Team report · Lower league

High Rollers

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Season 01 (this season)Preseason 01 Preseason 00

Cores

Table Who they field Core vs coreBest matchups1v1 head-to-head

Each core's best 3 races and up to 3 where it's below average (3+ races there). Pick a team in Compare with to unlock best matchups and 1v1 head-to-heads.

Core	Races	Earns the point	Best races	Needs work
SWIFT ESCORT	839	1.3× avg	1800m 24 gate madness top 3 30% (avg 13%) · 56 1800m 16 gate WTA wins 33% (avg 6.3%) · 6 1600m 16 gate WTA wins 22% (avg 6.3%) · 9	1400m 16 gate WTA wins 0.0% (avg 6.3%) · 20 1600m 24 gate madness top 3 0.0% (avg 13%) · 7 1600m 1v1 wins 33% (avg 50%) · 12
CHEESY LOVE🧀♥️	823	1.1× avg	1000m 24 gate madness top 3 38% (avg 13%) · 21 2200m 22 gate WTA wins 20% (avg 4.5%) · 15 1400m 24 gate madness top 3 30% (avg 13%) · 30	2200m 16 gate WTA wins 0.0% (avg 6.3%) · 20 1400m 22 gate WTA wins 0.0% (avg 4.5%) · 24 1600m 24 gate madness top 3 0.0% (avg 13%) · 7
EMINENT FORCE	695	1.2× avg	1800m 12 gate WTA wins 31% (avg 8.3%) · 13 1400m 24 gate madness top 3 30% (avg 13%) · 30 1400m 4 gate WTA wins 75% (avg 25%) · 4	2000m 6 gate WTA wins 3.1% (avg 17%) · 32 1400m 16 gate WTA wins 0.0% (avg 6.3%) · 20 1000m 22 gate WTA wins 2.0% (avg 4.5%) · 49
CHEESY NINES	622	1.3× avg	1600m 24 gate WTA wins 11% (avg 4.2%) · 35 1000m 12 gate madness top 3 67% (avg 25%) · 6 1400m 22 gate WTA wins 13% (avg 4.5%) · 24	1400m 12 gate madness top 3 17% (avg 25%) · 6 1000m 24 gate madness top 3 9.5% (avg 13%) · 21 1000m 4 gate WTA wins 21% (avg 25%) · 19
CHEESY ETHER🧀⚠️	582	1.1× avg	1600m 22 gate WTA wins 10% (avg 4.5%) · 30 1000m 12 gate madness top 3 50% (avg 25%) · 6 1000m 22 gate WTA wins 8.2% (avg 4.5%) · 49	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 35 1600m 24 gate madness top 3 0.0% (avg 13%) · 7 1400m 24 gate madness top 3 6.7% (avg 13%) · 30
GRATED ETHER🧀	556	1.3× avg	1000m 22 gate WTA wins 14% (avg 4.5%) · 49 1600m 24 gate madness top 3 43% (avg 13%) · 7 1400m 24 gate WTA wins 20% (avg 4.2%) · 10	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 35 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11 1600m 6 gate WTA wins 0.0% (avg 17%) · 4
SHREDDED LOVE🧀	528	0.7× avg	1600m 24 gate WTA wins 8.6% (avg 4.2%) · 35 1200m 22 gate WTA wins 6.9% (avg 4.5%) · 29 1000m 12 gate madness top 3 33% (avg 25%) · 6	2200m 24 gate madness top 3 2.4% (avg 13%) · 85 2000m 22 gate WTA wins 0.0% (avg 4.5%) · 48 1000m 1v1 wins 17% (avg 50%) · 6
RED BULL	513	0.4× avg	1200m 24 gate WTA wins 20% (avg 4.2%) · 10 1800m 6 gate madness top 3 55% (avg 50%) · 11	2200m 24 gate madness top 3 0.0% (avg 13%) · 85 1800m 24 gate madness top 3 0.0% (avg 13%) · 56 2000m 12 gate madness top 3 0.0% (avg 25%) · 12
