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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

  • Rolling Stones’ Top 50

    Rolling Stones’ Top 50

    Tired of draft retconning. So, let’s fight about something else! Rolling Stones published their Top 50 Rock Bands of All Time, and let’s just say, the torches were lit!

    I’m no musicologist, I only play one on YT, but ranking U2 ahead of Pink Floyd is more insane than Syd Barrett [too soon?]

    Remember when Apple ‘gifted’ iTunes’ customers with a free U2 album, and it pissed off so many, people even uninstalled iTunes! Pepperidge Farm remembers…

    Plenty of others on list which I don’t even think I heard a song of [T Rex, Wilco, Cream, Primal Scream…]. I don’t know how they put Stone Roses ahead of The Cure, Black Sabbath, Ramones, CCR while many bands like Alice in Chains, Rage and Rammstein didn’t even make the cut.

    One interesting take is Chicago’s very own Billy Corgan claiming ‘they’ cucked rock.

    Then again he also swears he fucked a reptilian [google it, and prepare to go down the Reddit rabbit hole].

    Anywho, let’s play a game.

    Name the band you listened to the most until you were 21.

    The band you listened to the most in your 30s, 40s, and 50s.

    One band per decade, roughly.

  • Tulip Mania

    Tulip Mania

    At the peak of Dutch Tulip Mania in 1637, a single Semper Augustus bulb cost up to 10,000 guilders, which is estimated to be worth roughly $250,000+ in modern currency. This amount was enough to buy a luxurious mansion on an Amsterdam canal, making it the most expensive bulb in history.

    I know what you’re asking, “What the hell does the Tulip craze [and crash] of 1637 have to do with the NFL?”

    Well, good question, grasshopper.

    Whilst watching the NFL Draft, I was utterly stunned that BJ/Poles drafted yet another TE. I mean, it’s not as if Kmet is a weed. So using the 3rd [69th overall] on TE3 seemed overkill esp when Bears roster a bottom 3rd Dline.

    When I played FF, ppl generally implemented two strategies. You can either spend bigly on prime Kelce/Kittle/Antonio Gates/Gonzales/Gronk, or pass on them altogether and spend on WR1, WR2, RB1, RB2, and throw a measly $buck for a TE1 at the end of draft. “Stars and scrubs.”

    But as Dylan twanged, ‘the times, they are a-changing’.

    Two/Three TE packages [12-13 personnel] is now all the NFL rage. The Pats provided the blueprint with Gronk/Hernandez. McVey has modernized it. Ben Johnson obviously taking it to the next lvl.

    BJ isn’t alone. NYJ started the TE push when drafting TE Sadiq 16th overall. TE Stowers went in the 2nd [54th], Boerkircher 2nd [56th], Klein [59th], Klare [61] then the 3rd RD opened.

    At this point BJ/Poles must’ve thought, “holy shit, I don’t think Roush is going to survive this round.” TE Mania was in full effect. So, with the 69th pick, Bears selected TE Sam Roush – a beastly blocker with drop issues.

    9ers wasted no time in drafting Edge Romello Height very next pick. Puke in same round drafted DT Chris McLellan, Jags DT Albert Regis, Vikings fan fav DT Big Citrus Orange, Cowboys Edge Barham, so it’s not as if Poles couldn’t have drafted Dline. He [or more accurately, BJ] chose TE over dline.

    Stowers, Delp, Klare, Roush and Raridon combined for just nine touchdowns in 2025, while Sadiq had eight by himself. These tight ends are not household names, even amongst the most diehard college football fans.

    Will the risk of these tight end selections this early in the draft be worth it down the road?

    Maybe.

    However, many general managers could be left scratching their heads before these tight ends finish playing on their rookie contracts.


    The TE frenzy wasn’t over. THREE more TEs were drafted in the 2nd after Roush. About TWENTY were drafted by the time Mr. Irrelevant hit the stage. Keep in mind that this TE class wasn’t particularly viewed as strong, and much like toilet paper during Covid, GMs bumrushed the TE aisles to stock up before missing out. Talk about FOMO.

    Rationale.
    As any finance man will admit, the market masks itself in logic, laws, equations, algos – SCIENCE, but all it takes is one ansty townsfolk sprinting to the bank to trigger a run.

