Kelly Criterion is bet size optimized to maximize long-run growth without ruin. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0421, within the Probability family. The core principle: bet size optimized to maximize long-run growth without ruin. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Bet size optimized to maximize long-run growth without ruin.
Plain-English Definition
Bet size optimized to maximize long-run growth without ruin.
Feynman Explanation
Bet too big and you blow up. Bet too small and you starve.
Core Principle
Bet size optimized to maximize long-run growth without ruin.
Mechanisms
Pending editorial review.
Bet size optimized to maximize long-run growth without ruin.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Sizing big bets so the org can survive losing them.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Bet too big and you blow up. Bet too small and you starve.
Examples
- Position sizing in investing and in capital allocation.
- Sizing big bets so the org can survive losing them.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
This is one of the elements leaders describe as a values gap. It is a payoff gap. The mechanism underneath it is straightforward: bet size optimized to maximize long-run growth without ruin. You can recognize it in the field by its signature: bet too big and you blow up. Bet too small and you starve. Every element in the Cognition dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, sizing big bets so the org can survive losing them. It is amplified whenever sizing big bets so the org can survive losing them. Inside organizations that shows up as sizing big bets so the org can survive losing them. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to size every major bet by survivability, not just expected value. Watch for it at the boundaries: handoffs, promotions, incident reviews, and budget cycles are where this element gets its power.
Famous Experiments
Pending editorial review.
Design Principles
- Size every major bet by survivability, not just expected value.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Size every major bet by survivability, not just expected value.
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Ignoring general statistics in favor of specific, vivid information.
Posterior = (likelihood × prior) / evidence.
Update beliefs in proportion to the strength of new evidence.
Start with a prior; update with new evidence.
Novices experiencing early success, often due to variance and small samples.
High-impact, hard-to-predict, retrospectively explainable events.
Striking pattern that is statistically expected in large samples.
Reasoning in distributions — ranges and probabilities — rather than points.
Average outcomes across the population differ from outcomes across time for one person.
A rough calculation using order-of-magnitude reasoning.
In quantum mechanics, certain pairs of properties cannot both be precisely known.
We ignore sample size when judging probability.
Where Kelly Criterion is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- EssayGoodhart's Law in the Real World
How measurable proxies capture judgment.
- EssayThe Perverse Incentives Hiding in Your KPIs
Cognitive shortcuts turned into scorecards.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
Questions about Kelly Criterion
- What is Kelly Criterion?
- Kelly Criterion is bet size optimized to maximize long-run growth without ruin. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0421, within the Probability family. The core principle: bet size optimized to maximize long-run growth without ruin. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of Kelly Criterion?
- Sizing big bets so the org can survive losing them. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0421).
- How is Kelly Criterion exploited?
- Sizing big bets so the org can survive losing them.
- How do you design around Kelly Criterion?
- Size every major bet by survivability, not just expected value.
- Which behavioral dimension does Kelly Criterion belong to?
- Kelly Criterion is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Probability", class "Mental Model". Its permanent identifier is HBT-COG-0421 and its evidence grade is B.