Slays — CS2 Stats

76561198077250524[U:1:116984796]Steam profile ↗

162Tracked matches43%Win rate2020Tracked since

2,073Hours in CS

CSDB Rating6.8 SolidAggressive Rifler

Premier CS Rating19,051Purple band · top ~12.3% of ranked players (population est.)

CSDB Leaderboard#8399 of 16897 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim87

Positioning68

Utility60

0–100 skill scores via Leetify.

Recent form

STEADY46–45–9Last 10046%Win rateLWWLLLWWWW

Last 10 vs previous 10: +40pp win rate · +0.02 avg rating

Player DNA

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

Aim8.7

Aggression8.7

Utility6.0

Positioning6.8

Opening Duels4.4

Sharp aimerEffective flashes

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 donk 95% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Strengths

Aim. Aim score of 87 — the mechanical foundation is a clear strength.

Flashes. 0.82 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 655ms 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

Aim8.7

Positioning6.8

Utility6.0

Mechanics8.3

Opening Duels4.4

Win Impact2.6

Composite 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.02

Reaction time645ms−3ms

first ⅓ avg 648ms → last ⅓ avg 645ms

Headshot accuracy27.5%−3.2%

first ⅓ avg 30.7% → last ⅓ avg 27.5%

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

0.20Best rating — nuke 13–2

13–0Biggest win — mirage

7Longest win streak

9–11In matches decided by ≤2 rounds

7Overtime games

Map breakdown

cacheBest map · 63% over 8infernoWeakest map · 35% over 20

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	23	10–13	43%	0.02
dust2	B	22	10–12	45%	0.02
inferno	C	20	7–13	35%	0.04
cache	A	8	5–3	63%	0.04
ancient	C	7	3–4	43%	0.01
train	B	6	3–3	50%	0.02
overpass	A	5	3–2	60%	0.05
nuke	—	4	3–1	75%	0.08
vertigo	—	2	0–2	0%	-0.00
anubis	—	2	2–0	100%	-0.03
grail	—	1	0–1	0%	-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (35% over 20). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

63,682Lifetime kills

1.03K/D

3,402Matches

41.2%Match win rate

36.8%Headshot %

17.4%Shot accuracy · Top 25% of tracked players

7,103MVPs

2,073Hours (in match)

2,055Bombs planted

662Bombs defused

Most-used weapons

AK-4721,742

AWP11,199

M4A4 / M4A1-S7,409

Desert Eagle6,940

P2000 / USP-S2,776

Glock-182,141

Tec-91,204

Five-SeveN1,193

P901,118

P2501,037

Lifetime map wins

8,147dust2

4,942inferno

682train

602nuke

528cbble

507vertigo

148office

73lake

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

Faceit stats

Combat

122Matches

55%Win rate

1.10Avg K/D

—ADR

38%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

7Longest win streak

Recent Faceit resultsLWWLW

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.

26.8%Headshot accuracy

38.6%Accuracy (enemy spotted)

43.0%Spray accuracy

87.3%Counter-strafing

9.2°Preaim

655msReaction time

42.3%T opening success

52.6%CT opening success

0.82Enemies flashed / flash

8.6%Flash assists

9.15HE damage / grenade

9.38Flashes / 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.