    The NFL differs little. Only need ONE NFL GM to ‘overdraft’ or buck ‘consensus’, then the rest of the GMs frantically redraw their boards.

    Bears specifically likely valued TE much more than other teams:

    Kirsten Tanis@Kirsten_Tanis1
    ·May 2
    2025 BEARS OFFENSE

    Plays
    🔸 11 Personnel: 569 (51.6%)
    🔸 12 Personnel: 360 (32.6%)
    🔸 13 Personnel: 94 (8.5%)

    EPA/Play
    🔸 11 Personnel: +0.05
    🔸 12 Personnel: +0.08
    🔸 13 Personnel: +0.32 😳

    In the 2nd half of the season, 12 + 13 personnel accounted for 50% of the plays. So Ben kept ratcheting them up all season

    Considering this, it may not seem that much of an “over reach” despite DESPERATELY needing to upgrade Dline.

    TE trend makes sense in the macro as well. The NFL is a punch, counter-punch kinda league. Os went pass heavy. Ds retired the neck-roll and got smaller and faster. Now QBs struggle mightily [see Kiper’s epic rant to outlaw the Cover 2], ergo many OCs now want to revert to Tank Packages. Surprisingly, tank packages aren’t just to run it down their throats either as studies have shown that teams actually throw more out of 12-13 personnel than expected. Again, punch, counter-punch. DC spots heavy, expects run, that leaves Loveland isolated with a LB – boom.

    It might make sense in the micro too. Packers traded for Parsons. If you’re the Bears with an IFFY LT/C, it may not be the best idea to throw it 40 times a windy game. Instead, just run right at the small fast DE with an achy back.

    This strat can apply to all other teams with a 3-4 Edge who are typically undersized at about 240.

    Will Roush payoff more than a Dlinemen like Big Orange?

    I suppose only time will tell.

    In our 2021 MiB podcast, he made this observation:

    “To the extent you succeed in finance, you succeed by suppressing the limbic system, your system 1, the very fast-moving emotional system. If you cannot suppress that, you are going to die poor.”

    Think about what that means every time FOMO rears its head…

    Ultimately, we’re going to have to trust this man over timid draftnerds.

    Let’s hope the gambit turns up roses and not tulips.

  • Zavion Velus Hester Thomas

    Zavion Velus Hester Thomas

    Rd 3, Pick 89: Zavion Thomas, WR, LSU

    When I first heard ‘Zavion’ called, I got excited. I thought the Bears drafted the other Zxavion, Zxavion Harris. A DT with a record. Turns out, Harris didn’t even get drafted because of his red flags. Get on it, Poles!

    My second initial reaction, “Great, another Velus-Cohen special.” Perhaps I’m just an overly traumatized Bear fans, “Tell me where Halas touched you…”

    For any who still doubt that BJ is driving and Poles riding shotgun, this is the pick. So this really is the “in Ben we trust” era.

    “This guy is going to be a weapon,” Bears assistant director of college scouting Francis St. Paul said on Friday. “This is one of the guys that Ben, when he saw the tape, started doing his little rocking and you could tell he was really excited about him.”

    The new kickoff rules have actually pushed a lot of prospects with return skills up the boards making iffy HBs, scatbacks and hybrid WRs much more viable than in previous years. Drafniks hadn’t factored this much into their mocks, as such, they made Zavion Thomas a 7th RDer or priority UFDA;

    Nevertheless, actual GMs and coaches obviously covet starting field position much more.

    Silvy@WaddleandSilvy

    Our friend @FieldYates told us a great story about Zavion Thomas. Field didn’t have him in his top 150. Someone called him and asked why. That person told him that Thomas would eventually be a third round pick. And it wasn’t from someone w/ the #Bears.

    Teams would kick it out of the back of the endzone because that’s what the math dictated. Roughly 23% of kickoffs were returned. That’s not much value for a returner. They changed the rule to punish teams that booted it out. Suddenly coaches didn’t want to cede a measly extra 5 yards because it changed the winning/losing math. This dramatically boosted returns from 23% to about 70%, or as Hoge relayed, about 70 chances to create a big play per season.

    If Zavion Thomas can gift the O an extra 5-7 yds per drive, that alone might be worth the pick. Think about how some clutch Devin Durvernay returns changed momentum and even a win or two.

