EM_Fenix at Planetary Qualifier Madrid Alcobendas

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Planetary Premier May 31, 2025 Record 3-4-0 Field 95

Rating after 1,325

+49

Rating before 1,277 RD 147

Rating after 1,325 RD 128

Effective multiplier 1.0×

Performance 1,456

Field strength Mean 1,543 · Median 1,500 · 95 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 1277 → Swiss 1325 +48.8

Top Cut Bracket Full bracket on the event page

Quarterfinals

CarryPotter 0

Hibadino 2

TGB_JulioJ 0

tarkin84 2

Xexu 0

JS_Likeaprophet 2

shadowblade 2

LorenzoM 1

Semifinals

Hibadino 2

tarkin84 0

JS_Likeaprophet 1

shadowblade 2

Finals

Hibadino 2

shadowblade 0

See full bracket on the event page →

Swiss · 7 matches 3-4 +48.8 1.0× +0.0 +48.8 1325

Total 3-4-0 +48.8 1325

Biggest upset Beat TGB_Romaero 1498 at 32% odds / surprise +0.68

Toughest win Beat dagotroll 1500 at 33% odds

Costliest loss Lost to Rodric 1500 at 33% odds / surprise -0.33 /

Matches (7)

R1 TGB_Romaero Win 2-1 1.0× +47.0 Swiss

Glicko-2 predicted only 32% 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 138, true skill could span ±275).

R2 Dashrendar72 Loss 1-2 1.0× Swiss

R3 DaniGon Loss 1-2 1.0× Swiss

R4 Luislorean Win 2-1 1.0× +40.6 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 177, true skill could span ±355).

R5 tarkincito123 Loss 0-2 1.0× Swiss

R6 dagotroll Win 2-0 1.0× +43.5 Swiss

Glicko-2 predicted only 33% 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).

R7 Rodric Loss 0-2 1.0× Swiss