‘My mayor Muslim, my bagel’s Jewish’: who’s behind the Knicks chant uniting New York? 29%

By Matthew Cantor0%

6/11/2026, 9:35:05 AM

BS Summary: This article contains 33 faulty reasoning types, including Availability Heuristic, Hasty Generalization, and Ambiguity (Equivocation), with Attempt to Sell a Product or Service as the most egregious example at 13.9% saturation with 137 hits. Analysis detected 1,884 faulty-reasoning hits from 985 analyzed words, generating a BS Score of 39.2% and a BS Rank of 29% (15,679 of 21,887 articles). This article is better (less manipulative) than 71.60% of the article peer group.

The New York Knicks are 3-1 up in the NBA finals, one game away from winning the championship for the first time since the 1970s. 
The mood in New York is electric, the city is strewn with blue and orange, crowds roar outside Madison Square Garden, and  at least last week  a viral chant has become a new unofficial New York City anthem: 
My mayor Muslim 
My bagel’s Jewish 
My Christian Dior 
Knicks in four 
After the team’s loss on Sunday, the last line is no longer viable  no team can now win the series in four games  but the chant has taken on a life of its own thanks to MD Ahnaf Hossain, a 23-year-old Knicks fan who shouted the bars in a Kalshi-branded TikTok video after a Knicks win last week. 
The New York Times called the lines “pure New York City poetry”, but the viral clip has spread far beyond the city limits, with 7.4m views on TikTok and the words appearing on T-shirts and hats. 
Last night Hossain was again filmed on the streets of New York with an updated version, which reflected the reality of the series and one Knicks fan celebrating in the Vatican: 
My mayor still Muslim 
My bagel’s still Jewish 
The pope’s on our side 
Knicks in five 
What is it about these lyrics that has propelled their rise? 
There’s Kalshi’s marketing power, of course  the video appeared on a channel where a Kalshi-branded robot interviews fans, trying to copy the viral formula of the more organic New York man-on-the-street channel Sidetalk. 
There’s the positivity of the lines amid so much toxicity on social media. 
And there’s the easy sense of unity in a world that direly needs it, especially after a mayoral contest in which Zohran Mamdani’s opponents attempted to pit religious identities against each other. 
“I grew up with Jews, Muslims, Haitians, Pakistanis, Bengalis,” Hossain told the Washington Post. 
“I just had to bring everyone together.” 
‘That was a dumbass play’: De’Aaron Fox’s gaffe leaves door open for historic Knicks comeback 
The lyrics also build on hip-hop tradition, says AD Carson, a rapper and associate professor of hip-hop at the University of Virginia. 
“Hip-hop is ultimately as mimetic as any popular cultural product can be.” 
The first line is reminiscent of the Young Jeezy song My President, released in 2008 amid the rise of Barack Obama, which features the line “My president is Black, my Lambo’s blue”; the next year, after Obama’s inauguration, a Jay-Z remix of the song featured similar lyrics: “My president is Black, my Maybach too.” 
The Dior line, as Hossain has acknowledged, references the rapper Pop Smoke’s hit Dior. 
(Both Pop Smoke, who died in 2020, and Jay-Z are New Yorkers.) 
And the final line  a prediction of victory for a favored team in a set number of games  is also a familiar trope. 
“What the four lines are borrowing from  it’s a pretty rich, pretty fertile cultural text,” Carson says. 
What feels like an “offhand viral video moment” reveals “the capacity of rap  even a cappella rap lyrics  to hold information”. 
New York Knicks center Karl-Anthony Towns shoots as San Antonio Spurs guard Stephon Castle defends during an NBA finals game. 
The lyrics also appear to have a direct predecessor: commentators have pointed out that tweets from May and early June use virtually the same language. 
Hossain told the Post he hadn’t seen the tweets. 
But how much would it matter if he had? 
“It’s hard to ever have a conversation like this about culture without discussing the politics of intellectual property,” Carson says. 
“I absolutely believe this is related to mimetic culture, which is to say he may not have seen the tweets and still could be influenced by them in the same way that ‘My mayor is Muslim’ seems to reference My President.” 
But that’s not the only source of controversy over the video. 
Others have pointed out that it is essentially an ad for Kalshi. 
The prediction market company is the source of the original clip, which was reposted by an X account with a bio that promotes the site. 
Kalshi later posted a follow-up interview with Hossain, who said he was drawn to the “iconic green mic”. 
Kalshi gifted him an actual Dior scarf, during the second interview. 
Kalshi has since acknowledged “smart marketing” was behind the video, but remained vague about exactly how the clip was set up, telling Front Office Sports “it was also organic  we didn’t go find him and say, ‘Hey, come talk into this mic.’ 
He found us and then we connected to make the second video.” 
Jeff Hancock, founding director of the Stanford Social Media Lab, says marketing is part of the clip’s success, but it doesn’t explain all of it. 
