Rankings / ECL_Mickeyd / Galactic Championship Day 2-3

ECL_Mickeyd at Galactic Championship Day 2-3

melee.gg
Galactic Premier July 26, 2025 Record 5-3-0 Field 564
Rating after 1,914
+11
Rating before 1,903 RD 97
Rating after 1,914 RD 90
Effective multiplier 1.5× weighted avg
Performance 1,944 vs field +136
Field strength Mean 1,808 · Median 1,799 · 565 rated

// 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 Galactic tier multiplier (1.5×) amplifies every gain and every loss.

Making cut at this Galactic event adds a flat +50 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
Beton 2
Matthew Yakobina 0
BN_Cerberus 2
Joshua Everly 0
ECL_LegoPizza 2
Magog29 0
Ophir Marom 2
MikaelC 1
Semifinals
Beton 2
BN_Cerberus 1
ECL_LegoPizza 2
Ophir Marom 1
Finals
Beton 2
ECL_LegoPizza 1
See full bracket on the event page →
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 8 matches 5-3 +7.5 1.5× +3.7 +11.2 1914
Total 5-3-0 +11.2 1914
Biggest upset Beat taldejamal 1895 at 51% odds / surprise +0.49
Costliest loss Lost to CoryTill 1775 at 60% odds / surprise -0.6 / 1.5× / +47 swing

Matches (8)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1695 CCC_Ordan Win 67% 2-0 1.5× +16.0 Swiss
R2 ▼ 1775~ CoryTill Loss 60% 1-2 1.5× -28.3 Swiss
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. Their rating wasn't well-established (RD 169, true skill could span ±337).
R3 1728~ goodmanfai Win 64% 2-1 1.5× +16.8 Swiss
R4 1839 BN_georgethehulk Loss 55% 0-2 1.5× -26.7 Swiss
Glicko-2 predicted 55% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.
R5 1717 Picardy3rd Win 65% 2-1 1.5× +16.8 Swiss
R6 1702 C1C_rskellington Win 66% 2-0 1.5× +16.3 Swiss
R7 ▲ 1895 taldejamal Win 51% 2-0 1.5× +23.9 Swiss
R8 1966 Carlos Apodaca Loss 45% 0-2 1.5× -21.6 Swiss

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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