assassin at the ready since fucking a major market like Chicago will gain you all kinds of 2nd rate journalists picking up the story once the first-rate ones open that gate. 

    The reward: One flag per game. Either holding on the oppo OL or OPI on their wideouts. You have to imagine a conversation that singles out 10 of 15 crews, because the NFL psych profile won’t risk it on the other five, and you say to them “don’t call MORE penalties on the Bears, just DON’T call one penalty on their opponents that you otherwise would have. Don’t go more than one, or the stats will start to look too bad, just one flag and then go back to being a fair ref. Maybe you just need the line judge or the back judge and not the whole crew. You have heard of point shaving, this is penalty shaving. 

    What does that buy you in terms of W-L? A single flag? Almost nothing. It’s so improbable to change a game the math isn’t worth showing. So, you risk the state of the whole league to just, perhaps, do a 2nd order point shave? Wouldn’t it be easier to just Art Schliester that shit and get to a QB who needs money? Or a RB? Just about any player is a better risk than a ref, who isn’t paid that well, may be a lawyer himself in real life, and is likely to be much more savvy about leaking the story? Or can we just say that the Bears didn’t draw holding because the DL was not that good at getting sacks? Or the Bears OL didn’t get DPI because for alot of that time their QB was basically another running back? We live in insane times where all manner of insane conspiracies get chummed. It’s sad that it’s coming from people who hold themselves out as experts, because their “expertise” is shit. 

  • GP 2. Electric Boogaloo

    GP 2. Electric Boogaloo

    Pt. 2

    Last article we looked at Warren Sharp and Kristin Tanis assertion that, according to Tanis, the NFL is going out of it’s way to fuck the Bears over. They assertively postulated that the what exists, with no discussion on a possible why. They hate the McCaskeys? They are angry about the team not going to the Ryan family? Nobody is talking about what would be a massive scandal for the NFL, that they conspired to shit on a major market and a very popular team and keep them down. 

    So, what’s going on? Because the net effect of this chum in the water is that it exonerates the McCaskey family for years of utter incompetence as owners. In the week that followed Floose’s Thanksgiving Day meltdown, people like Colin Cowerd let the veil slip and said what Chicagoans have known for years – Ditka was right. The McCaskeys suck. They hired shit coaches, shit staff. Jeff spent years talking about what a viper pit that Halas Hall was. Because it was all true. 

    Saying the NFL hates the Bears feels very propaganda, it feels like a few low life journos on the interwebz just throw that into the water and give Ginny and her boys a great big pass. So that’s my take. But, in order to really push this nonsense off, we are going to go down the Neil DeGrasse Tyson MasterClass path and teach a bit about critical thinking. And that’s to say, give what you may think is bullshit a full shrift. 

    Last article I calculated the SD, Mean, z-score, p-score and looked at the bias, and found what I thought may be reasonable explanations why the Bears opponents don’t get as many penalties as other teams. Why they are always last in opponent yards flagged. Is the fix in? The refs are told, “yeah dude, if a team is playing the Bears, let them get away with some shit. Let them hold, don’t flag them for false starts, just let them go so that the Bears get fucked.” And we found that over the life of the thing, the Bears are down about a single flag, a 10 yard penalty. Had one more flag been called per game across 4 seasons, this would not be a conversation. But that’s enough to look at it, and the data there – at the aggregate level, says wow – Bears suck at drawing penalties, but to really really know if this is a thing the refs are told to do, it helps to know if it was all the krews or just some. And that takes work from nflpenalties.com.

    So, to rise to the metaphor, we have spears in our back and two yellow barrels pulling us up, but we have no choice – if we are gonna kill the crew of the Orca we gotta submerge, we gotta go deep. 