    An extra 5-7 yards could be the difference between a short shanked punt which only nets 20 yds, or turning a 60 yd FG attempt into a 53 yder to tie/win the game.

    That’s not even accounting for the sky in the pie scenario where Thomas plays more like the OTHER Chicago returner named Devin.

    Ben Johnson obviously calculated the risk to be worth it. Something else to consider. Maybe BJ doesn’t see Thomas as a gadget/ speed slot WR. Maybe, just maybe, he sees him more as his Jahmyr Gibbs.

    Or Thomas was ridiculously overdrafted and Velus 2.0…

  • Greetings from Earth 2

    Greetings from Earth 2

    My fellow Bearthen!

    I have slipped through some inter-dimensional portal and have somehow arrived here. I originate from a timeline where the Bears won the Bradshaw coin flip. Where Martin didn’t break McMahon. Where the Bears traded up a measly two spots to steal Aaron Donald. Where Tharris and Mike Brown stay healthy, and Lovie keeps pounding the rock with Thomas Jones, thus becoming the first AF American HC to win a SB.

    Where Mahomes, not Trubisky, was selected, and the double-doink never doinked because, well, Da Bears’ Mahomes-Mack-Attack lead the SB charge. M&Ms even pumped out a special Bears’ edition which naturally we ate up [puns are still a thing on Earth 2.]

    SB Shuffle VI with Mahomes and Mack doing the Kid-N-Play was epic! something my grandchildren will cherish.

    However, I am dismayed to see NONE of this transpired on this Earth. For that, I offer my condolences. How a team can land Butkus and Sayers in the same draft and STILL not win a SB is truly a cosmic outlier; tbh one timestream in the multiverse must be the Steven Baldwin of Earths, and I am eternally grateful that it is YOURs and not mine. Whew.

    On that note, I will relay how the Bears’ Draft 2026 unfolded on Earth 2.

    Bears’ draft picks 2026:

    Rd 1, Pick 25: DE Keldrick Faulk
    Rd 2, Pick 57: SS Emmanuel McNeil-Warren
    Rd 3, Pick 69: DT Tyler Onyedim
    Rd 3, Pick 89: C-IOL-T Trey Zuhn III
    Rd 4, Pick 124: CB Malik Muhammad
    Rd 5, Pick 166: WR Kendrick Law
    Rd 6, Pick 213: DT Jordan van den Berg

    Rd 1, # 25 DE Keldric Faulk. Allen is picky, and Faulk is one of the few DEs who actually fits his mold. The GM on Earth 2 isn’t counting on an old Jarrett, schizo Dexter, Motivated Dayo [coming off an achilles] or Turner [coming off a torn ACL] to magically become elite and improve a terrible Dline which can neither stop the run or rush the QB.

    Rd 2, #57 SS Emmanuel McNeil-Warren. Yes, Still needed a S in Earth 2, and yes, many over here likewise mocked EMW to Bears at #25, so fantastic value that fills a need. No-brainer.

    RD 3, #69, DT Tyler Onyedim actually fell 2 spots to Bears. Can never roster enough Dline, right? Well, at least that’s what Bears in Earth 2 believe. On Earth 1, apparently, Bears can never roster enough TEs.

    RD 3, #89 C-IOL-T Trey Zuhn III. Shockingly, the Bears on Earth 2 also needed a C, except on our planet, Dalman didn’t retire but tragically died in a stand-fucking orgy at Coachella. I guess he really didn’t want to play for the Bears in any timeline. As such, Bears still needed a C, so they pick a 6’6 320 Zuhn. Now, this isn’t exactly a new C since he also played LT, but luckily for Bears, they need that too! Braxton-Benedet-Trapilo are sketchy at best while Thuney isn’t getting any younger. Ergo Zuhn who can sub across the Oline wherever needed.

    RD 4, #124 CB Malik Muhammad
    We’re earth 2, not bizzaro world, so some overlap is natural, and it seems a universal Konstant that Tyrique Stevenson is a bozo who can not be trusted. Some still wanted C Connor Lew to further solidify the trenches.

    RD5, #166 WR Kendrick Law
    BJ must be appeased on any Earth! He saw something in Law – a thick YAC weapon with some return chops. I see in this version the Lions drafted him at #168 as they share the same type as BJ.

