Rankings / Mateja / Planetary Qualifier Oviedo

Mateja at Planetary Qualifier Oviedo

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Planetary Premier April 25, 2026 Record 2-4-0 Field 44
Rating after 1,408
-92
Rating before 1,500 RD 250
Rating after 1,408 RD 178
Effective multiplier 1.0× weighted avg
Performance 1,297 vs field -248
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
Quarterfinals
JAEstwald 1
Diego-jr 2
Loira 2
Farreli 0
Evilcloud 0
miguividal 2
Fuegoscuro86 2
McLion34 1
Semifinals
Diego-jr 0
Loira 2
miguividal 2
Fuegoscuro86 1
Finals
Loira 2
miguividal 1
See full bracket on the event page →
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 6 matches 2-4 -92.3 1.0× +0.0 -92.3 1408
Total 2-4-0 -92.3 1408
Biggest upset Beat Yoda FGC 1504 at 50% odds / surprise +0.5
Costliest loss Lost to Diego-jr 1500 at 50% odds / surprise -0.5 / +170 swing

Matches (6)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1584 leninegz Loss 43% 1-2 1.0× -77.8 Swiss
R2 1472~ JaiQT Win 52% 2-0 1.0× +85.1 Swiss
R3 ▲ 1504~ Yoda FGC Win 50% 2-0 1.0× +88.5 Swiss
Glicko-2 predicted only 50% 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 185, true skill could span ±370).
R4 ▼ 1500~ Diego-jr Loss 50% 0-2 1.0× -85.1 Swiss
Glicko-2 predicted 50% 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 250, true skill could span ±500).
R5 1500~ DiegoAguiar Loss 50% 0-2 1.0× -85.1 Swiss
Glicko-2 predicted 50% 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 250, true skill could span ±500).
R6 1500~ SauronOp Loss 50% 0-2 1.0× -85.1 Swiss
Glicko-2 predicted 50% 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 250, true skill could span ±500).

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.

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