TCT_Adrian at Planetary Qualifier Oberhausen

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Planetary Limited December 21, 2025 Record 3-4-0 Field 76
Rating after 1,457
-43
Rating before 1,500 RD 250
Rating after 1,457 RD 171
Effective multiplier 1.0× weighted avg
Performance 1,423 vs field -135
Field strength Mean 1,558 · Median 1,500 · 76 rated 56th Percentile Planetaries, 2025 Q4

// 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
Phase Record Raw Δ Multiplier Bonus Applied Running
Swiss · 7 matches 3-4 -43.0 1.0× +0.0 -43.0 1457
Total 3-4-0 -43.0 1457
Biggest upset Beat dannyketchum110 1540 at 47% odds / surprise +0.53
Costliest loss Lost to DanSolo 1472 at 52% odds / surprise -0.52 / +178 swing

Matches (7)

Round HRI Opponent Result Odds Game W-L Multiplier Δ Type
R1 1500~ NGNR_Phorlo Win 50% 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 1603~ BTG_Djadmar Loss 42% 0-2 1.0× -74.2 Swiss
R3 1483~ kazuya82 Loss 51% 0-2 1.0× -90.4 Swiss
Glicko-2 predicted 51% 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 184, true skill could span ±368).
R4 1472~ DanSolo Loss 52% 0-2 1.0× -93.2 Swiss
Glicko-2 predicted 52% 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).
R5 1500~ Suomenpojat Win 50% 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).
R6 1540~ dannyketchum110 Win 47% 2-1 1.0× +94.9 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 152, true skill could span ±304).
R7 1500~ NGNR_AnMi94 Loss 50% 0-2 1.0× -85.1 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).
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