    RD 6 #213 DT Jordan van den Berg
    Did I mention that on our Earth Bears stack the trenches? Faulk and Berg at bare minimum spell Motivated Dayo, Jarrett and Sweat, and as such, make them more efficient. Worst case scenario – Dayo busts, Jarret gets old as Turner struggles to find a position while recovering from his torn ACL forcing Faulk and Berg to pick up the slack.

    As Mario Lemieux famously said:
    “Tu rates 100% des tirs que tu ne prends pas.”

    Best case? SB 7 here we come!

  • Draft Wrap ’26

    Draft Wrap ’26

    Bears’ draft picks 2026:

    Rd 1, Pick 25: Dillon Thieneman, S, Oregon
    Rd 2, Pick 57: Logan Jones, C, Iowa
    Rd 3, Pick 69: Sam Roush, TE, Stanford
    Rd 3, Pick 89: Zavion Thomas, WR, LSU
    Rd 4, Pick 124: Malik Muhammad, CB, Texas
    Rd 5, Pick 166: Keyshaun Elliott, LB, Arizona St.
    Rd 6, Pick 213: Jordan van den Berg, DT, Georgia Tech

    UDFA Signings / Invites
    Player, Pos, School

    Beau Gardner LS Georgia
    Caden Barnett G Wyoming [Vanilla Gorilla!]
    Coleman Bennett RB Kennesaw St
    Gabriel Plascencia K SDSU
    Hayden Large TE Iowa
    Jaren Kump C Utah
    Jayden Loving DT Wake Forest
    KC Eziomume CB Tulane
    Mason Murphy OT Auburn
    Miller Moss QB Louisville
    Omari Kelly WR Michigan State
    Skyler Thomas S Oregon State
    Squirrel White WR Florida State

    Tryout Invites
    Dain Walter OT UWL
    Devin Pringle DB UConn
    Jaheim Ward DB Eastern Kentucky
    Josh Kreutz C Illinois
    Terrell Tilmon DE Texas Tech

    SEA ’25 D
    Overall Defensive DVOA: 1st (-24.2%)
    PPG: [1st ]17.2
    YPG: [1st] 267.0
    Pass Defense DVOA: 1st
    Run Defense DVOA: 1st
    Pressure Rate: 3rd (34.2%)
    Takeaways: Tied for 6th (18)


    Bears ’25 D
    Overall Defensive DVOA: 25th (6.1%)
    PPG [23rd] 24.4
    YPG [29th] 361.8
    Pass Defense DVOA: 24th (12.3%)
    Run Defense DVOA: 25th (approx. 10.4% based on 2025 reports)
    Pressure Rate 29th [31.1%]

    Bears’ 25 D sum:

    YPG 361.8 [29th]
    Rush YPG 134.5 [27th]
    Pass YPG 227.2 [22nd]
    PPG 24.4 [23rd]
    Takeways 33 [1st] 23 INTs, 10 FFs
    –Byard 7 INTs, Wright 8TOs, Edmunds 5TOs, Gardner-Johnson 2INTs, 1 FF, Brisker 1 INT.

    TOs, which are notoriously fickle yr-to-yr, were the ONLY factor separating us from laughing stock Ds like Dallas. Bears need to replace approx 24/33 TOs.

    TLDR:

    BJ/Poles declared they were going BPA, and that’s EXACTLY what they did. If they went for need, they would’ve drafted:

    DT Peter Woods [KC drafted him @ 29] or Edge Keldric Faulk [31st]

    Then scooped up S Emmanuel McNeil-Warren in the 2nd [Browns #58th overall]

    Still landed a C in Jake Slaughter at #60 or doubled-down on Dline with DT Tyler Onyedim or DE Keyron Crawford in same range.

    However, they stuck to their tiers, drafted prospects they deemed best BJ/Allen fits, and called it a day.

    Guess we’ll find out if that translates to more wins. Hey, if all else fails, Bears could win gold in flag football.


