Rankings / Darthsilk_DSP / Planetary Qualifier Stafford

Darthsilk_DSP at Planetary Qualifier Stafford

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Planetary Premier April 18, 2026 Record 6-2-0
Rating after 1,811
-2
Rating before 1,813 RD 69
Rating after 1,811 RD 69
Effective multiplier 1.16x delta-weighted

// rating math · glicko-2 phase replay

How this rating change was computed

Glicko-2 doesn’t reward record — it rewards surprise. Winning a match the system expected you to win is worth almost nothing. Losing one is expensive. Losing to someone rated below you costs the most. The Planetary tier multiplier (1.0×) amplifies every gain and every loss. Top-cut rounds add more on top (Quarterfinals +0.15, Semifinals +0.25, Finals +0.35).

Phase Record Raw Glicko-2 Multiplier Applied Running
Swiss · 6 matches 5-1 +6.2 1.0× +6.2 1819
Quarterfinals · 1 match 1-0 +6.5 1.15× +7.5 1826
Semifinals · 1 match 0-1 -13.5 1.25× -16.8 1810
Total 6-2-0 -1.8 1811

Phase numbers use each opponent’s pre-tournament rating (the one shown on the leaderboard). The engine uses the opponent’s rating at the moment of the match — which for top-cut rounds includes their own Swiss performance — so the phase contributions above are approximate for Quarterfinals, Semifinals, and Finals. The Total is the engine’s actual output.

Biggest upset Beat Morgz 1652 at 67% odds / surprise +0.33
Costliest loss Lost to JohannesHill 1651 at 67% odds / surprise -0.67

Matches (8)

Round HRI Opponent Result Odds Game W-L Multiplier Type
R1 1652 Morgz Loss 66% 0-2 1.15x Swiss
R2 1500 danw53 Win 76% 2-0 1.15x Swiss
R3 1301 Jose_F Win 88% 2-0 1.15x Swiss
R4 1553 Rob Syratt Win 74% 2-1 1.15x Swiss
R5 1536 Zhrine Win 76% 2-0 1.15x Swiss
R6 1428 kwunho Win 83% 2-1 1.15x Swiss
▲ QF 1652 Morgz Win 67% 2-0 1.15x Top Cut
▼ Semis 1651 JohannesHill Loss 67% 0-2 1.25x Top Cut

Per-match multipliers reflect what the engine applied at the time this snapshot was recorded. The Effective Multiplier above is a delta-weighted average across all phases — Finals matches swing the headline more than Swiss rounds when they produced bigger rating changes. How it works.