SnowT — CS2 Stats

US76561198129977363[U:1:169711635]Steam profile ↗1 game ban

1,672Tracked matches61%Win rate2020Tracked since

4,591Hours in CS2Hrs last 2 wks

CSDB Rating6.9 SolidAggressive Rifler

WingmanLegendary Eagle

Ladder ranks via Leetify

Performance scores

Aim84

Positioning61

Utility64

0–100 skill scores via Leetify.

Recent form

HOT45–49–6Last 10045%Win rateWWWWWWWLWW

Last 10 vs previous 10: +30pp win rate · -0.03 avg rating

Player DNA

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

Aim8.4

Aggression10.0

Utility6.4

Positioning6.1

Opening Duels4.7

Clutch3.2

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 device 95% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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

Reaction time. 608ms 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

Aim8.4

Positioning6.1

Utility6.4

Mechanics8.0

Opening Duels4.7

Win Impact8.6

Composite 6.9/10 (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 rating0.06+0.03

first ⅓ avg 0.02 → last ⅓ avg 0.06

Reaction time610ms−14ms

first ⅓ avg 624ms → last ⅓ avg 610ms

Headshot accuracy25.1%+5.4%

first ⅓ avg 19.7% → last ⅓ avg 25.1%

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

0.50Best rating — mirage 1–1

13–1Biggest win — mirage

7Longest win streak

W7Current streak

7–14In matches decided by ≤2 rounds

4Overtime games

Map breakdown

ancientBest map · 67% over 9infernoWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	25	11–14	44%	0.05
dust2	C	17	7–10	41%	0.02
cache	B	16	8–8	50%	0.03
inferno	D	13	4–9	31%	0.04
ancient	S	9	6–3	67%	0.01
anubis	D	6	2–4	33%	0.04
nuke	D	6	2–4	33%	-0.00
office	—	2	2–0	100%	0.08
overpass	—	2	1–1	50%	0.05
train	—	1	1–0	100%	0.06
fachwerk	—	1	1–0	100%	0.13
boulder	—	1	0–1	0%	0.05
shelter	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

138,386Lifetime kills

1.03K/D

11,410Matches

62.9%Match win rate · Top 5% of tracked players

46.0%Headshot % · Top 50% of tracked players

14.2%Shot accuracy · Top 50% of tracked players

20,700MVPs

2,802Hours (in match)

6,012Bombs planted

3,550Bombs defused

Most-used weapons

AK-4740,065

AWP21,639

M4A4 / M4A1-S17,694

Desert Eagle11,079

P2000 / USP-S8,901

Glock-185,378

SSG 083,662

Knife3,318

P2502,895

MP91,846

Lifetime map wins

12,505dust2

11,719inferno

2,055nuke

2,030train

1,729vertigo

1,219cbble

797office

749lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

348Matches

51%Win rate

1.09Avg K/D

76.0ADR

53%Headshot %

Clutches & streaks

36%1v1 clutch win

17%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	74	53%	1.12	15.9
Inferno	57	61%	1.14	15.6
Ancient	48	48%	0.98	13.8
Dust2	39	49%	1.15	16.1
Anubis	15	33%	0.86	12.9
Vertigo	13	54%	1.34	15.6
Nuke	11	64%	1.09	14.4
Overpass	4	100%	1.18	16.8

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.

24.7%Headshot accuracy

35.5%Accuracy (enemy spotted)

