SC_louloup at Planetary Qualifier Sotteville les Rouen

melee.gg
Planetary Premier August 23, 2025 Record 5-2-1 Field 83
Rating after 1,898
+28
Rating before 1,870 RD 84
Rating after 1,898 RD 83
Effective multiplier 0.94× weighted avg
Performance 1,981 vs field +411
Field strength Mean 1,570 · Median 1,500 · 83 rated 76th Percentile Planetaries, 2025 Q3

// 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 · 7 matches 5-1-1 +23.5 1.0× +0.0 +23.5 1894
Quarterfinals · 1 match 0-1 -12.8 0.82× 1.00 · -0.18 +2.3 -10.5 1882
Top-cut bonus Tier-scaled additive ‧ Planetary at 83 +15.0 1897
Total 5-2-1 +28.0 1898
Biggest upset Beat BN_ioucounoujr 2180 at 26% odds / surprise +0.74
Costliest loss Lost to TPS_mathalien 1785 at 59% odds / surprise -0.59 / +23 swing

Matches (8)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1352~ CallMeUkyo Win 85% 2-0 1.0× +3.7 Swiss
R2 1246~ Naihna Win 89% 2-0 1.0× +2.7 Swiss
R3 1355~ Khazad Win 85% 2-0 1.0× +3.7 Swiss
R4 2180 BN_ioucounoujr Win 26% 2-1 1.0× +18.3 Swiss
Glicko-2 predicted only 26% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.
R5 1979 BN_MaddieKinabox Loss 41% 1-2 1.0× -10.0 Swiss
R6 1592 EC_Lasax Win 72% 2-1 1.0× +6.9 Swiss
R7 1797 SC_Noxm Draw 0-0 1.0× ±0.0 Swiss
QF 1785 TPS_mathalien Loss 59% 0-2 0.82× -11.4 Top Cut
Glicko-2 predicted 59% 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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