_ODIN_WAN_KENOBI_ at Planetary Qualifier Yuma

melee.gg

Planetary Limited April 25, 2026 Record 4-3-0 Field 43

Rating after 1,643

+143

Rating before 1,500 RD 250

Rating after 1,643 RD 172

Effective multiplier 0.96×

Performance 1,709

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 1500 → Swiss 1670 +170.1 → Quarterfinals 1622 -47.8 → Top-cut bonus 1637 +15.0

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 +170.1 1.0× +0.0 +170.1 1670

Quarterfinals · 1 match 0-1 -51.6 0.82× 1.00 · -0.18 +9.3 -42.3 1622

Top-cut bonus Tier-scaled additive ‧ Planetary at 43 +15.0 1637

Total 4-3-0 +142.9 1643

Biggest upset Beat CBG_Taylor 1695 at 34% odds / surprise +0.66

Costliest loss Lost to llopez101 1563 at 59% odds / surprise -0.59 /

Matches (7)

R1 CBG_Taylor Win 2-0 1.0× +120.5 Swiss

Glicko-2 predicted only 34% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R2 CaptainFTB Win 2-1 1.0× +108.8 Swiss

Glicko-2 predicted only 39% 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 152, true skill could span ±304).

R3 ShazamPowers Win 2-0 1.0× +97.5 Swiss

Glicko-2 predicted only 45% 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 152, true skill could span ±304).

R4 llopez101 Loss 1-2 1.0× Swiss

R5 CheeseKahuna Loss 0-2 1.0× Swiss

R6 Tommycallahan123 Win 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 llopez101 Loss 1-2 0.82× 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. Their rating wasn't well-established (RD 152, true skill could span ±304).