Don Schlesinger is a blackjack researcher, author and 2015 Blackjack Hall of Fame inductee. He is best known for Blackjack Attack, the SCORE comparison framework and work identifying high-value strategy indexes.
Blackjack Attack
The Blackjack Hall of Fame dates the first edition of Blackjack Attack: Playing the Pros’ Way to 1997 and notes expanded editions in 2001 and 2004. The book developed articles Schlesinger had written for Blackjack Forum and incorporated computer studies commissioned from Norm Wattenberger.
SCORE
Schlesinger developed SCORE, commonly expanded as Standardized Comparison of Risk and Expectation, to compare card-counting games under standardized bankroll and risk assumptions. A SCORE value is meaningful only with its rules, penetration, spread, strategy and risk assumptions; it is not a guaranteed hourly win.
Illustrious 18 and Fabulous 4
The Illustrious 18 are a selected group of high-value playing indexes for counters. QFIT documentation distinguishes the Sweet 16, which removes two ten-splitting decisions, and the Fabulous 4 surrender indexes. The Illustrious 18 are not eighteen card-counting systems and do not replace basic strategy.
Use the work accurately
- Keep edition and simulation assumptions with every result.
- Do not apply shoe-game results to a different ruleset.
- Separate expected value from variance and risk of ruin.
- Recalculate current conditions rather than copying an old profit figure.
Which explanation should you read next?
| Your question | Start here | What it explains |
|---|---|---|
| When can a count change a play? | Illustrious 18 | Threshold direction, count conversion and compatible rules |
| When does surrender help? | Fabulous Four | Surrender eligibility and expected-value comparisons |
| How can two counting games be compared? | SCORE and c-SCORE | Standardization, simulation inputs and hourly-rate limits |
| What happens while waiting to enter? | Back-counting | Observed versus played rounds and access constraints |
These topics answer different questions. Learning a playing index does not supply a betting ramp, and a favorable comparison score does not specify your acceptable loss risk. Read the basic-strategy and count-conversion prerequisites before practicing deviations, then keep the actual rules with any calculation.
A small expected gain can accompany much larger fluctuation
Consider an invented fixed-stake practice model, not a forecast for a real table. Suppose each round has an expected net gain of 0.20 dollars and a standard deviation of twelve dollars, with independent rounds and unchanged distributions. Over one hundred rounds, expectation adds to 100 × 0.20 = 20 dollars. Variances add, so total standard deviation is 12 × √100 = 120 dollars, not twelve hundred.
The standard deviation is six times the expected gain in this example. It is neither a fee to subtract nor a maximum loss. A positive average therefore does not mean a particular hundred-round session is likely to look like a steady twenty-dollar profit. Calculating an exact chance of finishing ahead would require the outcome distribution and additional assumptions.
Under this same simplified model, expectation equals one standard deviation when n = (12 ÷ 0.20)² = 3,600 rounds: both are 720 dollars. This crossover does not guarantee a winning result or define the chance of exhausting a bankroll. QFIT’s simulator definitions describe this kind of expectation-versus-fluctuation measure as N₀ and distinguish it from risk of ruin. Changing stakes, errors, round dependence or game conditions requires a different analysis rather than reuse of this illustrative number.
Sources
Further reading
Research can improve decisions, but no model removes gambling risk.
