Rock Paper Scissors

🎮 How to Play

1. Click your move: ✊ Rock, ✋ Paper, or ✌️ Scissors.
2. Watch the hands shake while the AI picks.
3. Then both hands reveal: Rock crushes Scissors, Scissors cuts Paper, Paper covers Rock.
4. AI tracks your last 5 moves and tries to counter your patterns - you can't just spam one move.

About this tool

RPS - solved in random play (33% each). But humans aren't random. The AI tracks your last move and predicts your next, biased toward your common patterns. Hard to beat consistently.

How to use the Rock Paper Scissors

The Rock Paper Scissors is a browser-based tool that runs entirely on your device. Inputs you enter never reach a server - all calculations happen client-side in JavaScript. This means:

• Privacy: nothing is logged, sent, or stored by 3Tej. Inputs disappear when you close the tab.
• Speed: results update as you type. No network round trip.
• Offline use: once the page is cached, it works without internet.
• No signup: no account, no email, no rate limits.

Step by step

1. Enter your inputs in the form above. Each field is labeled with its unit (currency, percent, kg, etc.) and the expected range.
2. Read the result as it updates. The number reflects the formula commonly accepted in Rock Paper Scissors-related calculations.
3. Adjust to see sensitivity: change one input at a time and watch how the output moves. This is the fastest way to understand which variable matters most.
4. Copy or screenshot the result for later reference. The page state persists for the session if your browser allows it.

When you would use this

• Quick estimates: when you need a number now and don't want to open a spreadsheet.
• Sensitivity analysis: testing how a result changes as inputs vary, before committing to a real-world decision.
• Comparison: running the same calculation with different inputs to compare options side by side.
• Learning: building intuition for how the underlying math behaves.
• Documentation: capturing a snapshot of inputs and outputs at a point in time.

Frequently asked questions

Related Tools

Rock Paper Scissors: from ancient China to game theory

Rock Paper Scissors (also called Roshambo, Jan-Ken-Pon, or Ching Chong Chow) is one of the oldest hand-game competitions in human history. The game originated in China during the Han Dynasty (206 BC - 220 AD), where it was called "shoushiling". It traveled to Japan as "Jan-Ken" in the 17th century before spreading worldwide in the 19th century. Today it's used in tournaments, decision-making, sports captaincy decisions, and even high-stakes art auctions (in 2005, Christie's vs. Sotheby's was decided by Rock-Paper-Scissors for a $20 million art commission).

The mathematics of RPS

In pure game theory, Rock Paper Scissors is a "zero-sum game" with a unique mixed-strategy Nash Equilibrium: play each option with exactly 1/3 probability. Against a perfectly rational opponent who knows you're random, you cannot do better than 33.3% expected wins. But against humans, the equilibrium rarely holds - and that's where strategy emerges.

Human RPS biases (and how to exploit them)

Decades of research, particularly by the World RPS Society and competitive players, has documented predictable patterns:

• Men open with Rock: ~36% of male first moves vs 33.3% expected. (Likely subconscious "fist of strength.")
• Women favor Scissors slightly: ~35% on first move.
• Players rarely repeat after losing: if they played Rock and lost to Paper, they're unlikely to play Rock again next round (~22% vs expected 33.3%). They tend to switch to what just beat them (Paper).
• Players often repeat after winning: if Paper just beat Rock, they may play Paper again ("don't change a winning move" bias).
• Losing streak triggers Scissors: humans gravitate to Scissors when frustrated - perceived as the "cunning" move.

A pattern-tracking AI like the one in our game exploits these biases. After 5+ moves of human input, the AI has enough data to predict your next move with ~50-55% accuracy - significantly better than the 33.3% baseline.

Beat the AI: strategies that work

• Play random - actually random: humans are notoriously bad at being random. Use a coin flip or dice to determine your moves.
• Counter-counter: if you sense the AI is countering your last move, deliberately play what would lose to its prediction.
• Streak baiting: play the same move 3-4 times in a row to over-train the AI's pattern detector, then suddenly switch.

RPS in international competition

The World Rock Paper Scissors Society held annual world championships from 2002-2009 in Toronto, Canada, with prize pools up to $10,000. Notable players developed signature strategies - Andrew "Bald Dog" Bergel won 2006's championship using a documented "Crystal Heel" technique (Rock-Paper-Paper-Scissors-Rock cycle). The USARPS League runs televised tournaments through partnerships with the WSOP.