railm0 — CS2 Stats

76561197960866331[U:1:600603]Steam profile ↗✓ No bans

2,207Tracked matches43%Win rate2020Tracked since

CSDB Rating5.5 SolidAggressive Rifler

FaceitLevel 8 · 1,845 ELOTop 31.2% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim71

Positioning66

Utility62

0–100 skill scores via Leetify.

Recent form

COLD43–57Last 10043%Win rateLLLWWWLLLL

Last 10 vs previous 10: -30pp win rate · -0.02 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.1

Aggression8.0

Utility6.2

Positioning6.6

Opening Duels3.5

Clutch2.8

Strong CT-side opener

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like b1t 93% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

T-side openings. Opening success drops from 56% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 581ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim7.1

Positioning6.6

Utility6.2

Mechanics5.5

Opening Duels3.5

Win Impact2.8

Composite 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.01

Reaction time570ms+3ms

first ⅓ avg 567ms → last ⅓ avg 570ms

Headshot accuracy19.9%+1.0%

first ⅓ avg 18.8% → last ⅓ avg 19.9%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.14Best rating — anubis 13–8

13–2Biggest win — ancient

5Longest win streak

L3Current streak

12–10In matches decided by ≤2 rounds

12Overtime games

Map breakdown

anubisBest map · 48% over 21overpassWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
anubis	B	21	10–11	48%	0.01
ancient	C	19	8–11	42%	0.01
inferno	B	15	7–8	47%	0.01
nuke	B	15	7–8	47%	-0.01
cache	B	13	6–7	46%	0.00
overpass	C	8	3–5	38%	-0.01
mirage	—	4	1–3	25%	-0.01
dust2	—	3	0–3	0%	-0.03
vertigo	—	1	0–1	0%	-0.01
train	—	1	1–0	100%	0.07

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,533Matches

49%Win rate

1.04Avg K/D

81.3ADR

44%Headshot %

Clutches & streaks

34%1v1 clutch win

19%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	292	51%	1.11	16.9
Ancient	257	47%	1.06	16.5
Anubis	249	49%	1.05	16.0
Nuke	141	54%	1.04	15.6
Mirage	124	41%	0.95	15.4
Overpass	101	50%	1.07	16.3
Dust2	71	45%	1.00	14.6
Train	55	56%	1.28	17.2

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

20.0%Headshot accuracy

35.1%Accuracy (enemy spotted)

37.0%Spray accuracy

74.9%Counter-strafing

9.5°Preaim

581msReaction time

31.7%T opening success

56.2%CT opening success

0.65Enemies flashed / flash

7.5%Flash assists

11.95HE damage / grenade

10.19Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 31.6641% — below the 40% mark we flag