    Bears 2025 game-level data with crews:

    Wk   Opp       Crew               Agst  Benef   Net
    W1   vs MIN    Alan Eck            127     50   -77
    W2   @ DET     Land Clark           50     28   -22
    W3   vs DAL    Clay Martin          41     25   -16
    W4   @ LV      Adrian Hill          60     36   -24
    W6   @ WAS     Alex Moore           84     40   -44
    W7   vs NO     Scott Novak          92     30   -62
    W8   @ BAL     Shawn Smith          79     45   -34
    W9   @ CIN     Clete Blakeman       43     49    +6
    W10  vs NYG    Adrian Hill          25     69   +44
    W11  @ MIN     Brad Rogers          40     15   -25
    W12  vs PIT    John Hussey          83     41   -42
    W13  @ PHI     Carl Cheffers        35     44    +9
    W14  @ GB      Craig Wrolstad       17     55   +38
    W15  vs CLE    Ron Torbert          25     21    -4
    W16  vs GB     Alex Kemp           105     40   -65
    W17  @ SF      Alex Moore           39     55   +16
    W18  vs DET    Brad Rogers          25     35   +10
    WC   vs GB     Adrian Hill           5     65   +60
    Div  vs LAR    Shawn Hochuli        24      5   -19
                                       999    748  -251

    Aggregated to 15 distinct crews:
    Crew              G    Net   Net/g
    Alan Eck          1   -77   -77.0
    Alex Kemp         1   -65   -65.0
    Scott Novak       1   -62   -62.0
    John Hussey       1   -42   -42.0
    Shawn Smith       1   -34   -34.0
    Land Clark        1   -22   -22.0
    Shawn Hochuli     1   -19   -19.0
    Clay Martin       1   -16   -16.0
    Alex Moore        2   -28   -14.0
    Brad Rogers       2   -15    -7.5
    Ron Torbert       1    -4    -4.0
    Clete Blakeman    1    +6    +6.0
    Carl Cheffers     1    +9    +9.0
    Craig Wrolstad    1   +38   +38.0
    Adrian Hill       3   +80   +26.7

    What the breakdown actually tells you:

    The Bears were net negative under 11 of 15 crews. Sign test under H0 of 50/50 per crew: one-sided p = 0.059. Game-level (12 of 19 negative): p = 0.18. Borderline at the crew level, not significant at the game level.

    The pattern is spread across crews rather than concentrated, which is the bias-consistent shape — but with the obvious problem that 12 of the 15 crews only worked a single Bears game, so each “data point” is one game’s noise. You cannot distinguish “Alan Eck has it in for Chicago” from “Week 1 was just a flag-fest” with n=1.

    The most interesting signal cuts the other direction: Adrian Hill worked three Bears games (W4, W10, Wild Card vs GB) and his crew was hugely positive for Chicago — net +80 yards, averaging +27/game. If the league were systematically tilted against Chicago, you’d expect no crew to swing that positive over three games. That single data point is enough to make a “uniform anti-Bears bias” hypothesis hard to defend; it shifts the explanation toward “specific crews have specific tendencies that happened to disfavor Chicago in 2025.” Which is a much weaker claim and frankly an unfalsifiable one without crew-level data across many seasons. We must leave the n=1 noise floor, like Jaws must jam his nose into the wooden planks of the Orca despite the pain. We have found a crew in 2025 that cut Bears-positive. Maybe he didn’t get the memo. Maybe he’s secretly born in Joliet. 

    Does not matter. If Adrian Hill stays positive for the Bears across all four seasons and Alan Eck stays negative, you’ve got something real and specific. If everyone regresses to the mean across years, the 2025 spread was just variance and the cumulative Bears deficit needs a different explanation.

    Cumulative crew-level net (Beneficiary minus Against), Bears 2022–2025:
    Crew              G    Agst   Benef    Net   Net/g    Years
    Alex Kemp         2     181      64   -117   -58.5    23,25
    Scott Novak       5     282     105   -177   -35.4    22-25
    Alan Eck          3     237     144    -93   -31.0    23-25
    Ron Torbert       4     218      95   -123   -30.8    22-25
    John Hussey       4     221     110   -111   -27.8    22-25
    Shawn Smith       2     134      95    -39   -19.5    24,25
    Brad Rogers       6     277     175   -102   -17.0    22-25
    Tra Blake         3     137      90    -47   -15.7    22-24
    Clay Martin       5     300     229    -71   -14.2    22-25
    Alex Moore        2     123      95    -28   -14.0    25
    Clete Blakeman    5     249     204    -45    -9.0    22-25
    Land Clark        4     221     198    -23    -5.8    22,24,25
    Carl Cheffers     6     249     230    -19    -3.2    22-25
    Bill Vinovich     2      78      79     +1    +0.5    23,24
    Shawn Hochuli     2      64      75    +11    +5.5    22,25
    Adrian Hill       7     261     341    +80   +11.4    22-25
    Craig Wrolstad    3     128     170    +42   +14.0    22,23,25
    Brad Allen        5     113     225   +112   +22.4    22-24

