The Valkyries’ winning streak is over. It barely dents a stunning first half 68%

By Jane Kenny45%

7/21/2026, 3:30:52 PM

BS Summary: This article contains 26 faulty reasoning types, including Halo Effect, Post Hoc (False Cause), and Ambiguity (Equivocation), with Optimism Bias as the most egregious example at 24.6% saturation with 233 hits. Analysis detected 1,357 faulty-reasoning hits from 948 analyzed words, generating a BS Score of 61.3% and a BS Rank of 68% (6,898 of 21,170 articles). This article is worse (more manipulative) than 67.40% of the article peer group.

The Golden State Valkyries have spent an entire month riding high as the WNBA’s hottest team. 
Until the final five minutes on Monday night. 
The winners of nine straight left the floor with their first loss since June 21 after the Washington Mystics poured in 36 fourth-quarter points and closed on a 22-5 run, spoiling Golden State’s bid for a double-digit win streak heading into the All-Star weekend. 
The late-game collapse frustrated the Valkyries, who led by as many as nine in the final period but were overwhelmed by the Mystics’ size in the 90-82 loss. 
Even so, there’s plenty for Golden State to build on as it enters the break, with Gabby Williams headed to Chicago as a starter and 17 regular-season games left. 
“Really proud of us, honestly, I think that was also a message,” Veronica Burton said postgame. 
“We don’t want this to seep into this All-Star break and leave a bad taste in our month. 
But, I’m really proud of the way we’ve showed up  we’ve competed at home, on the road, we’ve gotten close, we’ve stuck together.” 
The positive spin is warranted. 
The Valkyries are in third place, own the best defensive rating, and have the WNBA’s most productive bench by a solid margin. 
The fact that Monday’s finish felt uncharacteristic may be one of the biggest positives. 
It’s a reflection of how quickly Golden State has established a winning culture. 
In Year 1, a meltdown loss like that would’ve blended into the rest  they lost 13 regular-season games by fewer than 10 points in 2025. 
Now, the expectation, and the sentiment, is clearly different. 
“You don’t win that many games without handling adversity well. 
Today was just sort of a tough one,” Kaitlyn Chen said following her career-high 20-point, six-assist outing. 
“We played four minutes of rough basketball at the end, which is really unfortunate.” 
Monday’s defensive lapse was an anomaly, not necessarily a sign of regression. 
The Valkyries are 0-4 when allowing 90-plus points, but they’ve held opponents below 80 points in more than half of their games. 
Natalie Nakase directs a stingy defensive operation  the Valkyries surrender the fewest points per game and allow the fewest field-goal attempts and the lowest field-goal percentage in the league. 
The Valkyries’ 19-8 start has also validated the organization’s biggest offseason bet: continuity. 
What was viewed as a potential question mark has become a strength, as Golden State returned more players than any team in the league and trusted that internal development and individual offseason leaps would drive its next phase. 
So far, it’s been the team’s advantage. 
Chen, who entered Year 2 signed on a training-camp contract, has become a highly valuable backup point guard and has scored in double-figures 10 times this season  last year she appeared in 24 games and scored 48 total points. 
Janelle Salaun is a leading candidate for Sixth Player of the Year, embracing her Year 2 role as a reserve with the biggest scoring punch off the bench in the league. 
Even Williams, one of the team’s two free-agent additions, is making her career year last season look modest compared to what she has accomplished with Golden State. 
An All-Star for the first time last season while averaging 11.6 points per game for Seattle, she’s now an All-Star starter averaging 14.8 points per game and is playing fewer minutes. 
Despite the positives, the end of the winning streak served as a valuable lesson for a franchise with limited playoff experience. 
Facing the Mystics in back-to-back games provided a glimpse of the adjustments and challenges that could await in the postseason. 
Washington’s late-game adjustments ultimately exposed some of Golden State’s weaknesses. 
The Mystics went bigger, attacked the interior, and overwhelmed the Valkyries physically  forcing Nakase’s team out of a small-ball lineup to close the game. 
The Valkyries allowed 40 paint points and were significantly outrebounded for the second consecutive game. 
They failed to execute a game plan that centered on taking away the low post against one of the league’s biggest and most efficient defensive teams. 
“Usually we’ve been good in those situations because we talk about time and score,” Nakase said postgame. 
“This is something that we can definitely learn from, but we have done well in the past with that.” 
On paper, the Valkyries have one of the easier schedules remaining. 
They’ll see Dallas and New York again, and Minnesota twice, but the other remaining games are all matchups with teams currently ninth or lower in the standings. 
Still, the standings are constantly in flux, and one or two teams getting hot could reshape the playoff race. 
Remember just how much the Valkyries’ season changed after the All-Star break last year? 
Golden State was just outside of the playoff position this time last year. 
Then, All-Star Kayla Thornton suffered a season-ending injury, Golden State welcomed Iliana Rupert and Kaila Charles into the mix, and the real, undeniable stretch in Burton’s Most Improved Player campaign began. 
In the end, the Valkyries squeaked past the Sparks to earn the WNBA’s final postseason berth. 
Now, the Valkyries hold three critical head-to-head tiebreakers over likely playoff teams in the Indiana Fever, Atlanta Dream, and New York Liberty, but also are just 1 1/2 games ahead of the fourth-place Wings. 
