The Girls Are Fighting (Literally): Athena Brings Live Swordplay to Theatre NOVA 53%

By Angel Delich69%

7/20/2026, 12:26:33 PM

BS Summary: This article contains 22 faulty reasoning types, including Framing Effect, Appeal to Authority, and Attempt to Sell a Product or Service, with Hasty Generalization as the most egregious example at 20.6% saturation with 134 hits. Analysis detected 1,158 faulty-reasoning hits from 649 analyzed words, generating a BS Score of 51.5% and a BS Rank of 53% (10,480 of 21,886 articles). This article is worse (more manipulative) than 52.10% of the article peer group.

ANN ARBOR, Mich.  A razor-sharp, darkly funny duel of ambition and recognition is coming to Ann Arbor as Theatre NOVA presents Athena by Gracie Gardner, a play that drops audiences into the high-stakes world of competitive girls’ Junior Olympic fencing. 
Running July 17–August 9 at Theatre NOVA (410 W. 
Huron St., Ann Arbor), the production follows Mary Wallace and Athena  both 17, both fencers, both training for the Junior Olympics  as their lives intertwine through practice, competition, and the question they can’t quite answer: can they be friends in a world built to make them rivals? 
Live swordplay, story-first stage combat 
Theatre NOVA’s production stars Jen Pan in the title role, alongside Brittany Batell as Mary Wallace and Amanda Buchalter as Jamie, with fight direction by Joe Wright. 
“This cast has some of the most trained stage combatants in the entire southeast Michigan area and I can’t wait for audiences to experience how good and story-driven it can look in a live show,” Pan said. 
Wright and Pan are founders of Theatrica Gladiatoria, a Ypsilanti-based company focused on training and choreography for stage and screen. 
The cast also includes Theatrica Gladiatoria students, including Batell  a 1x certified SAFD Actor Combatant in singlesword with additional training at the Fredericksen Intensive in smallsword  and Buchalter, a 5x certified SAFD Actor Combatant and certified Intermediate Actor Combatant with Fight Directors Canada. 
“The thing about stage combat is that each fight is a mini-story in itself, of trading advantages and disadvantages, strengths and weaknesses, wins and losses,” Batell said. 
Pan added she hopes the show sparks curiosity beyond the theater. 
“I want people who come see this show to discover how cool fights can be and, perhaps, get interested in trying a fencing, stage combat, or martial arts class…If you loved Princess Bride or Game of Thrones, this play is for you. 
Come for the swords, stay for the awkward teenage drama,” she said. 
“Violently tender and ferally-feminine” 
The production is directed by Shelby R. 
Seeley, Theatre NOVA Producing Artistic Director and a Yale-certified director who recently returned from an international Directing Residency at the Banff Centre for Arts and Creativity. 
“The stories I want to tell are violently tender and ferally-feminine, and Athena encapsulates that,” Seeley said. 
“I have pitched this play fifteen times over many years to local professional theatres, and Theatre NOVA is the first theatre brave– or crazy– enough to say yes.” 
Buchalter notes that the swords may draw people in, but the story sticks for different reasons. 
“Fencing is obviously a huge part of Athena, but it’s not what the show is really about,” Buchalter said. 
“Fencing is a vehicle for what building friendships can feel like in a world that tells you everything is a competition.” 
Tickets and venue info 
Performances run at Theatre NOVA, 410 W. 
Huron St., Ann Arbor. 
Tickets are $30 general admission, $25 for ages 65+, and $15 for students (student IDs accepted at the door). 
Tickets can be purchased online at here or in person one hour before each performance. 
Seating begins 30 minutes before showtime. 
Theatre NOVA notes ample free parking and walkable access to nearby restaurants, bars, bakeries, and coffee shops. 
Full performance schedule 
Friday, July 17 at 8 p.m.  Opening Night 
Saturday, July 18 at 8 p.m.  Student Night 
Sunday, July 19 at 2 p.m. 
Friday, July 24 at 8 p.m.  Industry Night 
Saturday, July 25 at 3 p.m. and 8 p.m. 
Sunday, July 26 at 2 p.m. 
Friday, July 31 at 8 p.m. 
Saturday, August 1 at 3 p.m. and 8 p.m. 
Sunday, August 2 at 2 p.m. 
Friday, August 7 at 8 p.m. 
Saturday, August 8 at 3 p.m. and 8 p.m. 
Sunday, August 9 at 2 p.m. 
Copyright 2026 by WDIV ClickOnDetroit - All rights reserved. 
Article reasoning-pattern comparisonThis article: 2.9%Angel Delich: 1.0%WDIV: 3.0%Confirmation Bias2.9%This article: 0.0%Angel Delich: 0.0%WDIV: 0.7%Anchoring Bias0.0%This article: 6.3%Angel Delich: 4.3%WDIV: 3.0%Availability Heuristic6.3%This article: 4.2%Angel Delich: 1.4%WDIV: 0.8%Representativeness Heuristic4.2%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Hindsight Bias0.0%This article: 0.0%Angel Delich: 3.8%WDIV: 1.3%Overconfidence Bias0.0%This article: 20.3%Angel Delich: 11.5%WDIV: 4.4%Framing Effect20.3%This article: 0.0%Angel Delich: 0.0%WDIV: 0.7%Loss Aversion0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.3%Status Quo Bias0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Sunk Cost Effect0.0%This article: 10.0%Angel Delich: 3.3%WDIV: 2.0%Optimism Bias10.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.7%Pessimism Bias0.0%This article: 7.6%Angel Delich: 2.5%WDIV: 6.0%Negativity Bias7.6%This article: 4.3%Angel Delich: 2.9%WDIV: 0.8%Self-Serving Bias4.3%This article: 0.0%Angel Delich: 0.0%WDIV: 0.5%Fundamental Attribution Error0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.3%Actor-Observer Bias0.0%This article: 6.5%Angel Delich: 2.2%WDIV: 0.7%In-Group Bias6.5%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Out-Group Homogeneity Bias0.0%This article: 8.3%Angel Delich: 6.4%WDIV: 2.2%Halo Effect8.3%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Horn Effect0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 1.1%Recency Bias0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Primacy Effect0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Blind-Spot Bias0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Ad Hominem0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Straw Man0.0%This article: 19.7%Angel Delich: 11.6%WDIV: 3.9%Appeal to Authority19.7%This article: 7.6%Angel Delich: 4.0%WDIV: 0.7%False Dilemma7.6%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Slippery Slope0.0%This article: 2.6%Angel Delich: 0.9%WDIV: 0.3%Circular Reasoning2.6%This article: 20.6%Angel Delich: 10.7%WDIV: 2.2%Hasty Generalization20.6%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Red Herring0.0%This article: 1.8%Angel Delich: 2.8%WDIV: 0.6%Bandwagon1.8%This article: 8.3%Angel Delich: 7.7%WDIV: 3.5%Appeal to Emotion8.3%This article: 0.0%Angel Delich: 0.0%WDIV: 0.5%Begging the Question0.0%This article: 3.2%Angel Delich: 1.1%WDIV: 2.8%Post Hoc (False Cause)3.2%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Tu Quoque0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 1.1%Burden of Proof0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.2%Appeal to Nature0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Composition/Division0.0%This article: 6.3%Angel Delich: 2.1%WDIV: 1.9%Anecdotal6.3%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%No True Scotsman0.0%This article: 2.9%Angel Delich: 1.0%WDIV: 2.1%Ambiguity (Equivocation)2.9%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Middle Ground0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Personal Incredulity0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.0%Special Pleading0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Genetic Fallacy0.0%This article: 5.7%Angel Delich: 1.9%WDIV: 1.8%Unattributed Quote5.7%This article: 1.8%Angel Delich: 1.0%WDIV: 1.5%Quote-first Misdirection1.8%This article: 12.0%Angel Delich: 7.2%WDIV: 1.7%Biased Writer Voice12.0%This article: 0.0%Angel Delich: 0.0%WDIV: 1.9%Indoctrination0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Angel Delich: 0.0%WDIV: 0.1%Politically Right Leaning Bias0.0%This article: 15.3%Angel Delich: 19.5%WDIV: 1.7%Attempt to Sell a Product or S…15.3%