He sees three ingredients at work: first, it’s all about New York, which remains the country’s biggest media market, second “it fits a moment, it’s funny, it’s engaging, it’s short and simple”. 
And finally, there’s the marketing behind the scenes, typically “some hidden engagement machine in which both the algorithms and some coordinated behavior”  related accounts that may be paid for highlighting and reposting a clip  serve to boost it. 
Of course, this doesn’t always succeed, which speaks to the potency of the chant. 
“They probably tried to do this kind of thing dozens of times, and it’s rare for it to go viral,” Hancock says. 
Hossain himself seems to be taking his newfound celebrity in his stride  he’s mostly focused on the games and the impact they’re having on New York. 
He told the New York Times on Monday: “I think the sportsmanship is bringing a type of love we haven’t seen in the city for a long, long time.” 
Article reasoning-pattern comparisonThis article: 6.1%Matthew Cantor: 1.5%the Guardian: 3.7%Confirmation Bias6.1%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.6%Anchoring Bias0.0%This article: 13.7%Matthew Cantor: 3.4%the Guardian: 3.1%Availability Heuristic13.7%This article: 2.5%Matthew Cantor: 0.6%the Guardian: 1.2%Representativeness Heuristic2.5%This article: 1.4%Matthew Cantor: 0.4%the Guardian: 1.0%Hindsight Bias1.4%This article: 8.6%Matthew Cantor: 2.2%the Guardian: 1.6%Overconfidence Bias8.6%This article: 4.4%Matthew Cantor: 2.3%the Guardian: 6.1%Framing Effect4.4%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.6%Loss Aversion0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.6%Status Quo Bias0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.2%Sunk Cost Effect0.0%This article: 5.3%Matthew Cantor: 2.1%the Guardian: 2.5%Optimism Bias5.3%This article: 3.2%Matthew Cantor: 0.8%the Guardian: 2.1%Pessimism Bias3.2%This article: 8.1%Matthew Cantor: 2.4%the Guardian: 10.4%Negativity Bias8.1%This article: 1.9%Matthew Cantor: 0.5%the Guardian: 1.6%Self-Serving Bias1.9%This article: 2.7%Matthew Cantor: 0.7%the Guardian: 1.4%Fundamental Attribution Error2.7%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.3%Actor-Observer Bias0.0%This article: 3.2%Matthew Cantor: 0.8%the Guardian: 1.3%In-Group Bias3.2%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.7%Out-Group Homogeneity Bias0.0%This article: 2.9%Matthew Cantor: 0.7%the Guardian: 3.2%Halo Effect2.9%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.3%Horn Effect0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.0%Dunning-Kruger Effect0.0%This article: 7.2%Matthew Cantor: 1.8%the Guardian: 1.2%Recency Bias7.2%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.4%Primacy Effect0.0%This article: 4.4%Matthew Cantor: 1.1%the Guardian: 0.1%Blind-Spot Bias4.4%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 2.0%Ad Hominem0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.6%Straw Man0.0%This article: 7.9%Matthew Cantor: 3.9%the Guardian: 3.8%Appeal to Authority7.9%This article: 4.4%Matthew Cantor: 1.1%the Guardian: 1.7%False Dilemma4.4%This article: 4.1%Matthew Cantor: 1.0%the Guardian: 1.1%Slippery Slope4.1%This article: 1.4%Matthew Cantor: 0.4%the Guardian: 0.1%Circular Reasoning1.4%This article: 12.4%Matthew Cantor: 4.6%the Guardian: 6.3%Hasty Generalization12.4%This article: 4.5%Matthew Cantor: 1.1%the Guardian: 0.2%Red Herring4.5%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.7%Bandwagon0.0%This article: 9.8%Matthew Cantor: 4.9%the Guardian: 5.6%Appeal to Emotion9.8%This article: 4.2%Matthew Cantor: 1.0%the Guardian: 0.9%Begging the Question4.2%This article: 11.6%Matthew Cantor: 2.9%the Guardian: 2.9%Post Hoc (False Cause)11.6%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.1%Tu Quoque0.0%This article: 0.9%Matthew Cantor: 0.2%the Guardian: 0.4%Burden of Proof0.9%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.2%Appeal to Nature0.0%This article: 2.5%Matthew Cantor: 0.6%the Guardian: 0.4%Composition/Division2.5%This article: 9.9%Matthew Cantor: 2.5%the Guardian: 3.1%Anecdotal9.9%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.1%No True Scotsman0.0%This article: 12.2%Matthew Cantor: 3.0%the Guardian: 1.6%Ambiguity (Equivocation)12.2%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.1%Middle Ground0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.1%Personal Incredulity0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.1%Special Pleading0.0%This article: 3.7%Matthew Cantor: 0.9%the Guardian: 0.3%Genetic Fallacy3.7%This article: 3.8%Matthew Cantor: 1.2%the Guardian: 1.6%Unattributed Quote3.8%This article: 1.5%Matthew Cantor: 1.3%the Guardian: 1.1%Quote-first Misdirection1.5%This article: 6.8%Matthew Cantor: 2.1%the Guardian: 10.4%Biased Writer Voice6.8%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 1.8%Indoctrination0.0%This article: 0.0%Matthew Cantor: 0.8%the Guardian: 3.1%Politically Left Leaning Bias0.0%This article: 0.0%Matthew Cantor: 0.0%the Guardian: 0.3%Politically Right Leaning Bias0.0%This article: 13.9%Matthew Cantor: 12.4%the Guardian: 1.0%Attempt to Sell a Product or S…13.9%

