Rankings / FF_LordBuckethead / Planetary Qualifier Brighton

FF_LordBuckethead at Planetary Qualifier Brighton

melee.gg
Planetary Premier May 17, 2025 Record 4-3-0 Field 71
Rating after 1,511
+45
Rating before 1,465 RD 175
Rating after 1,511 RD 141
Effective multiplier 1.0× weighted avg
Performance 1,602 vs field +109
Field strength Mean 1,493 · Median 1,500 · 71 rated 4th Percentile Planetaries, 2025 Q2

// 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
yehosera 2
TheBigG 1
Alfie Crust 1
Darthsilk_DSP 2
Reader_DSP 2
Tommaso Madonia 1
Wylde77 2
kabbage345 0
Semifinals
yehosera 2
Darthsilk_DSP 1
Reader_DSP 2
Wylde77 1
Finals
yehosera 2
Reader_DSP 1
See full bracket on the event page →
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 7 matches 4-3 +45.3 1.0× +0.0 +45.3 1511
Total 4-3-0 +45.3 1511
Biggest upset Beat Lolokolo 1534 at 44% odds / surprise +0.56
Costliest loss Lost to Stealthmoose_DSP 1492 at 48% odds / surprise -0.48 / +95 swing

Matches (7)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1500~ FreddieC Win 47% 2-1 1.0× +47.5 Swiss
Glicko-2 predicted only 47% 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 1548~ supermaz Loss 43% 0-2 1.0× -40.7 Swiss
R3 1500~ LoganDamario Win 47% 2-0 1.0× +47.5 Swiss
Glicko-2 predicted only 47% 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~ CDamario Win 47% 2-1 1.0× +47.5 Swiss
Glicko-2 predicted only 47% 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 ▲ 1534~ Lolokolo Win 44% 2-1 1.0× +52.1 Swiss
Glicko-2 predicted only 44% 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 182, true skill could span ±365).
R6 1500~ VTJake Loss 47% 1-2 1.0× -42.6 Swiss
R7 ▼ 1492~ Stealthmoose_DSP Loss 48% 0-2 1.0× -45.5 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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