Diego-jr at Planetary Qualifier Oviedo

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Planetary Premier April 25, 2026 Record 5-2-1
Rating after 1,737
+237
Rating before 1,500 RD 250
Rating after 1,737 RD 167
Effective multiplier 0.97× weighted avg
Performance 1,878 vs field +333
Field strength Mean 1,545 · Median 1,519 · 44 rated 33rd 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 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 4-1-1 +228.8 1.0× +0.0 +228.8 1729
Quarterfinals · 1 match 1-0 +42.1 1.12× 1.00 · +0.12 +5.1 +47.1 1770
Semifinals · 1 match 0-1 -52.8 0.73× 1.00 · -0.27 +14.2 -38.5 1728
Total 5-2-1 +237.4 1737
Biggest upset Beat Sergio1975 1667 at 36% odds / surprise +0.64
Costliest loss Lost to Loira 1652 at 60% odds / surprise -0.6 / +185 swing

Matches (8)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1863 Vanieh Draw 23% 1-1 1.0× +51.6 Swiss
R2 1667 Sergio1975 Win 36% 2-0 1.0× +116.4 Swiss
Glicko-2 predicted only 36% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.
R3 1652 Loira Loss 37% 1-2 1.0× -68.2 Swiss
R4 1500~ Mateja Win 50% 2-0 1.0× +85.1 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 250, true skill could span ±500).
R5 1652 JaviHT Win 37% 2-1 1.0× +113.6 Swiss
Glicko-2 predicted only 37% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.
R6 1500~ DiegoAguiar Win 50% 2-1 1.0× +85.1 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 250, true skill could span ±500).
QF 1558~ JAEstwald Win 64% 2-1 1.12× +110.7 Top Cut
Semis 1652 Loira Loss 60% 0-2 0.73× -49.8 Top Cut
Glicko-2 predicted 60% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.
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