37.0%Spray accuracy

86.2%Counter-strafing

8.3°Preaim

608msReaction time

53.6%T opening success

43.9%CT opening success

0.66Enemies flashed / flash

11.8%Flash assists

11.21HE damage / grenade

6.35Flashes / match

Recommended for you

Spend your practice time on Inferno

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

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	13–3	0.07	17%	25 Aug →
train	13–7	0.06	42%	16 Aug →
ancient	13–8	0.09	23%	10 Aug →
mirage	13–7	-0.03	10%	10 Aug →
dust2	13–8	-0.00	12%	5 Aug →
ancient	13–6	0.00	20%	3 Aug →
cache	13–11	0.03	27%	26 Jul →
anubis	10–13	0.05	24%	23 Jul →
anubis	13–8	0.17	21%	23 Jul →
cache	13–2	0.01	25%	23 Jul →
dust2	13–6	0.06	29%	22 Jul →
mirage	13–6	0.00	32%	22 Jul →
dust2	9–13	0.08	25%	22 Jul →
cache	6–13	0.05	31%	20 Jul →
mirage	13–4	0.05	33%	20 Jul →
cache	13–2	0.13	37%	20 Jul →
dust2	13–2	0.17	19%	19 Jul →
mirage	13–11	0.06	28%	19 Jul →
cache	12–12	0.02	16%	19 Jul →
mirage	12–12	0.12	22%	19 Jul →
mirage	9–13	0.03	16%	16 Jul →
cache	4–13	0.03	30%	16 Jul →
mirage	2–13	0.14	35%	15 Jul →
dust2	13–11	0.02	33%	14 Jul →
mirage	7–13	0.15	15%	14 Jul →
dust2	9–13	0.12	21%	12 Jul →
cache	9–13	0.06	15%	12 Jul →
mirage	6–13	0.09	25%	11 Jul →
cache	13–9	0.09	35%	11 Jul →
inferno	8–13	0.04	29%	11 Jul →
mirage	11–13	-0.00	18%	11 Jul →
anubis	8–13	-0.06	26%	11 Jul →
cache	13–6	0.00	37%	11 Jul →
nuke	13–10	-0.05	24%	11 Jul →
fachwerk	13–8	0.13	23%	10 Jul →
boulder	8–13	0.05	14%	10 Jul →
office	13–6	0.13	34%	10 Jul →
office	13–11	0.03	24%	10 Jul →
shelter	6–13	0.03	21%	9 Jul →
dust2	4–13	-0.03	23%	8 Jul →
inferno	12–12	0.00	25%	6 Jul →
inferno	7–9	-0.03	32%	6 Jul →
inferno	9–2	0.06	27%	6 Jul →
ancient	11–13	0.03	16%	6 Jul →
anubis	11–13	0.05	28%	6 Jul →
nuke	9–13	-0.02	30%	6 Jul →
mirage	8–13	0.02	29%	6 Jul →
ancient	13–8	0.03	32%	6 Jul →
dust2	7–13	-0.08	18%	5 Jul →
ancient	13–11	-0.02	23%	5 Jul →
ancient	13–4	0.07	18%	5 Jul →
inferno	11–13	0.06	15%	5 Jul →
nuke	15–15	0.03	22%	5 Jul →
ancient	13–7	-0.07	24%	4 Jul →
dust2	7–13	-0.01	21%	4 Jul →
nuke	8–13	0.03	22%	4 Jul →
inferno	10–13	0.07	18%	4 Jul →
inferno	13–6	0.08	24%	4 Jul →
dust2	16–12	0.01	31%	3 Jul →
mirage	13–6	0.01	20%	3 Jul →
overpass	9–13	0.06	24%	3 Jul →
dust2	13–4	0.02	13%	3 Jul →
mirage	13–4	0.01	17%	3 Jul →
cache	1–13	-0.06	22%	2 Jul →
cache	9–13	-0.02	21%	1 Jul →
cache	13–5	0.07	41%	1 Jul →
mirage	9–13	-0.03	24%	30 Jun →
inferno	5–13	-0.05	13%	30 Jun →
anubis	13–2	0.07	25%	30 Jun →
anubis	7–13	-0.06	11%	30 Jun →
mirage	13–4	0.10	16%	30 Jun →
overpass	13–9	0.04	12%	30 Jun →
nuke	11–13	-0.04	26%	29 Jun →
mirage	13–4	0.01	13%	29 Jun →
dust2	11–13	-0.01	15%	28 Jun →
nuke	13–9	0.03	18%	28 Jun →
mirage	9–13	0.00	10%	28 Jun →
dust2	13–11	-0.06	22%	28 Jun →
dust2	3–13	0.01	30%	28 Jun →
inferno	16–13	0.04	12%	27 Jun →
dust2	10–13	0.00	28%	27 Jun →
cache	11–13	0.02	19%	25 Jun →
cache	13–10	-0.03	18%	24 Jun →
inferno	9–4	0.09	13%	23 Jun →
inferno	7–9	-0.01	12%	23 Jun →
mirage	13–1	0.05	11%	23 Jun →
mirage	9–13	0.02	35%	23 Jun →
mirage	6–13	-0.07	22%	23 Jun →
ancient	14–16	-0.02	14%	23 Jun →
cache	13–11	0.03	27%	23 Jun →
mirage	13–10	-0.04	19%	22 Jun →
mirage	11–13	0.01	22%	22 Jun →
ancient	2–13	-0.01	17%	22 Jun →
inferno	8–13	0.07	21%	22 Jun →
cache	3–8	0.02	48%	22 Jun →
inferno	8–8	0.14	26%	22 Jun →
dust2	12–12	-0.03	18%	19 Jun →
mirage	11–13	-0.01	9%	19 Jun →
mirage	1–1	0.50	27%	19 Jun →
dust2	11–13	0.01	19%	19 Jun →