    Sign Tests:

    Crew level:  13 of 18 crews negative, 5 positive   → one-sided p = 0.048
    Game level:  45 of 70 games negative, 24 positive  → one-sided p = 0.0077
    Year-over-year persistence (the more diagnostic question):

    Crew              2022      2023      2024      2025
    John Hussey       -5.0(1)   -27.0(1)  -37.0(1)  -42.0(1)   ← all 4 negative, getting worse
    Brad Rogers       -4.5(2)   -38.0(1)  -40.0(1)  -7.5(2)    ← all 4 negative
    Scott Novak       -43.0(1)  -37.0(2)  +2.0(1)   -62.0(1)   ← 3 of 4 negative
    Ron Torbert       -54.0(1)  -66.0(1)  +1.0(1)   -4.0(1)    ← 3 of 4 negative
    Carl Cheffers     +23.5(2)  -28.5(2)  -18.0(1)  +9.0(1)    ← mixed
    Brad Allen        +8.0(2)   +31.5(2)  +33.0(1)    –        ← all 3 positive (retired ’24)
    Adrian Hill       -6.5(2)   -40.0(1)  +53.0(1)  +26.7(3)   ← flipped from neg to strong pos
    Craig Wrolstad    -25.0(1)  +29.0(1)    –       +38.0(1)   ← mostly positive

    What this actually shows.

    The crew-level sign test is borderline (p = 0.048). Game level is solidly significant (p = 0.008). Both consistent with the cumulative finding — the Bears are net-flagged-against across most of the league’s officiating, not just by a few crews.

    But the per-crew sample sizes are still ugly. Most crews worked 2–6 Bears games over four years; the standard error on a single game’s net is ~50 yards, so even Hussey’s −27.8/g across four games has a 95% CI that crosses zero. You cannot, with this dataset alone, say “Hussey calls Bears games unfairly” with statistical confidence — you can only say his four data points all happen to be negative. That’s interesting but it’s not proof. Maybe he’s just a bad ref.

    The two findings that meaningfully update the bias hypothesis, in opposite directions:

    1. Spread-out negative pattern is real. 13 of 18 crews coming out negative isn’t what you’d see from a one-or-two-bad-crews story. It looks like the Bears get net-flagged against by most of the league. That’s the bias-consistent pattern or the structurally-flag-heavy-team pattern; both predict this.
    2. Brad Allen’s three years are the killer counterargument to bias. All three of his Bears games came in clean +30s. Adrian Hill flipped from negative to strong positive over time. Wrolstad is positive. If the league were systematically tilted, you should see no crew running consistently +20 or +30 net for Chicago. The fact that you do — and that “+22.4/g” Allen exists in the same dataset as “−27.8/g” Hussey — is hard to reconcile with uniform institutional bias. It’s much more consistent with crews having different general flag-throwing tendencies, full stop, and the Bears being a flag-heavy team that gets hurt more by high-volume crews.

    Let’s stop there, just for a moment. Last camp, how many times did you read that Ben Johnson brought the full camp to a stop. Huddled everyone up. He was seeing all manner of false starts, route confusion and guys not knowing what page they were on. He admitted he scaled back his offense. Is that consistent with a culture that sucks? A culture that had a lot of skating, a lot of dodging the hard mental work needed? Seemed that way to everyone at the time, because the consistent narrative was that BJ was changing the culture and making people accountable. 

    You, dear reader, are saying “oh GP, you pretentious fuck, you all but admitted your bias, and while there is a counterpoint crew, you just gave your own game away. You showed that there is a large group of crews that don’t like the Bears. McCaskey is exonerated! Let’s salute the brave denziens of Twatter/X with their ability to call out mass fuckery!” 

    Well.. hold on there Cowboy. 

    The cleanest test still missing. 

