Brad Weaver at Planetary Qualifier North Canton

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Planetary Premier May 03, 2025 Record 2-3-0 Field 50

Rating after 1,420

-80

Rating before 1,500 RD 250

Rating after 1,420 RD 187

Effective multiplier 1.0×

Performance 1,320

Field strength Mean 1,509 · Median 1,500 · 50 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 1420 -80.5

Top Cut Bracket Full bracket on the event page

Quarterfinals

Michael Ashbaugh 2

JohnnyReese 1

DougBongos 2

Tbold123 0

Ray Tan 2

LadyGaGaFan 0

Elyndil 2

VG23 0

Semifinals

Michael Ashbaugh 0

DougBongos 2

Ray Tan 2

Elyndil 1

Finals

DougBongos 1

Ray Tan 2

See full bracket on the event page →

Swiss · 5 matches 2-3 -80.5 1.0× +0.0 -80.5 1420

Total 2-3-0 -80.5 1420

Biggest upset Beat Theo Weaver 1500 at 50% odds / surprise +0.5

Costliest loss Lost to DTartagOne 1463 at 53% odds / surprise -0.53 /

Matches (5)

R1 Theo Weaver 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).

R2 DTartagOne Loss 1-2 1.0× Swiss

Glicko-2 predicted 53% 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 189, true skill could span ±379).

R3 Eclipsered Loss 1-2 1.0× 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).

R4 R3dSmith Win 2-0 1.0× +55.1 Swiss

R5 Austin_Kimbrell Loss 0-2 1.0× Swiss