Master Blackjack Strategy

Understanding optimal blackjack strategy isn’t about luck — it’s about mathematics, probability, and consistent decision-making. Learn the essential principles that reduce the house edge and build real strategic thinking.

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What You'll Learn

Fundamental strategy for every hand scenario
Core probability and expected value concepts
Why certain actions outperform others mathematically
The basics of card counting (strictly for education)

Basic Strategy Chart

The chart below displays the statistically optimal action for every player hand vs. dealer upcard. Select any cell to view an in-depth explanation.

Legend: H = Hit | S = Stand | D = Double (Hit if not available)

Your Hand	2	3	4	5	6	7	8	9	T	A

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Pro Tip: Start by memorizing the decisions for hard hands 12–16 against dealer 2–6. These situations appear often and have the biggest impact on long-term results.

Understanding Probability

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Probability Basics

Blackjack outcomes follow predictable mathematical patterns. Here are the essentials:

52 cards in a standard deck
Each rank appears four times
There are 16 total 10-value cards (10, J, Q, K)
Chance of drawing a 10-value card: 16/52 ≈ 30.8%

This is why a dealer’s 7, 10, or Ace is considered a “strong” upcard — the probability behind their final hand is significantly improved.

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Understanding the House Edge

Even when you make the best decision every time, the dealer maintains a small statistical advantage:

Perfect basic strategy: ~0.5% house edge
Random or “gut feeling” play: ~2–3% house edge
Savings per $1000 wagered with correct strategy: $15–$25

Note: This content is educational. tars.space does not support or encourage real-money gambling. Focus on understanding the logic — not betting.

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Expected Value (EV)

Every blackjack action has an EV — the average result over many repeated plays.

Example: 16 vs Dealer 10

Hit on 16:

P(reaching 17–21): 38%
P(busting): 62%
EV: -0.54 units

Stand on 16:

P(win): 23%
P(lose): 77%
EV: -0.54 units

Both moves are equally bad — which is why 16 vs 10 is known as one of blackjack’s toughest situations.

Under the Hood: How Our WASM Engine Works

tars.space is designed for transparency. Here’s what powers every simulation.

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Fair Shuffle Algorithm

We use the Fisher–Yates shuffle, a mathematically proven method for unbiased randomness:

Start with an ordered deck
For each card from last to first:
- Select a random index
- Swap cards
The result: perfectly uniform randomness

This technique is standard across professional digital card games and ensures true fairness.

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Why WebAssembly?

Most browser games rely on JavaScript. Our engine is compiled to WebAssembly (WASM), offering:

2–20× faster execution than JavaScript
Stable 60 FPS on modern and older hardware
Compact build size for fast loading
Offline functionality after first load
Transparent, auditable Rust source code

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Provably Fair System

Every shuffle and hand outcome is generated using a deterministic, verifiable process:

Cryptographically secure RNG
Shuffle occurs before gameplay starts
No “rigged” sequences — pure math only

Because the algorithm is open and auditable, outcomes cannot be manipulated in any way.