    What I haven’t done is compare each crew’s Bears-game numbers to that crew’s non-Bears numbers. If Hussey’s crew calls 50 against / 60 for in non-Bears games but 55 against / 27.5 for in Bears games, that’s anti-Bears. If Hussey’s crew calls 55 against / 28 for in every game they work, the Bears are just unlucky to draw the same crew four times. That’s the next layer of analysis, and it’s the one that would actually distinguish “Bears get unfairly flagged” from “Bears get a lot of flags and a few referee crews call a lot of flags.

    That is for article three. Now… go get your shine box

  • Mathing Bears Getting Screwed

    Mathing Bears Getting Screwed

    Let’s begin this story where many stories start; somebody posted some shit on Twitter. Specifically, Warren Sharp stirred it up with this: 

    Now, if you chum the waters from the back of the Orca, sometimes you’re gonna need a bigger boat. Sometimes sharks appear. So let’s be a Great White, shall we, and take a big bite out of this. Because it started to get legs with this Tanis lady picking that ball up and running with it. 

    Tanis goes on to say, “Either the Bears have the worst luck in the history of history, or the NFL is going out of their way to screw over the bears (which seems most likely seeing how they were not awarded the comp picks when Cunningham was hired by ATL). Every team thinks the refs are screwing their team over. However there are stats that show it’s actually happening to the Bears. On a yearly basis. And you can’t say it’s coaching/play calling, bc there have been two (technically three) different head coaches for the bears in the last 4 years. “

    Can you leave that alone? I decided not to. Bears Tax. It’s all that the regs on DBB and DBB2 ever talked about for years, how the NFL hates Chicago and how the Packers get their ring rimmed constantly, esp. in the 4th Q when the fix is sent in on carrier pigeon by Goodell himself. I mean, seriously, fuck that guy. FTP. All of it. 

    So, let’s preface first. There was a DBB reg named Data. Or that’s what we called him. Nice guy, Jeff at DBB used to let him guest post. He used to post “statistics” as conversation starters, and that was all well and good. His idea of statistics was to open up Excel and make a pivot table, and punch some information in, then draw a conclusion from said information, and the debate was on the way. Nice guy. It had no bearing on actual stats, but it was pat on the head nice. I offered to help him with actual statistical analysis, but he shooed me away (politely) and said that he was quite happy in his life doing his tables and drawing his conclusions, and not to mess with his Wizard of Oz magical ways. So, I did not. 

    But a Bears tax won’t be served by a pivot table. We need stats from Yahoo and we need to tranquilize this Lion and open it’s mouth and check it’s teeth. So, in case you were wondering, we shall now engage in ACTUAL STATISTICS.

    GP calculating tip at restaurant for four separate parties

    Our postulation: the NFL or given crews have it out for the Chicago Bears. That a Bears Tax exists, or are these just journalists who are bad at stats doing what the Twatter was made for: stirring the pot. Getting a big wooden spoon and swirling the shit until the scent attracts real sharks. Let’s take a bite of that swordfish on the line being towed. As Khan himself said, Sharp tasks me! He tasks me, and I shall have him!

    Step 1- Summary Stat

    Bears total beneficiary yards (2022-25)

    = 652 + 530 + 794 + 748 = 2,724
    Bears total games = 17 + 17 + 17 + 19 = 70
    Bears yds/game (x_CHI)= 2,724 / 70 = 38.9143

    Step 2 – We need a cross-team reference distribution, For each of the 32 teams I computed cumulative yds/game (total beneficiary yds ÷ total games over the four seasons). What do we see?

    Unweighted mean   x̄ = (1/n) Σ x_i = 1557.0305 / 32  = 48.6572
    Weighted mean     μ_w = ΣY / ΣG = 110,739 / 2,278 = 48.6124
    SS deviations     Σ(x_i – x̄)² = 481.9894
    Sample variance   s² = SS / (n-1)  = 481.9894 / 31 = 15.5480
    Sample SD         s  = √15.5480 = 3.9431

    The two means differ by 0.04 because teams have different game counts (playoff teams play more). 
    Use the unweighted x̄ as the location parameter for the cross-team distribution since the SD is also computed across teams.

    Step 3 – Z-Score
    z = (x_CHI – x̄) / s = (38.9143 – 48.6572) / 3.9431 = -2.4709
    Step 4 – P-values

    Bears weren’t pre-specified. We’re picking them because they’re the outlier. Correcting for 32 teams (i.e., asking “what’s P[some team this extreme]”):

    P(any team z ≤ -2.47) = 1 – (1 – 0.006739)^32     = 0.1946    ≈ 1 in 5
    Bonferroni upper bound = 32 × 0.006739            = 0.2157


    Step 5 – Cumulative deficit interpretation.

