In Chess960, the starting position is randomly selected from 960 possibilities before the match, with two rules: Bishops must be on opposite colors, and the King must be between the Rooks.
Have you ever wondered if the “First Move Advantage” in chess is actually fair? Or does randomization in Chess960 (Fischer Random) introduce a hidden “Luck Factor” that we haven’t fully quantified?
In standard chess, we know White starts with a slight edge. But what happens when you shuffle the pieces into one of 960 random positions? Is every starting position created equal? I decided to find out using Stockfish 18 at a consistent Depth 25.
The “Luck” Gap
I analyzed all 960 starting positions. The results were fascinating—and a bit concerning for competitive integrity.
While standard chess (Position 518) gives White a familiar +0.32 advantage, some shuffle variations push this number to nearly +0.80. To put that in perspective, +0.80 is almost a full pawn advantage without a single move being played.
On the flip side, some setups are incredibly docile, evaluating at a dead 0.00.
The Unofficial “Luck Factor”: If the randomizer selects ID #80 (Highest Advantage), White is effectively gifted a winning advantage. If ID #644 is selected, the game starts dead even. In a short tournament format, this variance matters.
The Data
Here are the positions where the “Luck of the Draw” heavily favors White, and the positions where Black has the easiest time equalizing.
🏛️ White’s Top 10 (Highest Advantage)
Randomization gifts White a massive head start here. Eval is near +0.80.
| ID | Eval | Placement | Pieces |
|---|---|---|---|
| 80 | +0.80 | BBNNRKRQ |
♗♗♘♘♖♔♖♕ |
| 477 | +0.79 | RNNBKRBQ |
♖♘♘♗♔♖♗♕ |
| 604 | +0.77 | RBQNKRBN |
♖♗♕♘♔♖♗♘ |
| 848 | +0.77 | BBRKNRNQ |
♗♗♖♔♘♖♘♕ |
| 879 | +0.77 | QRKRNNBB |
♕♖♔♖♘♘♗♗ |
| 935 | +0.77 | RKBRNQNB |
♖♔♗♖♘♕♘♗ |
| 794 | +0.75 | RQKNBBRN |
♖♕♔♘♗♗♖♘ |
| 176 | +0.74 | BBNRNKRQ |
♗♗♘♖♘♔♖♕ |
| 557 | +0.74 | RNKBNQBR |
♖♘♔♗♘♕♗♖ |
🛡️ Black’s Top 10 (Least Disadvantage)
These positions are effectively drawn from move 1. Eval is -0.01 to +0.12.
| ID | Eval | Placement | Pieces |
|---|---|---|---|
| 644 | -0.01 | RBBNKRQN |
♖♗♗♘♔♖♕♘ |
| 247 | +0.07 | NRBKQNRB |
♘♖♗♔♕♘♖♗ |
| 497 | +0.08 | BRQBNKNR |
♗♖♕♗♘♔♘♖ |
| 774 | +0.09 | QRBKNBRN |
♕♖♗♔♘♗♖♘ |
| 204 | +0.09 | QBNRKNBR |
♕♗♘♖♔♘♗♖ |
| 194 | +0.10 | BQNRKBNR |
♗♕♘♖♔♗♘♖ |
| 603 | +0.11 | RQNKBRNB |
♖♕♘♔♗♖♘♗ |
| 29 | +0.11 | NQNBRKBR |
♘♕♘♗♖♔♗♖ |
| 593 | +0.12 | BRQBNKRN |
♗♖♕♗♘♔♖♘ |
| 269 | +0.12 | NRKBNQBR |
♘♖♔♗♘♕♗♖ |
Conclusion
Chess960 succeeds in killing memorization, but it introduces a new variable: Randomness. While aiming to test pure skill, it inadvertently tests a player’s ability to adapt to “lucky” or “unlucky” starting evaluations.
However, this analysis is strictly for engines. For humans, the reality is different. Being White in a completely unfamiliar position—without centuries of theory to guide you—can actually feel like a disadvantage. You are forced to formulate a plan from scratch while under pressure, often making the “First Move Advantage” purely theoretical.
Perhaps true fairness isn’t about equal engine evaluations, but about how well you can navigate the unique chaos you’re dealt.
This analysis was inspired by the FIDE Freestyle Chess World Championship (Feb 13-15, 2026).
References & Downloads
- Tournament: FIDE Freestyle Chess World Championship - Weissenhaus
- Project Code: GitHub Repository
- Full Analysis Data: Download results.csv