SC_louloup at Regional Qualifier Lille

melee.gg

Regional Premier May 03, 2025 Record 9-4-0 Field 860

Rating after 1,787

+36

Rating before 1,751 RD 98

Rating after 1,787 RD 87

Effective multiplier 1.3×

Performance 1,876

Field strength Mean 1,543 · Median 1,500 · 860 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 Regional tier multiplier (1.3×) 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 Regional event adds a flat +35 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 1751 → Swiss 1787 +36.2

Top Cut Bracket Full bracket on the event page

Quarterfinals

Jonas Skjold Frederiksen 2

undefined 0

ImSoHumble 2

No_Rykyna 1

BN_Diyifei 1

Zkwyz 2

yehosera 1

Erik Eroth Kaleta 2

Semifinals

Jonas Skjold Frederiksen 2

ImSoHumble 1

Zkwyz 2

Erik Eroth Kaleta 0

Finals

Jonas Skjold Frederiksen 2

Zkwyz 0

See full bracket on the event page →

Swiss · 13 matches 9-4 +27.8 1.3× +8.4 +36.2 1787

Total 9-4-0 +36.2 1787

Biggest upset Beat Dim56 1896 at 38% odds / surprise +0.62

Costliest loss Lost to GLHF_GerritS 1660 at 58% odds / surprise -0.58 /

Matches (13)

R1 Dim56 Win 2-0 1.3× +26.4 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. Their rating wasn't well-established (RD 125, true skill could span ±250).

R2 joepeace01 Win 2-0 1.3× +12.4 Swiss

R3 Erioma Win 2-0 1.3× +13.8 Swiss

R4 Atomicworm Win 2-1 1.3× +11.4 Swiss

R5 MKE_Pipette Win 2-1 1.3× +11.6 Swiss

R6 Trapper Loss 1-2 1.3× Swiss

R7 MyhreDK Win 2-0 1.3× +11.9 Swiss

R8 GLHF_GerritS Loss 0-2 1.3× Swiss

Glicko-2 predicted 58% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.

R9 daftside Win 2-0 1.3× +17.6 Swiss

R10 BN_MaddieKinabox Loss 1-2 1.3× Swiss

R11 Tim van Trappen Win 2-0 1.3× +12.3 Swiss

R12 StevoHN Win 2-1 1.3× +17.7 Swiss

R13 NO_Ephemight Loss 1-2 1.3× Swiss

Glicko-2 predicted 57% odds in your favor. Unexpected losses carry the most rating signal — the system learns more from one upset than from many predictable wins.