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Season 01 (this season)Preseason 01 Preseason 00

Cores

Table Who they field Core vs core Best matchups 1v1 head-to-head

Each core's best 3 races and up to 3 where it's below average (3+ races there).

Core	Races	Earns the point	Best races	Needs work
Ascend	339	1.0× avg	1800m 24 gate madness top 3 33% (avg 13%) · 18 1600m 16 gate WTA wins 25% (avg 6.3%) · 8 2200m 24 gate WTA wins 33% (avg 4.2%) · 3	2000m 6 gate WTA wins 4.0% (avg 17%) · 25 2200m 16 gate WTA wins 0.0% (avg 6.3%) · 16 1800m 4 gate WTA wins 12% (avg 25%) · 17
Work from home	331	1.3× avg	1000m 22 gate WTA wins 24% (avg 4.5%) · 17 1200m 6 gate WTA wins 43% (avg 17%) · 21 1200m 24 gate madness top 3 50% (avg 13%) · 4	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 29 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11 1200m 12 gate WTA wins 0.0% (avg 8.3%) · 6
Carrick	323	1.3× avg	1600m 16 gate WTA wins 50% (avg 6.3%) · 8 1400m 24 gate madness top 3 33% (avg 13%) · 12 1600m 22 gate WTA wins 17% (avg 4.5%) · 12	1200m 24 gate madness top 3 0.0% (avg 13%) · 4 1800m 12 gate WTA wins 0.0% (avg 8.3%) · 6 2000m 6 gate madness top 3 39% (avg 50%) · 18
Nani	286	1.3× avg	1400m 16 gate WTA wins 19% (avg 6.3%) · 16 1200m 12 gate WTA wins 33% (avg 8.3%) · 6 1000m 16 gate WTA wins 18% (avg 6.3%) · 11	1400m 6 gate WTA wins 7.1% (avg 17%) · 14 1800m 24 gate madness top 3 5.9% (avg 13%) · 17 1600m 22 gate WTA wins 0.0% (avg 4.5%) · 12
Ibra	279	1.2× avg	1400m 16 gate WTA wins 19% (avg 6.3%) · 16 1000m 22 gate WTA wins 12% (avg 4.5%) · 17 1800m 24 gate madness top 3 22% (avg 13%) · 18	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 29 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11 1200m 24 gate madness top 3 0.0% (avg 13%) · 4
Cecilia	265	0.9× avg	1800m 12 gate WTA wins 50% (avg 8.3%) · 6 2000m 22 gate WTA wins 11% (avg 4.5%) · 19 1000m 24 gate madness top 3 29% (avg 13%) · 7	1400m 6 gate WTA wins 0.0% (avg 17%) · 14 2200m 16 gate WTA wins 0.0% (avg 6.3%) · 16 1800m 24 gate madness top 3 5.6% (avg 13%) · 18
Couch Potato	260	1.2× avg	1600m 24 gate madness top 3 67% (avg 13%) · 3 2200m 24 gate madness top 3 27% (avg 13%) · 30 2000m 22 gate WTA wins 11% (avg 4.5%) · 19	2000m 6 gate WTA wins 8.0% (avg 17%) · 25 1800m 12 gate WTA wins 0.0% (avg 8.3%) · 6 1800m 16 gate WTA wins 0.0% (avg 6.3%) · 6
Twat	247	0.3× avg	1600m 24 gate madness top 3 33% (avg 13%) · 3 1600m 6 gate madness top 3 54% (avg 50%) · 13	2200m 24 gate madness top 3 0.0% (avg 13%) · 29 1800m 24 gate madness top 3 0.0% (avg 13%) · 18 1600m 24 gate WTA wins 0.0% (avg 4.2%) · 29
J J Gabriel	235	0.9× avg	1400m 24 gate madness top 3 25% (avg 13%) · 12 1200m 24 gate WTA wins 13% (avg 4.2%) · 8 1400m 22 gate WTA wins 11% (avg 4.5%) · 9	1000m 24 gate madness top 3 0.0% (avg 13%) · 7 1000m 4 gate WTA wins 13% (avg 25%) · 16 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11
Arc Raider	216	1.3× avg	1000m 16 gate WTA wins 36% (avg 6.3%) · 11 1400m 6 gate WTA wins 50% (avg 17%) · 14 1400m 24 gate WTA wins 25% (avg 4.2%) · 8	1400m 16 gate WTA wins 0.0% (avg 6.3%) · 16 1200m 6 gate WTA wins 9.5% (avg 17%) · 21 1200m 22 gate WTA wins 0.0% (avg 4.5%) · 12
Expensive Earth	176	0.0× avg	—	2200m 24 gate madness top 3 0.0% (avg 13%) · 30 1400m 24 gate madness top 3 0.0% (avg 13%) · 12 1600m 24 gate WTA wins 0.0% (avg 4.2%) · 29
Speedy Freak	172	1.3× avg	1200m 24 gate WTA wins 25% (avg 4.2%) · 8 1400m 24 gate madness top 3 33% (avg 13%) · 12 1200m 24 gate madness top 3 50% (avg 13%) · 4	1400m 16 gate WTA wins 0.0% (avg 6.3%) · 16 2200m 24 gate madness top 3 6.7% (avg 13%) · 30 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 11
Living Mirage	115	0.6× avg	—	2000m 22 gate WTA wins 0.0% (avg 4.5%) · 19 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 17 1800m 24 gate madness top 3 5.6% (avg 13%) · 18
Hoofey	112	0.7× avg	2200m 16 gate WTA wins 13% (avg 6.3%) · 16 1600m 22 gate WTA wins 8.3% (avg 4.5%) · 12 2000m 22 gate WTA wins 5.3% (avg 4.5%) · 19	2200m 24 gate madness top 3 3.3% (avg 13%) · 30 2200m 6 gate madness top 3 25% (avg 50%) · 12 2200m 24 gate WTA wins 0.0% (avg 4.2%) · 3
Radicalised WFH	76	0.2× avg	1000m 24 gate madness top 3 14% (avg 13%) · 7	1400m 24 gate madness top 3 0.0% (avg 13%) · 12 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 17 1200m 22 gate WTA wins 0.0% (avg 4.5%) · 12
Ok Blood Sprinter	72	0.0× avg	—	1400m 24 gate madness top 3 0.0% (avg 13%) · 12 1000m 24 gate madness top 3 0.0% (avg 13%) · 7 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 17
Blazing Crystal	41	0.9× avg	2000m 22 gate WTA wins 5.3% (avg 4.5%) · 19 2200m 16 gate WTA wins 6.3% (avg 6.3%) · 16	2200m 22 gate WTA wins 0.0% (avg 4.5%) · 6
Left Eye Lopez	39	0.0× avg	—	1000m 24 gate madness top 3 0.0% (avg 13%) · 7 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 17 1200m 24 gate WTA wins 0.0% (avg 4.2%) · 8

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.

☄️The Hot 27☄️: Power 52.1, #20. 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 00, with each round weighted by how often maps reach it (most maps end by round 27–30).