GloktaPRT at Planetary Qualifier Oviedo

melee.gg
Planetary Premier April 25, 2026 Record 2-4-0 Field 44
Rating after 1,356
-7
Rating before 1,363 RD 113
Rating after 1,356 RD 105
Effective multiplier 1.0× weighted avg
Performance 1,320 vs field -225
Field strength Mean 1,545 · Median 1,519 · 44 rated 14th Percentile Planetaries, 2026 Q2

// 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.

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.

Top Cut Bracket Full bracket on the event page
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 6 matches 2-4 -7.0 1.0× +0.0 -7.0 1356
Total 2-4-0 -7.0 1356
Biggest upset Beat vidalvic 1710 at 24% odds / surprise +0.76
Costliest loss Lost to Evilcloud 1354 at 51% odds / surprise -0.51 / +41 swing

Matches (6)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1710~ vidalvic Win 24% 2-0 1.0× +32.4 Swiss
Glicko-2 predicted only 24% 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 145, true skill could span ±291).
R2 1354~ Evilcloud Loss 51% 1-2 1.0× -20.9 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 190, true skill could span ±379).
R3 1425~ McLion34 Loss 45% 1-2 1.0× -18.6 Swiss
R4 1598~ Ganix Ugarte Aja Loss 32% 0-2 1.0× -13.2 Swiss
R5 1658~ Ferrepower Loss 27% 0-2 1.0× -11.5 Swiss
R6 1500~ IvanBarrio Win 39% 2-0 1.0× +24.0 Swiss
Glicko-2 predicted only 39% 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 250, true skill could span ±500).
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