Cuendae at Planetary Qualifier Warsaw

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Planetary Premier April 19, 2026 Record 5-1-2 Field 63

Rating after 1,959

+77

Rating before 1,882 RD 109

Rating after 1,959 RD 104

Effective multiplier 0.97×

Performance 2,277

Field strength Mean 1,594 · Median 1,544 · 63 rated

// 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.

Shape D top-cut adjustments QF SF F Wins +0.12 +0.18 +0.25 Losses -0.18 -0.27 -0.35

Making cut at this Planetary event adds a flat +15 top-cut bonus on top of phase math. Making cut never costs you net rating — the made-cut floor pins the tournament delta to ≥ 0.

Start 1882 → Swiss 1936 +54.7 → Quarterfinals 1958 +21.9 → Semifinals 1942 -16.5 → Top-cut bonus 1957 +15.0

Top Cut Bracket Full bracket on the event page

Quarterfinals

Beton 0

Gibki 2

Jędrzej Sobota 2

DrakonianLord 1

Harrison_Solo 0

Piotr Jabłoński 2

siny 0

Cuendae 2

Semifinals

Gibki 2

Jędrzej Sobota 0

Piotr Jabłoński 2

Cuendae 0

Finals

Gibki 2

Piotr Jabłoński 0

See full bracket on the event page →

Swiss · 6 matches 4-0-2 +54.7 1.0× +0.0 +54.7 1936

Quarterfinals · 1 match 1-0 +20.5 1.12× 1.00 · +0.12 +2.5 +23.0 1958

Semifinals · 1 match 0-1 -21.3 0.73× 1.00 · -0.27 +5.7 -15.5 1942

Top-cut bonus Tier-scaled additive ‧ Planetary at 63 +15.0 1957

Total 5-1-2 +77.1 1959

Biggest upset Beat siny 1975 at 47% odds / surprise +0.53

Costliest loss Lost to Piotr Jabłoński 1815 at 62% odds / surprise -0.62 /

Matches (8)

R1 KarkosSWU Win 2-1 1.0× +6.4 Swiss

R2 Piotr Grabiec Win 2-0 1.0× +14.7 Swiss

R3 MikaelPL Win 2-0 1.0× +19.4 Swiss

R4 Erik Eroth Kaleta Win 2-0 1.0× +18.9 Swiss

R5 DrakonianLord Draw 0-0 1.0× ±0.0 Swiss

R6 siny Draw 0-0 1.0× ±0.0 Swiss

QF siny Win 2-0 1.12× +25.9 Top Cut

Glicko-2 predicted only 47% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

Semis Piotr Jabłoński Loss 0-2 0.73× Top Cut

Glicko-2 predicted 62% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.