SBS_Logray36 at Planetary Qualifier Yuma

melee.gg

Planetary Limited April 25, 2026 Record 4-2-0 Field 43

Rating after 1,571

+115

Rating before 1,456 RD 152

Rating after 1,571 RD 133

Effective multiplier 1.0×

Performance 1,897

Field strength Mean 1,575 · Median 1,552 · 42 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 Planetary tier multiplier (1.0×) amplifies every gain and every loss.

Shape D top-cut adjustments QF SF F Wins +0.12 +0.18 +0.25 Losses -0.18 -0.27 -0.35

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.

Start 1456 → Swiss 1571 +114.6

Top Cut Bracket Full bracket on the event page

Quarterfinals

Spencer Freeman 2

JonahBR 0

llopez101 2

_ODIN_WAN_KENOBI_ 1

CBG_Taylor 2

CheeseKahuna 0

Arteiris 2

CBG_Ruben 1

Semifinals

Spencer Freeman 2

CBG_Taylor 0

llopez101 2

Arteiris 0

Finals

Spencer Freeman 2

llopez101 1

See full bracket on the event page →

Swiss · 6 matches 4-2 +114.6 1.0× +0.0 +114.6 1571

Total 4-2-0 +114.6 1571

Biggest upset Beat tehPyro 1961 at 15% odds / surprise +0.85

Costliest loss Lost to Maclunkey 1516 at 45% odds / surprise -0.45 /

Matches (6)

R1 Nauk Loss 1-2 1.0× Swiss

R2 crayzd Win 2-0 1.0× +30.7 Swiss

R3 Amando Santos Win 2-0 1.0× +62.7 Swiss

Glicko-2 predicted only 18% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R4 Maclunkey Loss 0-2 1.0× Swiss

R5 tehPyro Win 2-1 1.0× +64.6 Swiss

Glicko-2 predicted only 15% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R6 hungh17 Win 2-0 1.0× +44.4 Swiss

Glicko-2 predicted only 40% 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 125, true skill could span ±250).