ddddd — CS2 Stats

RS76561198135183022[U:1:174917294]Steam profile ↗✓ No bans

1,777Tracked matches23%Win rate2020Tracked since

17,440Hours in CS

CSDB Rating3.5 Learning

FaceitLevel 10 · 3,388 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=3,007), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	63.9%	52.0%
Shot accuracy	16.0%	13.7%
Kill/death ratio	1.02	1.08
Match win rate	49.2%	48.8%

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Performance scores

Aim41

Positioning31

Utility35

0–100 skill scores via Leetify.

Recent form

COLD44–52–4Last 10044%Win rateLTWLLWLWTL

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

Aim4.1

Aggression1.7

Utility3.5

Positioning3.1

Opening Duels0.0

Clutch3.8

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 NiKo 68% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower opening-fight frequency; 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

Reaction time. 702ms 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

Aim4.1

Positioning3.1

Utility3.5

Mechanics6.5

Opening Duels0.0

Win Impact0.0

Composite 3.5/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.04−0.06

first ⅓ avg 0.01 → last ⅓ avg -0.04

Reaction time709ms+168ms

first ⅓ avg 540ms → last ⅓ avg 709ms

Headshot accuracy13.7%−6.7%

first ⅓ avg 20.4% → last ⅓ avg 13.7%

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

0.17Best rating — mirage 13–9

13–1Biggest win — dust2

9Longest win streak

5–6In matches decided by ≤2 rounds

9Overtime games

Map breakdown

anubisBest map · 70% over 10infernoWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	33	13–20	39%	-0.01
ancient	B	20	10–10	50%	-0.00
dust2	C	11	4–7	36%	0.01
anubis	S	10	7–3	70%	0.02
inferno	D	8	2–6	25%	-0.04
vertigo	A	7	4–3	57%	0.02
overpass	C	5	2–3	40%	-0.02
nuke	—	4	2–2	50%	0.01
train	—	2	0–2	0%	-0.14

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

427,468Lifetime kills

1.02K/D

8,049Matches

49.2%Match win rate · Top 50% of Level 10 players

63.9%Headshot % · Top 25% of Level 10 players

16.0%Shot accuracy · Top 50% of Level 10 players

28,199MVPs

17,440Hours (in match)

5,506Bombs planted

4,827Bombs defused

Most-used weapons

AK-47212,009

M4A4 / M4A1-S80,824

P2000 / USP-S38,594

AWP22,988

Desert Eagle20,859

Glock-1810,286

SG 5535,158

Galil AR4,647

FAMAS3,985

MP93,936

Lifetime map wins

20,563dust2

16,594inferno

3,562vertigo

2,522train

2,382nuke

252cbble

82office

73assault

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

Faceit stats

Combat

2,756Matches

54%Win rate

1.22Avg K/D

79.8ADR

51%Headshot %

Clutches & streaks

39%1v1 clutch win

23%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	236	57%	1.18	16.4
Mirage	223	54%	1.17	16.4
Anubis	164	53%	1.19	16.2
Dust2	78	64%	1.11	15.6
Inferno	57	56%	1.23	17.7
Vertigo	25	48%	1.32	18.7
Overpass	17	53%	1.16	16.2
Nuke	12	25%	0.96	14.8

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.

13.6%Headshot accuracy

30.1%Accuracy (enemy spotted)

33.2%Spray accuracy

79.1%Counter-strafing

10.1°Preaim

702msReaction time

15.4%T opening success

27.7%CT opening success

0.46Enemies flashed / flash

8.6%Flash assists

5.75HE damage / grenade

3.44Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.61% — below the 15% mark we flag
Aim Training →
Best CS2 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 702.4429ms — above the 700ms mark we flag
Aim Training →
Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4559 — below the 0.5 mark we flag
Grenade Lineups →

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.

