Kondziuldz at Planetary Qualifier Warsaw

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Planetary Premier April 19, 2026 Record 3-3-0 Field 63

Rating after 1,403

+36

Rating before 1,368 RD 120

Rating after 1,403 RD 110

Effective multiplier 1.0×

Performance 1,550

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 1368 → Swiss 1403 +35.8

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 3-3 +35.8 1.0× +0.0 +35.8 1403

Total 3-3-0 +35.8 1403

Biggest upset Beat MrUntiltable 1634 at 29% odds / surprise +0.71

Costliest loss Lost to qb 1356 at 51% odds / surprise -0.51 /

Matches (6)

R1 Jan Jurczyszyn Win 2-1 1.0× +27.6 Swiss

Glicko-2 predicted only 43% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R2 qb Loss 0-2 1.0× Swiss

Glicko-2 predicted 51% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins. Their rating wasn't well-established (RD 175, true skill could span ±350).

R3 Piotr Grabiec Loss 1-2 1.0× Swiss

R4 Zaglobnik Win 2-0 1.0× +28.0 Swiss

Glicko-2 predicted only 42% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R5 MrUntiltable Win 2-0 1.0× +34.1 Swiss

Glicko-2 predicted only 29% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect. Their rating wasn't well-established (RD 126, true skill could span ±253).

R6 Wojciech Bajger Loss 0-2 1.0× Swiss