Spend your practice time on Overpass

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–16	-0.03	17%	24 Aug →
ancient	10–13	0.04	26%	23 Aug →
anubis	11–13	-0.11	17%	22 Aug →
anubis	13–6	0.01	20%	22 Aug →
cache	13–7	0.02	28%	16 Aug →
anubis	13–5	0.09	14%	16 Aug →
inferno	11–13	0.03	28%	15 Aug →
ancient	10–13	0.01	31%	15 Aug →
vertigo	4–13	-0.01	26%	6 Aug →
ancient	9–13	-0.04	17%	6 Aug →
anubis	11–13	-0.05	17%	5 Aug →
ancient	13–7	0.04	17%	4 Aug →
inferno	7–13	0.03	19%	11 Jul →
cache	13–11	-0.01	22%	11 Jul →
nuke	16–12	-0.03	26%	11 Jul →
cache	13–4	0.12	20%	11 Jul →
inferno	1–13	-0.02	32%	28 Jun →
train	13–6	0.07	27%	20 Jun →
anubis	13–10	0.03	11%	20 Jun →
nuke	12–16	0.04	19%	11 Jun →
anubis	9–13	0.05	15%	8 Jun →
nuke	8–13	-0.07	17%	8 Jun →
ancient	16–13	0.01	15%	4 Jun →
ancient	16–13	0.01	21%	29 May →
ancient	11–13	-0.03	9%	29 May →
ancient	10–13	-0.01	13%	26 May →
cache	10–13	0.04	27%	26 May →
anubis	3–13	-0.01	14%	26 May →
ancient	13–6	0.08	20%	22 May →
ancient	13–11	-0.01	18%	22 May →
cache	9–13	-0.00	23%	22 May →
overpass	8–13	-0.04	14%	21 May →
nuke	11–13	-0.00	15%	21 May →
anubis	9–13	0.05	23%	21 May →
inferno	13–11	-0.04	23%	21 May →
nuke	13–11	0.01	19%	14 May →
anubis	13–10	-0.07	12%	14 May →
ancient	13–9	0.01	27%	14 May →
anubis	5–13	-0.03	11%	14 May →
overpass	11–13	-0.05	9%	14 May →
cache	6–13	-0.05	18%	12 May →
cache	3–13	-0.06	11%	3 May →
overpass	16–14	0.01	10%	30 Apr →
cache	10–13	-0.04	22%	30 Apr →
nuke	13–7	0.06	17%	30 Apr →
inferno	16–14	0.02	17%	30 Apr →
cache	13–11	-0.00	7%	29 Apr →
ancient	13–2	0.02	13%	29 Apr →
anubis	13–8	0.14	22%	29 Apr →
ancient	6–13	0.04	11%	24 Apr →
dust2	5–13	-0.03	17%	23 Apr →
anubis	4–13	-0.05	16%	23 Apr →
nuke	14–16	-0.02	20%	23 Apr →
overpass	5–13	-0.08	15%	23 Apr →
cache	9–13	0.05	14%	23 Apr →
cache	13–9	0.01	12%	23 Apr →
cache	13–7	0.01	24%	23 Apr →
overpass	13–9	-0.00	14%	17 Apr →
nuke	13–11	0.03	12%	16 Apr →
anubis	11–13	0.01	20%	16 Apr →
anubis	12–16	0.02	14%	15 Apr →
nuke	8–13	-0.04	8%	8 Apr →
inferno	6–13	0.01	21%	6 Apr →
anubis	13–6	0.07	11%	28 Mar →
ancient	7–13	-0.02	16%	27 Mar →
dust2	5–13	0.02	30%	27 Mar →
inferno	13–10	-0.02	4%	27 Mar →
nuke	12–16	-0.04	13%	26 Mar →
inferno	6–13	-0.04	21%	26 Mar →
overpass	13–2	0.07	23%	19 Mar →
overpass	6–13	-0.02	21%	19 Mar →
nuke	16–14	0.01	19%	19 Mar →
anubis	13–8	-0.01	16%	18 Mar →
anubis	7–13	-0.04	24%	17 Mar →
inferno	13–6	0.03	14%	17 Mar →
ancient	7–13	-0.03	13%	17 Mar →
dust2	1–13	-0.06	30%	11 Mar →
inferno	13–9	0.07	21%	11 Mar →
nuke	13–11	-0.06	26%	9 Mar →
ancient	7–13	0.03	16%	9 Mar →
ancient	9–13	0.02	17%	8 Mar →
anubis	13–8	0.05	19%	2 Mar →
inferno	6–13	-0.05	26%	2 Mar →
anubis	7–13	0.02	28%	2 Mar →
inferno	4–13	0.00	8%	28 Feb →
nuke	13–8	0.10	23%	28 Feb →
nuke	8–13	-0.05	19%	27 Feb →
mirage	8–13	-0.06	18%	27 Feb →
mirage	14–16	0.00	15%	21 Feb →
mirage	13–9	0.04	31%	20 Feb →
anubis	13–9	-0.05	11%	20 Feb →
ancient	13–11	0.05	16%	20 Feb →
overpass	6–13	0.03	20%	19 Feb →
inferno	8–13	0.02	18%	19 Feb →
anubis	13–9	0.06	25%	18 Feb →
inferno	13–7	-0.01	22%	17 Feb →
ancient	11–13	-0.06	9%	17 Feb →
nuke	7–13	-0.02	17%	17 Feb →
inferno	13–11	0.04	10%	7 Feb →
mirage	7–13	-0.04	13%	7 Feb →