HACKING THE ALGO	507	0.5× avg	1800m 24 gate WTA wins 14% (avg 4.2%) · 7 1800m 12 gate madness top 3 33% (avg 25%) · 3 1000m 24 gate madness top 3 14% (avg 13%) · 21	1400m 24 gate madness top 3 0.0% (avg 13%) · 30 2200m 24 gate madness top 3 2.4% (avg 13%) · 85 2000m 22 gate WTA wins 0.0% (avg 4.5%) · 48
GRATED SWAG🧀	449	0.4× avg	1000m 16 gate WTA wins 9.1% (avg 6.3%) · 11	1800m 24 gate madness top 3 1.8% (avg 13%) · 56 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 49 2000m 22 gate WTA wins 0.0% (avg 4.5%) · 48
AGAINST ALL ODDS	439	1.1× avg	2200m 24 gate madness top 3 21% (avg 13%) · 85 1600m 22 gate WTA wins 10% (avg 4.5%) · 30 2000m 4 gate WTA wins 50% (avg 25%) · 6	2200m 6 gate WTA wins 0.0% (avg 17%) · 7 1800m 12 gate WTA wins 0.0% (avg 8.3%) · 13 1800m 6 gate WTA wins 0.0% (avg 17%) · 6
BUDDHA	373	1.3× avg	1600m 16 gate WTA wins 38% (avg 6.3%) · 8 2200m 16 gate WTA wins 15% (avg 6.3%) · 20 2000m 22 gate WTA wins 8.3% (avg 4.5%) · 48	1800m 24 gate WTA wins 0.0% (avg 4.2%) · 7 1600m 24 gate WTA wins 3.2% (avg 4.2%) · 31 2000m 6 gate WTA wins 15% (avg 17%) · 26
Divine Harvest	188	0.6× avg	1400m 22 gate WTA wins 22% (avg 4.5%) · 9	1000m 24 gate madness top 3 0.0% (avg 13%) · 15 1400m 24 gate madness top 3 0.0% (avg 13%) · 15 1000m 12 gate madness top 3 0.0% (avg 25%) · 6
STRANGE CAR	130	1.7× avg	1200m 12 gate WTA wins 23% (avg 8.3%) · 13 1400m 16 gate WTA wins 20% (avg 6.3%) · 10 1200m 22 gate WTA wins 10% (avg 4.5%) · 29	2200m 22 gate WTA wins 0.0% (avg 4.5%) · 15 1200m 24 gate WTA wins 0.0% (avg 4.2%) · 10 1600m 24 gate WTA wins 0.0% (avg 4.2%) · 4
SHREDDED CHIDO🧀	111	0.3× avg	1000m 6 gate madness top 3 50% (avg 50%) · 6	1000m 24 gate madness top 3 0.0% (avg 13%) · 15 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 35 1200m 22 gate WTA wins 0.0% (avg 4.5%) · 29
SCARLET ESCORT	100	1.4× avg	2200m 24 gate madness top 3 20% (avg 13%) · 46 1400m 24 gate madness top 3 20% (avg 13%) · 15 2000m 6 gate WTA wins 33% (avg 17%) · 3	1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11
SHREDDED MATH 🧀🧮	93	0.8× avg	1200m 24 gate madness top 3 24% (avg 13%) · 17 1400m 24 gate WTA wins 10% (avg 4.2%) · 10	1400m 16 gate WTA wins 0.0% (avg 6.3%) · 20 1000m 24 gate madness top 3 0.0% (avg 13%) · 6 1400m 24 gate madness top 3 6.7% (avg 13%) · 30
DELICATE BUDDHA🧘‍♂️	90	0.5× avg	—	1200m 24 gate madness top 3 0.0% (avg 13%) · 12 1000m 24 gate madness top 3 0.0% (avg 13%) · 6 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11

Earns the point: how often a core does what wins its team the round — wins the race (1v1, WTA) or finishes top 3 (madness) — against an average entrant (1 in 2 for a 1v1, 1 in 22 for a 22-gate WTA). In big fields only an outright fast time wins, so steady cores that “beat most of the field” can still rarely score there. Best / needs-work segments need 3+ races.

A round is one race of a map; whoever wins it gets the point. Win % here is the share of rounds won in each segment this Preseason 01, with each round weighted by how often maps reach it (most maps end by round 27–30).