    Expected Bears yds at league rate
    = 70 × 48.6124  = 3,402.87
    Actual Bears yds = 2,724
    Deficit = 678.87 yds over 4 seasons
                                          = ~170 yds/season
                                          = ~10 yds/game

    Step 6 – What is this test rejecting?

    The cross-team SD of 3.94 includes both sampling noise and legitimate between-team variation (scheme, pace, QB style). So z = -2.47 against this SD says: “the Bears are far below where teams typically end up, including the noise of 70 games and the spread of 32 different football operations.” Rejecting at p = 0.007 means rejecting “all 32 teams have identical underlying penalty-drawing rates” — a null that was already false on inspection (Minnesota at 57.7, Bears at 38.9, both with 70 games). 

    It does not mean rejecting “no anti-Chicago referee bias.” So we must continue forward.

    A more aggressive test using only sampling variance (treating per-game yds as iid within each team and ignoring between-team scheme effects) would give a smaller p, but the inferential gap to “bias” gets wider, not narrower, because more of the variance gets attributed to legitimate team differences.

    Now we need a Bayesian wrapper on this: P(bias | data) = P(data | bias) × P(bias) / P(data)
                  = P(data | bias) × P(bias) / [P(data|bias)P(bias) + P(data|¬bias)P(¬bias)]

    If your prior P(systematic anti-Chicago bias) is 5%, and you generously assume P(z ≤ -2.47 | bias) = 0.50 vs. P(z ≤ -2.47 | no bias) = 0.195 (the look-elsewhere baseline — under “no bias” we still expect some team to be the outlier ~1 year in 5):
    Posterior = (0.50 × 0.05) / (0.50 × 0.05 + 0.195 × 0.95)
              = 0.025 / 0.21025
              = 0.119

    So the data moves the bias hypothesis from a 5% prior to ~12% posterior. Real movement, but nothing close to “proven.” 

    The data is moderately suggestive, not damning, and the dominant alternative explanation — that the Bears have run an anemic offense for most of this window and bad offenses don’t draw flags — costs nothing extra in plausibility.

    Oh GP, you fucker, you say, sure… Jussie was a shitbird and could not run an offense. Eberflus was so ill-regarded that other teams could see into their setups and adjust. Floose running the Cowboys D in such an inept manner showed his scheme just didn’t get breaks. But what about Caleb? What about BJ? That Tanis broad, she was on it, was she not? She points out that the Bears tax runs between regimes! Ha ha! Checkmate! Take your math and shove it you Grey Poupon eating pretentious math ass!

    Well… hold on there Cowboy. 

    2025 only: League mean 50.47 yds/g, SD 6.83, Bears 39.37. Bears z = −1.63, one-sided p = 0.052, look-elsewhere p = 0.82. So the single season isn’t statistically remarkable — the Bears were lowest, but only by 0.68 yds/g over Buffalo. What makes 2025 important isn’t the single-season significance; it’s that it removes the easiest counter-narrative.

    The asymmetry signal in 2025 is the cleaner one:

    Against/g    Benef/g    Net/g
    Bears             52.58      39.37    -13.21
    Buffalo           50.26      40.05    -10.21
    Denver          61.79      48.21    -13.58
    Detroit         42.24      41.24     -1.00
    SF                36.95      41.42     +4.47
    LA Rams       34.55      51.55    +17.00

    Yahoo has the 2025 Bears 6th in total yds/g (379.2) and 9th in PPG (25.9). I’ll grant top-10. Caleb’s 388 rushing yards is good-not-elite (Lamar’s typically 700–900) but the scramble-draws-flags mechanism is real. And the Bears threw 574 pass attempts — lots of dropbacks where DPI/holding could be called. So you’ve largely killed the “low pace / low pass volume” version of the alternative. What survives:

    1. Scheme-specific: Ben Johnson’s offense is precise and quick-throw oriented — fewer extended plays, fewer deep shots, fewer of the situations that draw DPI and defensive holding. Detroit ran a similar offense and was 3rd lowest in 2025.
    2. Sack rate: Bears took 24 sacks, well below average. Lower QB-hit volume = fewer roughing-the-passer chances. The Caleb-doesn’t-get-hit story works partly against the scramble-draws-flags story.
    3. Pure noise on a one-season sample.Sorry but that’s what it is. 