985 words analyzed.

Speakers

4speakers32%attributed speech670writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 14 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 40 words • 100.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 60 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 34 words • 100.0% coverageWriter's voice • 13 words • 100.0% coverageWriter's voice • 32 words • 0.0% coverageMD Ahnaf Hossain • 14 words • 100.0% coverageMD Ahnaf Hossain • 7 words • 0.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageAD Carson • 12 words • 0.0% coverageWriter's voice • 54 words • 0.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageAD Carson • 18 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 9 words • 0.0% coverageAD Carson • 20 words • 0.0% coverageAD Carson • 41 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 11 words • 100.0% coverageKalshi • 43 words • 100.0% coverageKalshi • 12 words • 100.0% coverageJeff Hancock • 25 words • 0.0% coverageJeff Hancock • 32 words • 0.0% coverageJeff Hancock • 40 words • 0.0% coverageWriter's voice • 14 words • 100.0% coverageJeff Hancock • 22 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageMD Ahnaf Hossain • 29 words • 0.0% coverage
Selected voice

Kalshi

100%flagged-word coverage
55 attributed words17% of attributed speech83% writer coverage
0%50.0%100.0%Attempt to Sell a Product +87.8 ptsWriter: 12.2%Kalshi: 100.0%100.0%Biased Writer Voice-10.0 ptsWriter: 10.0%Kalshi: 0.0%0.0%Unattributed Quote-3.4 ptsWriter: 3.4%Kalshi: 0.0%0.0%Quote-first Misdirection-2.2 ptsWriter: 2.2%Kalshi: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.