  • RD 4-7 Draft ’26

    RD 4-7 Draft ’26

    Round 2, Pick 57:Logan Jones, C, Iowa
    Pro Comparison: Seth McLaughlin
    Summary
    Logan Jones anchored Iowa’s Joe Moore Award–winning offensive line and won the Rimington Trophy after logging more than 2,800 snaps as a four-year starter. He shows good athletic traits and excellent consistency in Iowa’s zone-blocking system. Jones likely projects as a center only at the next level and lacks the ideal size and length the NFL typically covets, despite his stellar college career. He’s a savvy, intelligent player who could thrive in a zone or pin-and-pull scheme.

    About
    2025: Unanimous All-American
    2025: Rimington Trophy winner (nation’s top C)
    Strengths
    Excellent feet and athleticism to reach frontside defenders and cut off backside pursuit; smooth mover in space and to the second level.
    Good initial strike in pass protection with the footwork to mirror, clamp and stone defenders on counters.
    High football IQ, consistently setting protections, identifying the Mike and adjusting the point when needed.
    Weaknesses
    Struggles to move head-up defensive linemen in the run game and anchor consistently against power in pass protection.
    Lacks the ideal size and length [30″ arms] NFL teams prefer; combine measurements will be closely scrutinized.
    Smaller pass-protection sample in a run-heavy offense and has shown occasional issues picking up games and exotic blitzes.
    Combine Data
    40-yard dash: 4.90 seconds [Sub 5].
    Vertical jump: 32 inches
    20-yard shuttle run: 4.59 seconds
    Broad jump: 9 feet, 2 inches
    3-cone drill: 7.46 seconds

    Butch Take: I don’t mind this one [despite the Trex factor]. Bradbury was never the long-term answer and Logan Jones may actually supplant him. Iowa has a fantastic record with Oline and TEs. Seems a bit undersized, but BJ/Rouschar covet nimble Cs, and Jones can make blocks others can’t. It should be noted that other IOL/Cs like Slaughter, Hecht, Zuhn and Lew were frequently graded more highly, but hey, THEY didn’t win the Rimington, and I never trust ‘converted’ Cs. Prefer them to be true centers, and Jones is that. C is also notoriously difficult to judge, so I’m going to have to trust BJ knows WTF he’s doing.


    Round 3, Pick 69 (via Rams): Sam Roush, TE, Stanford
    Pro Comparison: Jack Doyle
    Summary
    Sam Roush is a sturdy, reliable tight end who excels as a traditional inline blocker and middle-of-the-field target. A high-achieving student-athlete at Stanford, he has a large catch radius and the strength to run through defenders in the open field. While he may not be the fastest player, his consistent blocking and ability to shield defenders make him a valuable asset in a balanced offense.

    About
    Career: 119 receptions, 1,201 receiving yards, 4 receiving TD
    Family: Two uncles and grandfather played in NFL
    Strengths
    Effective inline blocker who plays bigger than his 250-pound frame.
    Natural hands catcher with a large, reliable catch radius.
    Strong long-strider capable of running through arm tackles in space.
    Weaknesses
    Lacks high-end twitch or explosiveness of elite tight ends.
    Can struggle to create consistent separation against tight man coverage.
    Occasional losses early in reps against highly active edge rushers.
    Combine Data
    40-yard dash: 4.70 seconds
    Bench press: 25 reps
    Vertical jump: 38.5 inches
    20-yard shuttle run: 4.37 seconds
    Broad jump: 10 feet, 6 inches
    3-cone drill: 7.08 seconds

    Butch Take: must admit, this befuddled me. Poles just restructured Kmet. Loveland is obviously TE1, so drafting TE3 at 69 makes lil sense. I can only conclude BJ wanted to make up for Smythe’s 25% snaps [though I read Bears only lined up 8% in 13 personnel. Need to confirm]. Nevertheless, T3 ain’t going to stop Jahmyr Gibbs or sack Jordan Love.

    Round 3, Pick 89: Zavion Thomas, WR, LSU
    Pro Comparison: Rashid Shaheed
    Summary
    Zavion Thomas is an explosive, versatile playmaker who can line up across the formation or contribute as a dangerous return specialist. He relies on elite short-area quickness and precise footwork to create instant separation against man coverage. While he lacks the size to dominate in jump-ball situations, his ability to reach top speed quickly makes him a constant big-play threat in space.