    Tanis and her 2025 evidence kills the strongest version of the boring alternative (“Bears suck offensively, of course they don’t draw flags “). It does NOT kill the scheme-and-style version, and the look-elsewhere correction still applies to the cumulative case. If I redo the Bayes with prior 5%, P(data|bias) = 0.50, and revise P(data|no bias) down from 0.195 to maybe 0.12 (since the boring alternative is partly defanged):

    Posterior = (0.50 × 0.05) / (0.50 × 0.05 + 0.12 × 0.95) = 0.180

    You’re at ~18% posterior on bias. That’s three-and-a-half times the prior, but it’s still a minority position. The data is suggestive. To push it toward damning, the test you’d want is referee-crew breakdown — if the Bears’ deficit holds across all 17 crews, that’s hard to explain without bias; if it concentrates in three of them, you’ve got something more specific and frankly more interesting than “the league hates Chicago.” So, that is the rabbit hole we must go down in a future article. As Hippy likes  to say, “where the fuck do you find this stuff?”

    Per-game data with referee crews — pulled from the team-by-game pages:

    These give every Bears game with the date, opponent, ref crew, count, yards — both for penalties against the Bears and for penalties against their opponents. 

    So, for article 1 I have tried to show that Jussie + Floose just made for bad years, and I cannot suss out a systemic bias from the data. No way some journos without a quant background can do it. Easier to chum the water than reel the shark in, isn’t it? It took a scuba tank and Quint’s old M1 Garand to finish that monster off. If you are gonna get out there in public and declare a Bears tax exists, then extraordinary claims require extraordinary proof. And so we shall venture forth looking for Part 2 Hypothesis, which we shall call the Billy Butcher hypothesis, being:  “yeah, ok, but I bet some ref crews are rite cunts!”  Onward we go.

    Bear fans fighting refs every Sunday
  • Twitter Tues. WK6

    Twitter Tues. WK6

    So TJ Edwards, Kyler Gordon and Austin Booker are on track to return. Will that make a difference – who knows?

    Sack rate acceptable. It has as much to do with Ben Johnson’s vision and Caleb’s maturity as it does with the big fellas. Either way, reassuring.

    Run game another matter. Bears’ avg 102.3 YPG [24rth].

    However, when one slices out the Caleb scrambles leaving only RBs: 3.4 YPC, 2 TDs. Meanwhile, the Commanders: 156.4 YPG [1st].

    On D, the Bears are giving up a whopping 164.5 YPG [31st]. I blame this mostly on the DTs, but plenty of criticism to go around.

    OTOH the Commanders are in the middle of the pack in defending run at 117 YPG [17th], but do we really expect Swift or Monangai to take advantage?

    These QBs will forever be linked despite Fields not being in his 2nd but 5th yr.

    Apparently Saints are hosting a fire-sale. Unfortunately, none of their vets are appetizing.

    Jets may be another team selling away assets, and HB Breece Hall is at the top of that list.

    Some rumors about Titans’ DT Jefferey Simmons as well.

    In an ideal world, both Hall and Simmons are Bears while Booker finally lives up to hype, but to paraphrase Shawshank, “Halas is no fairytale…”

    Thank Jebus Halas extended Ryan Poles!

    I would love to make fun of Mark Sanchez, but I have done too many dipshit antics whilst drunk to throw any stones. So, I’ll let others do it for me!

  • Rapid Recap: Bears Beat Raiders

    Rapid Recap: Bears Beat Raiders

    Photo courtesy of AP News

    What a WILD game. I think this was the craziest game since that infamous Zona circa 2006.

    Talk about the Raiders letting Bears off the hook!

    Ashton Jeanty rushed for 128 yds, 1 TD, 6.5 per along with TWO rec TDs

    The #1 key was to stop or minimally contain Jeanty; they failed miserably.

    And before you crown his ass, a 33 yr old Raheem Mostert rushed 4 times for 62 yds at a mindboggling 15.5 per carry. They may as well have been Bo Jackson in Tecmo Bowl

    Raiders rushed for a total of 240 yds.7.7 avg yet somehow managed to still lose!