After Golden State powered through a two-week journey away from Chase Center to produce the league’s longest undefeated road trip (5-0) in five seasons, finishing in the top four and securing home-court advantage in the first round of the playoffs is Golden State’s ideal scenario  and it’s a goal well within reach. 
Article reasoning-pattern comparisonThis article: 5.2%Jane Kenny: 5.6%The San Francisco Standard: 2.8%Confirmation Bias5.2%This article: 0.0%Jane Kenny: 2.0%The San Francisco Standard: 1.1%Anchoring Bias0.0%This article: 4.1%Jane Kenny: 1.6%The San Francisco Standard: 3.4%Availability Heuristic4.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 1.1%Representativeness Heuristic0.0%This article: 5.9%Jane Kenny: 2.3%The San Francisco Standard: 0.8%Hindsight Bias5.9%This article: 5.7%Jane Kenny: 2.4%The San Francisco Standard: 1.4%Overconfidence Bias5.7%This article: 0.0%Jane Kenny: 4.8%The San Francisco Standard: 6.6%Framing Effect0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.5%Loss Aversion0.0%This article: 3.0%Jane Kenny: 0.8%The San Francisco Standard: 0.6%Status Quo Bias3.0%This article: 4.0%Jane Kenny: 1.1%The San Francisco Standard: 0.3%Sunk Cost Effect4.0%This article: 24.6%Jane Kenny: 12.7%The San Francisco Standard: 2.6%Optimism Bias24.6%This article: 1.9%Jane Kenny: 0.5%The San Francisco Standard: 1.3%Pessimism Bias1.9%This article: 6.2%Jane Kenny: 1.7%The San Francisco Standard: 7.4%Negativity Bias6.2%This article: 6.3%Jane Kenny: 6.5%The San Francisco Standard: 2.0%Self-Serving Bias6.3%This article: 7.3%Jane Kenny: 2.8%The San Francisco Standard: 0.9%Fundamental Attribution Error7.3%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.3%Actor-Observer Bias0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.7%In-Group Bias0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.2%Out-Group Homogeneity Bias0.0%This article: 18.1%Jane Kenny: 9.4%The San Francisco Standard: 4.0%Halo Effect18.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.2%Horn Effect0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.0%Dunning-Kruger Effect0.0%This article: 4.2%Jane Kenny: 2.7%The San Francisco Standard: 1.2%Recency Bias4.2%This article: 1.7%Jane Kenny: 0.5%The San Francisco Standard: 0.2%Primacy Effect1.7%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Blind-Spot Bias0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.4%Ad Hominem0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Straw Man0.0%This article: 5.1%Jane Kenny: 1.4%The San Francisco Standard: 3.4%Appeal to Authority5.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 1.2%False Dilemma0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.9%Slippery Slope0.0%This article: 5.4%Jane Kenny: 1.4%The San Francisco Standard: 0.2%Circular Reasoning5.4%This article: 7.1%Jane Kenny: 2.9%The San Francisco Standard: 5.3%Hasty Generalization7.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Red Herring0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.4%Bandwagon0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 4.5%Appeal to Emotion0.0%This article: 0.5%Jane Kenny: 0.3%The San Francisco Standard: 0.6%Begging the Question0.5%This article: 8.6%Jane Kenny: 5.6%The San Francisco Standard: 2.2%Post Hoc (False Cause)8.6%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Tu Quoque0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.4%Burden of Proof0.0%This article: 1.1%Jane Kenny: 0.3%The San Francisco Standard: 0.2%Appeal to Nature1.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.2%Composition/Division0.0%This article: 1.8%Jane Kenny: 0.5%The San Francisco Standard: 3.4%Anecdotal1.8%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%No True Scotsman0.0%This article: 8.1%Jane Kenny: 2.2%The San Francisco Standard: 1.5%Ambiguity (Equivocation)8.1%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.0%Gambler’s Fallacy0.0%This article: 2.0%Jane Kenny: 0.5%The San Francisco Standard: 0.1%Middle Ground2.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Personal Incredulity0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Special Pleading0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Genetic Fallacy0.0%This article: 1.7%Jane Kenny: 0.5%The San Francisco Standard: 1.3%Unattributed Quote1.7%This article: 1.9%Jane Kenny: 0.5%The San Francisco Standard: 1.1%Quote-first Misdirection1.9%This article: 1.7%Jane Kenny: 3.3%The San Francisco Standard: 5.4%Biased Writer Voice1.7%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 1.2%Indoctrination0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.2%Politically Left Leaning Bias0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Jane Kenny: 0.0%The San Francisco Standard: 2.2%Attempt to Sell a Product or S…0.0%

948 words analyzed.

Speakers

3speakers13%attributed speech823writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 6 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 44 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageVeronica Burton • 16 words • 100.0% coverageVeronica Burton • 18 words • 100.0% coverageVeronica Burton • 24 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageKaitlyn Chen • 17 words • 0.0% coverageKaitlyn Chen • 14 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 40 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageStephanie Nakase • 17 words • 0.0% coverageStephanie Nakase • 19 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 53 words • 0.0% coverage
Selected voice

Veronica Burton

100%flagged-word coverage
58 attributed words46% of attributed speech93% writer coverage
0%17.5%35.0%Quote-first Misdirection+31.0 ptsWriter: 0.0%Veronica Burton: 31.0%31.0%Unattributed Quote+27.6 ptsWriter: 0.0%Veronica Burton: 27.6%27.6%Biased Writer Voice+27.6 ptsWriter: 0.0%Veronica Burton: 27.6%27.6%

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.