Optimal Strategy in Darts Cricket

The Game

Cricket is one of the most popular darts games played in bars, leagues, and tournaments worldwide. Two players take turns throwing three darts per turn at a board with seven targets: the numbers 15, 16, 17, 18, 19, 20, and the Bullseye. The objective is to "close" all seven targets before your opponent while accumulating at least as many points.

Each target requires three marks to close. A single hit scores one mark, a double scores two, and a triple scores three — so a single triple can close a number in one dart. Once you close a target that your opponent has not yet closed, every additional hit on that number scores points equal to its face value (15 points for 15s, 20 points for 20s, 25 for Bullseye). Your opponent can stop the bleeding by closing that number themselves.

To win, a player must close all seven targets and have a score equal to or greater than their opponent's. This dual requirement creates a deep strategic tension: do you focus on closing numbers quickly, or do you try to build a scoring lead first? How you balance offense and defense — and when you switch between them — is the central question of cricket strategy.

Frongello's Framework

In 2018, Andrew Frongello published a systematic analysis of darts cricket strategy that defined 17 distinct strategies based on three parameters:

• Lead threshold — How far ahead in points you need to be before switching from scoring mode (building a lead) to covering mode (closing numbers).
• Extra darts — When you cannot close a number with the remaining darts in your turn, redirect those extra darts toward scoring on an already-closed number instead of wasting them.
• Chase — Prioritize closing numbers your opponent has already closed, aiming to neutralize their scoring opportunities.

By simulating 20,000 games per matchup between every pair of strategies in a round-robin tournament — at both equal skill and with a skill advantage — Frongello arrived at four key findings:

1. Score first, then cover — Build a point lead before shifting focus to closing numbers. S2 (“take any lead, then cover”) is optimal for equally skilled opponents. Purely defensive strategies consistently lose.
2. Use extra darts when more skilled — If you are the stronger player, S6 (S2 + extra darts) outperforms S2 by extending the game and leveraging your accuracy advantage. Against an equal opponent, S2 edges out S6.
3. Never chase — Do not waste darts trying to close numbers your opponent has already closed. Every flavor of chasing is dominated by S2 in every scenario.
4. Weaker players want short games — When outmatched, play S2 and hope your opponent does the same. Building large point cushions (S3–S5) extends the game and favors the stronger player.

What We Did

Frongello's original analysis tested strategies at uniform accuracy (equal skill) and with one player at 95% relative skill. Real darts players miss in complex, target-dependent ways: triples downgrade to doubles or singles, doubles to singles, and some throws miss entirely. We extended his framework with realistic probabilistic skill profiles to test whether his conclusions hold across a full range of ability levels.

• Implemented all 17 Frongello strategies in Python using a single parameterized class, ensuring exact fidelity to the original definitions.
• Added realistic skill profiles that model how darts actually land: miss rates, downgrades (aiming for a triple but hitting a single), and face-value probability distributions calibrated against published research.
• Tested at 11 skill levels from beginner (MPR ~0.8) to pro (MPR ~5.3), spanning the full range of real-world darts ability.
• Ran 20,000 games per matchup across a full 22-strategy round-robin tournament at each skill level — over 50 million simulated games in total.
• Designed and tested 4 experimental strategies: Early Bull, Honeypot, Greedy Close-and-Score, and Adaptive Threshold — each exploring a different hypothesis about where Frongello's framework might leave value on the table.
• Discovered and optimized a new strategy we call Phase Switch, which emerged from grid-searching over a two-phase scoring-to-covering transition.

Explore the Results