Daniel Holtzinger at Galactic Championship Day 2-3

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Galactic Premier July 26, 2025 Record 8-2-1 Field 564

Rating after 2,091

+101

Rating before 1,990 RD 112

Rating after 2,091 RD 97

Effective multiplier 1.5×

Performance 2,267

Field strength Mean 1,808 · Median 1,799 · 565 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 Galactic tier multiplier (1.5×) 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 Galactic event adds a flat +50 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 1990 → Swiss 2091 +100.8

Top Cut Bracket Full bracket on the event page

Quarterfinals

Beton 2

Matthew Yakobina 0

BN_Cerberus 2

Joshua Everly 0

ECL_LegoPizza 2

Magog29 0

Ophir Marom 2

MikaelC 1

Semifinals

Beton 2

BN_Cerberus 1

ECL_LegoPizza 2

Ophir Marom 1

Finals

Beton 2

ECL_LegoPizza 1

See full bracket on the event page →

Swiss · 11 matches 8-2-1 +67.2 1.5× +33.6 +100.8 2091

Total 8-2-1 +100.8 2091

Biggest upset Beat BN_ioucounoujr 2137 at 38% odds / surprise +0.62

Costliest loss Lost to zeroskatr12 1785 at 67% odds / surprise -0.67 / 1.5× /

Matches (11)

R1 Fonzie963 Win 2-0 1.5× +19.8 Swiss

R2 ADB_RemiWanKenobi Win 2-1 1.5× +12.7 Swiss

R3 branmuffiin Win 2-0 1.5× +18.7 Swiss

R4 zeroskatr12 Loss 1-2 1.5× Swiss

Glicko-2 predicted 67% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.

R5 Trapper Win 2-1 1.5× +26.5 Swiss

R6 ECL_dts Draw 1-1 1.5× -4.8 Swiss

R7 Docnicka Win 2-0 1.5× +31.2 Swiss

R8 Fireshow Win 2-0 1.5× +33.7 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.

R9 NO_SerThanos Win 2-1 1.5× +30.8 Swiss

R10 BN_ioucounoujr Win 2-1 1.5× +39.7 Swiss

Glicko-2 predicted only 38% odds for you. Upset wins move the rating model strongly because the system learns a lot from results it didn't expect.

R11 Beton Loss 1-2 1.5× 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.