35% win rate across 20 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
dust2	6–13	0.03	18%	26 Aug →
dust2	13–9	0.00	31%	19 Aug →
nuke	13–4	0.10	33%	7 Aug →
dust2	8–13	0.01	40%	7 Aug →
nuke	10–13	0.02	31%	5 Aug →
ancient	11–13	-0.03	35%	5 Aug →
cache	13–10	-0.02	28%	5 Aug →
nuke	13–2	0.20	58%	5 Aug →
mirage	13–11	-0.01	29%	5 Aug →
mirage	13–7	-0.02	37%	2 Aug →
cache	9–13	-0.04	25%	2 Aug →
vertigo	12–12	-0.01	17%	2 Aug →
inferno	13–16	-0.00	28%	2 Aug →
dust2	6–13	-0.03	41%	1 Aug →
cache	13–11	0.03	33%	1 Aug →
mirage	5–13	0.06	23%	25 Jul →
dust2	11–13	0.05	27%	25 Jul →
inferno	3–13	-0.00	27%	25 Jul →
cache	13–4	0.08	28%	25 Jul →
ancient	8–13	-0.00	23%	25 Jul →
cache	13–8	0.11	30%	23 Jul →
dust2	6–13	0.07	30%	23 Jul →
mirage	13–5	0.02	7%	23 Jul →
cache	13–16	0.02	20%	19 Jul →
anubis	13–6	-0.04	10%	16 Jul →
ancient	15–15	-0.01	14%	24 Jun →
mirage	11–13	0.01	27%	24 Jun →
dust2	6–13	-0.04	21%	17 Jun →
inferno	13–7	0.05	28%	16 Jun →
mirage	11–13	-0.04	22%	15 Jun →
dust2	13–4	0.01	37%	12 Jun →
overpass	13–2	0.08	28%	10 Jun →
mirage	13–11	-0.03	25%	3 Jun →
dust2	16–12	-0.02	16%	29 May →
ancient	13–11	0.02	30%	29 May →
ancient	13–2	0.01	17%	27 May →
inferno	13–9	0.08	36%	25 May →
mirage	11–13	0.01	26%	25 May →
anubis	13–9	-0.02	41%	22 May →
dust2	13–16	0.02	33%	22 May →
cache	12–12	0.10	20%	11 May →
cache	13–4	0.05	33%	30 Apr →
dust2	13–1	0.13	6%	24 Feb →
dust2	13–4	-0.03	24%	24 Feb →
mirage	1–13	-0.02	28%	24 Feb →
nuke	13–4	0.01	24%	24 Feb →
dust2	13–3	0.09	25%	24 Feb →
mirage	10–13	0.07	17%	24 Feb →
inferno	11–13	0.07	21%	24 Feb →
inferno	10–13	0.06	22%	23 Feb →
inferno	13–11	0.11	25%	23 Feb →
inferno	11–13	0.01	25%	23 Feb →
inferno	13–3	0.11	26%	23 Feb →
inferno	12–16	-0.01	25%	22 Feb →
mirage	3–13	-0.03	33%	22 Feb →
mirage	8–13	-0.02	26%	22 Feb →
inferno	10–13	0.04	31%	21 Feb →
dust2	7–13	0.05	39%	21 Feb →
overpass	13–7	0.10	26%	21 Feb →
dust2	15–15	0.01	26%	21 Feb →
dust2	13–5	0.05	26%	20 Feb →
overpass	13–5	0.04	22%	20 Feb →
inferno	7–13	0.02	34%	20 Feb →
mirage	13–11	0.12	28%	20 Feb →
mirage	9–13	-0.01	41%	20 Feb →
dust2	1–13	0.01	26%	19 Feb →
inferno	13–11	-0.01	44%	18 Feb →
inferno	7–13	-0.00	14%	18 Feb →
mirage	11–13	-0.05	15%	18 Feb →
dust2	13–2	-0.01	31%	11 Feb →
overpass	12–12	0.08	36%	25 Jan →
ancient	4–13	0.00	42%	25 Jan →
inferno	11–13	0.09	31%	24 Jan →
mirage	13–4	0.05	27%	24 Jan →
mirage	7–13	0.01	21%	3 Jan →
train	4–0	0.16	71%	3 Jan →
dust2	9–13	0.06	45%	3 Jan →
mirage	13–5	0.01	21%	17 Dec →
inferno	7–13	0.01	25%	23 Oct →
train	2–13	-0.04	36%	15 Jun →
vertigo	7–13	0.01	35%	15 Jun →
grail	2–13	-0.03	47%	15 Jun →
train	13–7	0.02	20%	28 Feb →
dust2	13–3	0.07	43%	27 Feb →
inferno	13–4	0.03	12%	27 Feb →
ancient	13–8	0.07	32%	13 Feb →
train	12–12	-0.00	18%	13 Feb →
inferno	13–3	0.03	24%	12 Feb →
mirage	13–4	-0.01	22%	12 Feb →
train	7–13	-0.05	30%	11 Feb →
inferno	9–13	0.02	35%	11 Feb →
mirage	12–12	0.09	24%	11 Feb →
mirage	13–0	0.06	83%	10 Feb →
dust2	12–12	0.01	25%	10 Feb →
inferno	11–13	0.02	26%	9 Feb →
mirage	12–12	0.10	36%	8 Feb →
overpass	11–13	-0.04	22%	8 Feb →
train	13–11	0.03	28%	7 Feb →
mirage	13–11	0.01	15%	7 Feb →
dust2	13–8	0.00	21%	7 Feb →