Team report · Lower league

North West

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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	700	1.2× avg	2200m 22 gate WTA wins 27% (avg 4.5%) · 11 2000m 22 gate WTA wins 11% (avg 4.5%) · 35 2000m 12 gate madness top 3 45% (avg 25%) · 22	1800m 6 gate WTA wins 0.0% (avg 17%) · 11 1600m 24 gate madness top 3 0.0% (avg 13%) · 7 1200m 24 gate madness top 3 5.9% (avg 13%) · 17
Carrick	662	1.2× avg	2200m 24 gate madness top 3 30% (avg 13%) · 69 1400m 24 gate madness top 3 32% (avg 13%) · 22 1600m 24 gate madness top 3 43% (avg 13%) · 7	2000m 4 gate WTA wins 9.1% (avg 25%) · 11 1600m 6 gate WTA wins 0.0% (avg 17%) · 6 1400m 22 gate WTA wins 0.0% (avg 4.5%) · 18
Work from home	602	1.2× avg	1000m 24 gate madness top 3 41% (avg 13%) · 22 1200m 22 gate WTA wins 18% (avg 4.5%) · 22 1600m 24 gate WTA wins 13% (avg 4.2%) · 31	1000m 22 gate WTA wins 0.0% (avg 4.5%) · 36 2000m 22 gate WTA wins 0.0% (avg 4.5%) · 35 1400m 16 gate WTA wins 0.0% (avg 6.3%) · 18
Cecilia	524	1.2× avg	1800m 6 gate WTA wins 55% (avg 17%) · 11 2200m 24 gate madness top 3 25% (avg 13%) · 69 1800m 12 gate madness top 3 75% (avg 25%) · 4	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 31 1400m 16 gate WTA wins 0.0% (avg 6.3%) · 18 1000m 24 gate madness top 3 4.5% (avg 13%) · 22
Nani	505	1.2× avg	1000m 24 gate madness top 3 36% (avg 13%) · 22 1800m 24 gate madness top 3 19% (avg 13%) · 36 1200m 22 gate WTA wins 9.1% (avg 4.5%) · 22	2000m 22 gate WTA wins 0.0% (avg 4.5%) · 35 1600m 22 gate WTA wins 0.0% (avg 4.5%) · 22 2200m 22 gate WTA wins 0.0% (avg 4.5%) · 11
Ibra	503	1.3× avg	1400m 16 gate WTA wins 22% (avg 6.3%) · 18 1200m 24 gate madness top 3 35% (avg 13%) · 17 1600m 24 gate madness top 3 43% (avg 13%) · 7	2200m 24 gate madness top 3 7.1% (avg 13%) · 56 1800m 24 gate WTA wins 0.0% (avg 4.2%) · 6 1000m 12 gate madness top 3 20% (avg 25%) · 10
Couch Potato	486	1.2× avg	2200m 22 gate WTA wins 18% (avg 4.5%) · 11 2200m 24 gate madness top 3 23% (avg 13%) · 69 2200m 4 gate WTA wins 40% (avg 25%) · 15	1600m 24 gate WTA wins 0.0% (avg 4.2%) · 31 1800m 16 gate WTA wins 0.0% (avg 6.3%) · 6 2000m 6 gate WTA wins 13% (avg 17%) · 38
Twat	437	0.4× avg	1600m 6 gate madness top 3 63% (avg 50%) · 24	1800m 24 gate madness top 3 0.0% (avg 13%) · 47 2200m 24 gate madness top 3 1.8% (avg 13%) · 56 1400m 12 gate madness top 3 0.0% (avg 25%) · 11
J J Gabriel	412	1.2× avg	1000m 22 gate WTA wins 22% (avg 4.5%) · 36 1200m 22 gate WTA wins 18% (avg 4.5%) · 22 1400m 22 gate WTA wins 17% (avg 4.5%) · 18	1800m 24 gate madness top 3 5.6% (avg 13%) · 36 1000m 12 gate madness top 3 10% (avg 25%) · 10 1600m 24 gate madness top 3 0.0% (avg 13%) · 7
Arc Raider	379	1.1× avg	1400m 24 gate WTA wins 33% (avg 4.2%) · 9 1200m 24 gate WTA wins 22% (avg 4.2%) · 9 1600m 22 gate WTA wins 14% (avg 4.5%) · 22	1400m 4 gate WTA wins 8.3% (avg 25%) · 12 1600m 24 gate madness top 3 0.0% (avg 13%) · 7 1200m 24 gate madness top 3 5.9% (avg 13%) · 17
Speedy Freak	306	1.1× avg	1200m 24 gate madness top 3 35% (avg 13%) · 17 1000m 24 gate madness top 3 23% (avg 13%) · 22 1400m 24 gate WTA wins 11% (avg 4.2%) · 9	1600m 24 gate madness top 3 0.0% (avg 13%) · 7 1000m 16 gate WTA wins 0.0% (avg 6.3%) · 10 1000m 22 gate WTA wins 2.8% (avg 4.5%) · 36
Expensive Earth	306	0.0× avg	—	2200m 24 gate madness top 3 0.0% (avg 13%) · 69 1400m 24 gate madness top 3 0.0% (avg 13%) · 22 1000m 24 gate madness top 3 0.0% (avg 13%) · 22
Hoofey	236	0.6× avg	2000m 22 gate WTA wins 8.6% (avg 4.5%) · 35 1600m 22 gate WTA wins 4.5% (avg 4.5%) · 22	2200m 24 gate madness top 3 2.9% (avg 13%) · 69 2000m 12 gate madness top 3 9.1% (avg 25%) · 22 1800m 24 gate madness top 3 6.4% (avg 13%) · 47
Living Mirage	206	0.5× avg	—	1000m 22 gate WTA wins 0.0% (avg 4.5%) · 36 2000m 22 gate WTA wins 0.0% (avg 4.5%) · 35 1800m 24 gate madness top 3 6.4% (avg 13%) · 47
Radicalised WFH	173	0.3× avg	1000m 24 gate madness top 3 14% (avg 13%) · 22	1200m 24 gate madness top 3 0.0% (avg 13%) · 17 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 36 2200m 24 gate madness top 3 0.0% (avg 13%) · 13
Ok Blood Sprinter	142	0.0× avg	—	1400m 24 gate madness top 3 0.0% (avg 13%) · 22 1000m 24 gate madness top 3 0.0% (avg 13%) · 22 1000m 22 gate WTA wins 0.0% (avg 4.5%) · 36
Left Eye Lopez	91	0.1× avg	—	1000m 22 gate WTA wins 0.0% (avg 4.5%) · 36 2200m 24 gate madness top 3 0.0% (avg 13%) · 13 1000m 24 gate madness top 3 4.5% (avg 13%) · 22
Blazing Crystal	64	0.0× avg	—	2000m 22 gate WTA wins 0.0% (avg 4.5%) · 35 2200m 16 gate WTA wins 0.0% (avg 6.3%) · 18 2200m 22 gate WTA wins 0.0% (avg 4.5%) · 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.

Killer Clowns: Power 54.4, #12. 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).