KUOW⁠72%

Ted Cruz + Maria Cantwell: Healing America With Sports? ⁠31%

By Libby Denkmann⁠0% Scott Greenstone⁠0% Catharine Smith⁠0% Gabrielle Healy⁠0%

6/18/2026, 10:43:05 PM

BS Summary: This article contains 11 faulty reasoning types, including Attempt to Sell a Product or Service, Confirmation Bias, and Negativity Bias, with Appeal to Authority as the most egregious example at 19.9% saturation with 27 hits. Analysis detected 155 faulty-reasoning hits from 136 analyzed words, generating a BS Score of 40.4% and a BS Rank of ⁠31% (14,722 of 21,176 articles). This article is better (less manipulative) than 69.50% of the article peer group.

College sports is chaos right now. 
But Texas Sen. 
Ted Cruz and Washington's Maria Cantwell are trying to do something about that with the Protect College Sports Act. 
It just passed the Senate Commerce Committee and heads to the Senate floor next. 
What's in the bill? 
And what do politicians gain when they take on this type of legislation? 
Guest 
Danny O'Neil, Seattle sportswriter and author of The Dang Apostrophe newsletter 
Thank you to the supporters of KUOW, you help make this show possible. 
If you want to help out, go to https://www.kuow.org/donate/soundpolitics/ 
Sound Politics is a production of KUOW in Seattle, a proud member of the NPR Network. 
Our editor is Catharine Smith. 
Our producer is Gabrielle Healy. 
Our hosts are Libby Denkmann and Scott Greenstone. 
Article reasoning-pattern comparisonThis article: 14.0%Libby Denkmann: 1.8%KUOW: 2.6%Confirmation Bias14.0%This article: 0.0%Libby Denkmann: 1.8%KUOW: 1.3%Anchoring Bias0.0%This article: 0.0%Libby Denkmann: 5.5%KUOW: 3.4%Availability Heuristic0.0%This article: 0.0%Libby Denkmann: 1.7%KUOW: 1.2%Representativeness Heuristic0.0%This article: 0.0%Libby Denkmann: 1.1%KUOW: 0.7%Hindsight Bias0.0%This article: 0.0%Libby Denkmann: 2.3%KUOW: 1.4%Overconfidence Bias0.0%This article: 6.6%Libby Denkmann: 13.1%KUOW: 7.4%Framing Effect6.6%This article: 0.0%Libby Denkmann: 2.1%KUOW: 1.0%Loss Aversion0.0%This article: 0.0%Libby Denkmann: 2.4%KUOW: 1.0%Status Quo Bias0.0%This article: 0.0%Libby Denkmann: 0.1%KUOW: 0.2%Sunk Cost Effect0.0%This article: 0.0%Libby Denkmann: 6.4%KUOW: 3.8%Optimism Bias0.0%This article: 4.4%Libby Denkmann: 0.7%KUOW: 1.8%Pessimism Bias4.4%This article: 14.0%Libby Denkmann: 8.6%KUOW: 8.0%Negativity Bias14.0%This article: 9.6%Libby Denkmann: 3.0%KUOW: 2.0%Self-Serving Bias9.6%This article: 0.0%Libby Denkmann: 0.5%KUOW: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Libby Denkmann: 0.1%KUOW: 0.2%Actor-Observer Bias0.0%This article: 0.0%Libby Denkmann: 6.7%KUOW: 2.0%In-Group Bias0.0%This article: 0.0%Libby Denkmann: 0.7%KUOW: 0.5%Out-Group Homogeneity Bias0.0%This article: 8.1%Libby Denkmann: 9.9%KUOW: 2.7%Halo Effect8.1%This article: 0.0%Libby Denkmann: 0.2%KUOW: 0.2%Horn Effect0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.0%Dunning-Kruger Effect0.0%This article: 10.3%Libby Denkmann: 2.5%KUOW: 1.1%Recency Bias10.3%This article: 0.0%Libby Denkmann: 0.4%KUOW: 0.4%Primacy Effect0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.0%Blind-Spot Bias0.0%This article: 0.0%Libby Denkmann: 0.1%KUOW: 0.5%Ad Hominem0.0%This article: 0.0%Libby Denkmann: 0.2%KUOW: 0.3%Straw Man0.0%This article: 19.9%Libby Denkmann: 5.7%KUOW: 4.3%Appeal to Authority19.9%This article: 0.0%Libby Denkmann: 2.6%KUOW: 1.4%False Dilemma0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.9%Slippery Slope0.0%This article: 0.0%Libby Denkmann: 0.2%KUOW: 0.1%Circular Reasoning0.0%This article: 4.4%Libby Denkmann: 5.6%KUOW: 4.1%Hasty Generalization4.4%This article: 0.0%Libby Denkmann: 0.8%KUOW: 0.3%Red Herring0.0%This article: 0.0%Libby Denkmann: 2.2%KUOW: 0.8%Bandwagon0.0%This article: 0.0%Libby Denkmann: 8.7%KUOW: 6.1%Appeal to Emotion0.0%This article: 0.0%Libby Denkmann: 1.3%KUOW: 0.8%Begging the Question0.0%This article: 0.0%Libby Denkmann: 1.4%KUOW: 2.2%Post Hoc (False Cause)0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.1%Tu Quoque0.0%This article: 0.0%Libby Denkmann: 0.1%KUOW: 0.3%Burden of Proof0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.2%Appeal to Nature0.0%This article: 0.0%Libby Denkmann: 0.2%KUOW: 0.2%Composition/Division0.0%This article: 0.0%Libby Denkmann: 2.9%KUOW: 3.3%Anecdotal0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.1%No True Scotsman0.0%This article: 6.6%Libby Denkmann: 0.7%KUOW: 1.4%Ambiguity (Equivocation)6.6%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Libby Denkmann: 0.1%KUOW: 0.1%Middle Ground0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.1%Personal Incredulity0.0%This article: 0.0%Libby Denkmann: 0.0%KUOW: 0.2%Special Pleading0.0%This article: 0.0%Libby Denkmann: 0.4%KUOW: 0.2%Genetic Fallacy0.0%This article: 0.0%Libby Denkmann: 0.5%KUOW: 1.0%Unattributed Quote0.0%This article: 0.0%Libby Denkmann: 0.3%KUOW: 0.8%Quote-first Misdirection0.0%This article: 0.0%Libby Denkmann: 2.4%KUOW: 3.2%Biased Writer Voice0.0%This article: 0.0%Libby Denkmann: 1.1%KUOW: 1.5%Indoctrination0.0%This article: 0.0%Libby Denkmann: 1.6%KUOW: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Libby Denkmann: 0.2%KUOW: 0.2%Politically Right Leaning Bias0.0%This article: 16.2%Libby Denkmann: 1.9%KUOW: 1.3%Attempt to Sell a Product or S…16.2%

136 words analyzed.

Speakers

3speakers36%attributed speech87writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageDanny O'Neil • 11 words • 0.0% coverageKUOW • 13 words • 100.0% coverageKUOW • 9 words • 100.0% coverageSound Politics • 16 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverage
Selected voice

Danny O'Neil

100%flagged-word coverage
11 attributed words22% of attributed speech70% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

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.