    Bears@Raiders Highlights

    I have way too many thoughts on the game to squeeze into one post but few pertinent notes.

    1. The Bears came out slow. I think they had 97 yds total in the first half despite the D spotting them great field position. Four times they started in Raider territory yet flopped.

    This was a combo of Nagyesque small-ball, Crosby scud, dropped passes, batted throws, miscues and way too many stupid penalties. Kmet especially did his best Kellen Davis impression.


    2. Raiders blitzed over 9 times, which was more in one half than Flus the entire game previously; it rattled Caleb. He looked uncomfortable, making iffy decisions [including on RPOs] and off throws. When he did scramble, his cast didn’t help him much. It was all discombobulated.

    3. The run game stunk! 69 yd total, 2.7 avg. Ben Johnson reverted to Nagy-ball of quick screens, flats and dump-offs near the LOS to essentially act as the defacto run game. Only thing missing was empty-set diamond formation. The results were predictable.

    However, all this seemed to change once Braxton was out [benched?], Benedet moved to LT, and Trapilo debuted at RT in the final drive before the half.

    After the half, the oline seemed to settle-in while BJ became more aggressive.

    It appeared BJ just gave up on the run, putting the game on Caleb’s shoulder, and he responded.

    I wrote in real time that Caleb somehow looks more comfortable in the clutch than at the start of games. It’s truly odd. The ‘scripted’ plays didn’t help much today.

    Caleb is a walking Dickenson quote, “It was the worst of halves, it was the best of halves…”

    Then came the final drive where it was all on Caleb.

    Flus’ Bears would’ve folded like knock-off jeans from a sweat-shop by the 4rth, but the Bears kept clawing back, including the D that forced the Raiders to settle for a FG late.

    The Bears’ final drive itself was bumpy as well. As Data keenly relayed:

    Bears were shooting themselves in the foot from the 1st drive. I’m shocked they had any paws to stand on by the last.

    Nonetheless, Caleb matriculated the ball downfield, and here we gotta give Swift some love as he finished when it mattered most.

    Naturally, it’s the Bears, so they [badly] screwed up the 2-point conversion making it 25-24 Bears.

    At this point, our Angelo-Emery-Pace-Poles trauma triggered as we were cynically expecting the inevitable, no Vaseline.

    Sure enough, the Raiders waltzed down field like Fred Astaire through the Red Sea, reaching the Kicker’s Promised Land which felt like anything near the 50.

    Like Pavlovian losers, I wouldn’t be shocked if thousands of Bear fans hit the parking-lot trying to beat Strip traffic or make one last all-you-can-eat buffet before leaving Vegas buzzed, broke and bitter.

    Then, the unimaginable manifested.
    Daniel Carslon lined up for a seemingly chip-shot 54 yd FG…

    Boom-shaka-laka!

    It only took 4 TOs, a slew of Raider mistakes, 4 Cairo FGs [including two beyond 51], a Tori coffin corner inside the 1 plus a blocked FG for a Bears’ victory!

    Crown em!

  • Twitter Thurs

    Twitter Thurs

    Some interesting twits of the week:

  • Twitter-day

    Twitter-day

    Nothing really to write about for now, so fun tweets!

  • Post-Draft mish-mash

    Post-Draft mish-mash

    Boy, I think this draft is going to split Bear fans

    Camp 1. Obviously BJ in charge now, and as such, he’s finally ushering the Bears into the modern NFL of offense and playmakers

    Camp 2. TE & WR were ‘luxury’ picks, and Ozzy was a big reach at LT in the 2nd. Poles shoulda stayed put and drafted trenches and HB – Draft Day Butch
    ———————-
    This is an informative Greg Gabriel interview [before day 2] cuz it shows how the sausage is made. Some insights.