649 words analyzed.

Speakers

6speakers37%attributed speech409writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 41 words • 100.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 49 words • 0.0% coverageWriter's voice • 5 words • 100.0% coverageWriter's voice • 27 words • 0.0% coverageJen Pan • 37 words • 100.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 45 words • 0.0% coverageBrittany Batell • 27 words • 0.0% coverageJen Pan • 11 words • 0.0% coverageJen Pan • 42 words • 100.0% coverageJen Pan • 12 words • 100.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageShelby R. Seeley • 17 words • 0.0% coverageShelby R. Seeley • 28 words • 100.0% coverageWriter's voice • 16 words • 100.0% coverageAmanda Buchalter • 19 words • 0.0% coverageAmanda Buchalter • 21 words • 0.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageTheatre NOVA • 17 words • 100.0% coverageWriter's voice • 3 words • 100.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWDIV ClickOnDetroit • 9 words • 0.0% coverage
Selected voice

Jen Pan

100%flagged-word coverage
102 attributed words43% of attributed speech55% writer coverage
0%27.5%55.0%Attempt to Sell a Product +46.1 ptsWriter: 6.8%Jen Pan: 52.9%52.9%Unattributed Quote+36.3 ptsWriter: 0.0%Jen Pan: 36.3%36.3%Biased Writer Voice-12.2 ptsWriter: 12.2%Jen Pan: 0.0%0.0%Quote-first Misdirection-2.9 ptsWriter: 2.9%Jen Pan: 0.0%0.0%

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

Loading…
Loading…
Loading…

Analysis

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