Rankings / SC_louloup / Planetary Qualifier Lyon

SC_louloup at Planetary Qualifier Lyon

melee.gg
Planetary Premier October 13, 2024 Record 3-4-0 Field 111
Rating after 1,453
-47
Rating before 1,500 RD 250
Rating after 1,453 RD 174
Effective multiplier 1.0× weighted avg
Performance 1,409 vs field -91
Field strength Mean 1,500 · Median 1,500 · 111 rated 43rd Percentile Planetaries, 2024 Q4

// 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
SaumonRegal 2
FZS_MATHELIN42 0
Ahunter 2
Aloye 0
BN_ioucounoujr 2
GU_Raskar 0
TheFrenchPalpaTexasRanger 1
SC_Spylk 2
Semifinals
SaumonRegal 2
Ahunter 0
SC_Spylk 0
BN_ioucounoujr 2
Finals
SaumonRegal 0
BN_ioucounoujr 2
See full bracket on the event page →
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 7 matches 3-4 -47.3 1.0× +0.0 -47.3 1453
Total 3-4-0 -47.3 1453
Biggest upset Beat Captain_Kiwii 1500 at 50% odds / surprise +0.5
Costliest loss Lost to SC_Noxm 1500 at 50% odds / surprise -0.5 / +170 swing

Matches (7)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 ▼ 1500~ SC_Noxm Loss 50% 1-2 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).
R2 ▲ 1500~ Captain_Kiwii 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).
R3 1500~ Fred57155 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).
R4 1500~ Keau 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).
R5 1500~ BN_MaddieKinabox 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~ MKE_Malette15 Loss 50% 1-2 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).
R7 1500~ xplirmus 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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