    About
    2025: 41 receptions, 488 receiving yards, 4 receiving TD
    Career: 1,213 receiving yards, 7 receiving TD, 1 rushing TD, 3 return TD
    Strengths
    Reaches top speed in two steps with elite acceleration.
    Precise route runner with twitchy movement out of breaks.
    Dangerous open-field runner with the ability to stack defenders vertically.
    Weaknesses
    Struggles to win contested-catch battles against larger defenders.
    Lacks the size and play strength to be an effective blocker.
    Difficulty separating on deep routes against physical cornerbacks.
    Combine Data
    40-yard dash: 4.28 seconds
    Vertical jump: 36 inches

    Butch Take: Another offensive weapon! [pun intended]. Honestly, my first reaction? “Great, Velus/Cohen 2.0”
    An apologist can argue that we needed a true ‘gadget’ threat. Someone who can take a jet sweep or return to the house, or back off the safeties with 4.28 ludicrous speed. Heck, some comp him to Tyreek Hill, and he’s somehow related to Sweetness.

    I guess Bears can score 50 a game.

    OT. Sat, RDs 4-7

    Jacob Infante@jacobinfante24
    ·28m
    #Bears GM Poles drafting in RD 3:

    • Velus Jones Jr.
    • Zacch Pickens
    • Kiran Amegadjie
    • Sam Roush
    • Zavion Thomas

    Not even gonna bother with best available. GMs usually go off the rails by RD 4 [some earlier, apparently].

    Only ones I maybe want:

    Edge, Dani Dennis-Sutton, Penn State

    DL Gracen Halton, Oklahoma

    DT Zxavian Harris, Ole Miss

    So Poles will likely draft a safety, scatback and water boy.

  • RD 3 Draft ’26

    RD 3 Draft ’26

    Best Available

    16. Jermod McCoy, CB, Tennessee
    34. Garrett Nussmeier, QB, LSU
    45. Keionte Scott, CB, Miami
    46. Dani Dennis-Sutton, Edge, Penn State
    47. Bryce Lance, WR, North Dakota State
    49. Emmanuel Pregnon, OG, Oregon
    53. Domonique Orange, DT, Iowa State

    • Keyron Crawford, Edge, Auburn
    • Elijah Sarratt, WR, Indiana
    • Connor Lew, G, Auburn
    • Zachariah Branch, WR, Georgia
    • Austin Barber, OT, Florida
    • Gracen Halton, DT, Oklahoma
    • Eli Raridon, TE, Notre Dame
    • Caleb Tiernan, OT, Northwestern
    • Chris Bell, WR, Louisville
    • Malachi Fields, WR, Notre Dame
    • Gennings Dunker, OT, Iowa
    • Keith Abney II, CB, Arizona State
    • Oscar Delp, TE, Georgia
    1. Romello Height, Edge, Texas Tech
    2. Daylen Everette, CB, Georgia
    3. Zane Durant, DT, Penn State
    4. Antonio Williams, WR, Clemson
    5. Jake Slaughter, C, Florida
    6. Travis Burke, OT, Memphis
    7. Jonah Coleman, RB, Washington
    8. Sam Hecht, C, Kansas State
    9. Ted Hurst, WR, Georgia State
    10. Davison Igbinosun, CB, Ohio State
    11. Chandler Rivers, CB, Duke
    12. Mike Washington, RB, Arkansas
    13. Chris Brazzell II, WR, Tennessee
    14. Kaleb Proctor, DT, Southeastern Louisiana
    15. Markell Bell, OT, Miami
    16. Malik Muhammad, CB, Texas
    17. Taylen Green, QB, Arkansas
    18. Jaiahawn Barham, Edge, Michigan
    19. Malik Muhammad, CB, Texas
    20. Jalon Kilgore, S, South Carolina
    21. Bud Clark, S, TCU
    22. Jalen Farmer, OG, Kentucky
    23. Will Kacmarek, TE, Ohio State
    24. Sam Roush, TE, Stanford
    25. Kaytron Allen, RB, Penn State
    26. Kyle Louis, Slot, Pittsburgh
    27. Joshua Josephs, Edge, Tennessee
    28. Julian Neal, CB, Arkansas

    UPDATE
    Bears Draft @#69, TE Sam Roush, Standford

    He’s athletic, which apparently is enough