    1. “James Pierce just doesn’t give a fuck”. No wonder he dropped some. Huge risk
    1. ‘Mike Green was off the board for some teams, so you know he was never on the Bears’ board’
    2. Scourton had 10 sacks at 256 standing up. As DE at 280 lost explosion. 5 sacks
    3. Colt’s Insider msged Greg Gabriel that Bears drafted right TE
    4. ‘Ppl say, ‘trade down’, the Colts would’ve traded up for Colston. Other teams were trying to do same
    5. That praise for Warren and Jeanty trade-up talk was to throw teams off Bears’ target: Loveland
    6. Gabriel contacted DR. Shoulder will be alright. Sounds worse than it really is
    7. OT Ersey is not a fit for Ben’s scheme. He doesn’t move well enough
    8. OT Charles Grant is basically another Kiran project
    9. ‘This was a good draft for oline, just not LT’. Doesn’t think Wright athletic enough for LT
    10. ‘HB is a one-contract position now. Is that value?’
    11. Alfred Collins had INJ concerns. ‘Not one big thing, just a lot of little shit’

    Day 3

    1. Daniel Jermiah comped Ozzy to Rob Havenstein, Gabriel thinks Ozzy like Mike McClinchey
    2. Ozzy has athleticism and bend to play OG, though true, not many 6’8 OGs
    3. “Shemar Turner is a bad MOFO”

    —————–
    Twitts
    ——————
    Courtney Cronin@CourtneyRCronin
    The Bears draft is over. Here’s their 2025 draft class:

    1st – 10th: TE Colston Loveland
    2nd – 39th: WR Luther Burden III
    2nd – 56th: OT Ozzy Trapilo
    2nd – 62nd: DT Shemar Turner
    4th – 132nd: LB Ruben Hyppolite II
    5th – 169th: CB Zah Frazier
    6th – 195th: G Luke Newman
    7th – 233rd: RB Kyle Monangai
    ——————————–
    Adam Hoge@AdamHoge

    [No. 36 – CLE drafts RB Judkins]
    No. 38 – NE drafts RB TreVeyon Henderson
    No. 39 – Bears draft Luther Burden
    No. 41 – Bears trade back

    No. 104 – JAX drafts RB Bhayshul Tuten
    No. 105 – NYG drafts RB Cam Skattebo
    No. 109 – Bears trade back

    No. 147 – SF drafts RB Jordan James
    No. 148 – Bears trade back
    —————————

    Kevin Fishbain@kfishbain

    Bears director of player personnel Trey Koziol on CB Zah Frazier: “We brought him in for a 30-visit and this guy was unbelievable. … Outgoing. Really self-aware. Had to take the long route to the NFL … but we absolutely loved having him in the building.”

    Adam Hoge@AdamHoge

    Summary on CB Zah Frazier from #Bears director of player personnel Trey Koziel:
    Height/length/speed guy. Got his hands on the ball a lot last year. Can turn and track the ball. Good instincts. Fits Dennis Allen’s desire for length/speed on the outside. 30-visit was great. A lot of energy.
    —————–

    Kent Lee Platte@MathBomb

    Ruben Hyppolite was drafted in round 4 pick 132 in the 2025 draft class. He scored a 8.22 #RAS out of a possible 10.00. This ranked 570 out of 3204 LB from 1987 to 2025.
    ——-

    https://twitter.com/BearsBlitznet/status/1916116771032940815/photo/1

    🌊
    @MIKEYSAINRISTIL

    Tyler Shough will officially be the last person drafted to the NFL born in the 1900’s
    —————-

    Butch post-draft musings

    1. BJ wants speed, speed and more speed. I think all draftees were fast for their position or ran a great 10 yd split [short area burst]. BJ wanted to give Caleb some easy completions. DJ/Rome/Kmet aren’t really ‘separators’. Loveland and Burden are.
    2. Shemar at 290 is a 3T. HOWEVER, Allen stated he likes his DEs about 280. Shemar loses 10 pounds, he’s a DE
    3. Bears needed a 3T and DE. Shemar may be both. He played INJed last year [stress fracture], but in ‘23 racked up 6 sacks
    4. Bears either nabbed BPA [Loveland/Burden] or “reached” [Ozzy/Hyppolite]. Add all the tradedowns, and it’s understandable why many fans are ‘wtf?’
    5. Poles may have reached for OT at #56, but look at draft. Another true OT [not projected OG] doesn’t get picked after Ozzy ’til pick #91 Emery Jones who may not fit BJ’s scheme.
      OT Charles Grant went #99, but he’s basically another Kiran project. So essentially the draft went a whole round without drafting an OT after Ozzy #tiers