Critical Play: Competitive Analysis – Mateo LF

High Level: Gartic, developed by Onrizon (and available on web browsers and mobile platforms), is a casual, multiplayer drawing game in the Pictionary tradition. It’s designed for spontaneous, low-stakes interaction, primarily targeting friend groups, classrooms, or online communities looking for quick and efficient social engagement. Our team’s game, Masquerade, targets a similar audience – players looking for fun and creative expression in a social setting, but approaches that goal differently. Where Gartic channels energy into rapid drawing and guessing, Masquerade expands the expressive medium, inviting players to respond to prompts via text, drawing, emoji, or roleplay, while introducing anonymous authorship and strategic deception.

The core questions become: How do these games support creative expression and social bonding? && What can Masquerade learn from Gartic’s elegant simplicity?

 

Word: “Singer”

 

Pacing: Gartic is all about real-time play: one player draws, and others race to guess the correct word. It’s fast, visual, and synchronous. This directness creates a tight/fast loop between action and reward. Guessers see each other’s attempts live, and the artist adjusts their drawing strategy in real time. In contrast, Masquerade builds social tension through delayed reveal. Prompts are answered anonymously, and guessing happens only after all responses are submitted. This slower, turn-based dynamic favors reflection, bluffing, and strategic disguise. The gameplay loop becomes more deductive than reactive. While Gartic rewards speed and visual clarity, Masquerade rewards inference and creativity across multiple modalities. This divergence reveals two different but valid models of social play: immediate feedback versus delayed attribution.

 

Masquerade Playtest

 

From a game design standpoint, Gartic is a clear example of low-friction onboarding. New players can join a public room, read the round’s topic, and immediately participate. This accessibility is a strength – especially because players don’t need a tutorial to play. However, the game’s reliance on drawing as the sole expressive mode introduces repetition. Once the novelty of the mechanic wears off, player engagement starts fluctuating a bit. Masquerade counters this by layering mechanics: players can respond in multiple forms, and special action cards like Bluff, Wildcard, or Double Down introduce variability (on the strategy side). But with greater depth comes the risk of cognitive overload. Without clear UX support, the complexity could confuse players unfamiliar with social deduction games. The design challenge for Masquerade is to preserve expressive freedom without sacrificing legibility or momentum.

Comment: After our first play test we realized that the pacing of the game felt incongruent with prompts like “answer in a haiku”, as many people thought it was too much to ask. 

 

Addressing the Ethical Question

Ethically, Gartic positions itself as light and low-risk. Its prompts are simple and visual: “cat,” “bicycle,” “saxophone” – and don’t encourage emotional self-disclosure. However, during gameplay, I did observe the emergence of antisocial behavior in the chat. Some players submitted inappropriate/offensive guesses, either as jokes or provocations. The game employs a reactive moderation system – an automated filter deletes flagged language almost instantly. While effective in addressing toxicity, the intervention feels mechanical, at times deleting harmless comments (that might have included words like “shit”) or disrupting the natural flow of conversation.

In contrast, Masquerade bakes ethical complexity directly into its design. Prompts like “What’s your red flag?” or “Describe your ex in emojis” invite humor, but also self-reflection and vulnerability. We face the risk that players may feel misrepresented, exposed, or uncomfortable depending on group dynamics or prompt tone. Here, the ethical stakes are not reactive but proactive. The design must anticipate and frame discomfort rather than simply moderate it after the fact. That means offering clear onboarding, the ability to skip or veto prompts, and setting expectations for tone and consent…

I won!

 

What can we learn from Gartic?

Masquerade can learn from Gartic’s pacing and visual clarity, particularly in the making of complex mechanics such as special action cards, short animations, and a visual timeline during the guessing phase could make pacing more intuitive without dumbing things down. But where Gartic avoids risk by sticking to safe, generic prompts, Masquerade deliberately invites discomfort through personal, vulnerable, and occasionally provocative content. This discomfort isn’t a flaw, it’s a feature, but only when framed by consent. Prompt curation shouldn’t aim to remove tension but to ensure players are opting into it knowingly. A tone calibration system or “safe mode” toggle could help groups set emotional boundaries without compromising depth. Finally, Gartic’s real-time feedback could inspire experimental hybrid rounds in Masquerade that mix live guessing with delayed reveals: adding energy while preserving the game’s core focus on identity, misrecognition, and social deduction 🙂

About the author

I’m a researcher and developer from Ecuador, specializing in human-computer interaction and auditory neuroscience at Stanford’s CCRMA (Center for Computer Research in Music & Acoustics). I’m part of the VR Design Lab and the Neuromusic Lab, where I explore the interection of creativity, well-being, and computation through perception, learning, simulation, and art-making. My work spans from developing multimodal grammars for learning in virtual reality to designing generative agents that simulate social interactions.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.