25% win rate across 8 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
nuke	2–13	-0.12	4%	1 Mar →
mirage	15–15	-0.05	10%	20 Feb →
inferno	4–1	-0.05	0%	20 Feb →
dust2	2–13	0.01	18%	20 Feb →
inferno	3–8	-0.08	0%	20 Feb →
ancient	13–11	-0.04	13%	20 Feb →
dust2	9–13	-0.03	21%	20 Feb →
mirage	13–10	-0.06	23%	19 Feb →
mirage	12–12	-0.04	12%	5 Feb →
mirage	7–13	0.01	17%	4 Feb →
mirage	13–7	-0.04	5%	1 Feb →
dust2	13–1	0.08	26%	1 Feb →
inferno	13–2	-0.01	20%	31 Jan →
mirage	10–13	0.03	11%	27 Jan →
mirage	3–13	0.07	11%	26 Jan →
mirage	7–13	-0.06	16%	30 Nov →
mirage	11–13	-0.07	24%	29 Nov →
dust2	4–13	-0.08	15%	29 Nov →
mirage	2–13	-0.08	8%	28 Nov →
overpass	6–10	-0.13	7%	27 Nov →
inferno	6–13	-0.08	13%	27 Nov →
inferno	0–13	-0.05	6%	27 Nov →
mirage	1–13	-0.11	13%	26 Nov →
inferno	10–13	-0.00	15%	25 Nov →
mirage	12–12	-0.03	16%	25 Nov →
mirage	3–13	0.00	22%	24 Nov →
inferno	11–13	-0.04	11%	24 Nov →
train	4–13	-0.11	16%	23 Nov →
mirage	5–13	-0.08	9%	23 Nov →
ancient	15–15	-0.07	10%	23 Nov →
dust2	10–13	-0.07	11%	23 Nov →
mirage	8–2	-0.03	21%	23 Nov →
mirage	4–13	-0.06	29%	22 Nov →
mirage	0–13	-0.09	0%	21 Nov →
mirage	10–13	-0.06	14%	20 Nov →
mirage	13–3	0.02	23%	19 Nov →
mirage	3–13	-0.06	12%	19 Nov →
mirage	3–13	-0.04	18%	19 Nov →
mirage	9–13	0.03	8%	20 Oct →
dust2	1–7	-0.03	11%	15 Oct →
dust2	13–9	0.05	16%	13 Oct →
mirage	9–13	0.06	20%	13 Oct →
ancient	13–9	0.05	30%	11 Oct →
mirage	10–13	-0.01	36%	11 Oct →
mirage	16–14	-0.03	12%	4 Oct →
ancient	14–16	0.05	16%	2 Oct →
mirage	13–11	-0.01	23%	22 Sept →
dust2	13–10	0.06	37%	21 Sept →
nuke	13–5	0.10	30%	21 Sept →
dust2	6–13	0.14	43%	20 Sept →
mirage	13–10	0.01	30%	20 Sept →
dust2	5–13	-0.02	28%	17 Sept →
mirage	13–6	0.14	21%	14 Sept →
train	7–13	-0.18	0%	31 Mar →
nuke	9–13	0.06	28%	28 Mar →
inferno	7–13	-0.01	52%	21 Mar →
ancient	4–13	-0.06	9%	18 Mar →
ancient	13–8	-0.01	20%	7 Mar →
mirage	13–9	-0.05	15%	1 Mar →
anubis	14–16	-0.00	37%	28 Feb →
mirage	13–5	-0.00	21%	2 Feb →
dust2	16–13	-0.02	10%	25 Jan →
mirage	13–9	0.17	30%	22 Jan →
ancient	13–6	0.01	26%	22 Jan →
mirage	13–6	0.11	37%	10 Jan →
anubis	13–10	-0.01	16%	9 Jan →
nuke	13–5	0.02	15%	7 Jan →
mirage	13–5	0.06	28%	24 Dec →
ancient	13–10	0.04	20%	10 Oct →
anubis	5–13	-0.07	11%	10 Sept →
ancient	6–13	-0.06	11%	4 Mar →
ancient	13–7	0.06	17%	4 Mar →
vertigo	13–2	0.13	35%	4 Mar →
vertigo	8–13	-0.07	8%	2 Mar →
ancient	14–16	0.01	15%	29 Feb →
anubis	13–6	0.04	16%	27 Feb →
ancient	13–10	0.06	23%	22 Feb →
anubis	13–10	0.05	17%	20 Feb →
ancient	9–13	0.02	19%	19 Feb →
anubis	13–9	0.01	20%	19 Feb →
vertigo	9–13	0.04	20%	19 Feb →
ancient	2–13	-0.05	23%	16 Feb →
vertigo	13–11	0.01	19%	16 Feb →
anubis	13–6	0.08	23%	16 Feb →
ancient	5–13	-0.03	14%	15 Feb →
anubis	13–5	0.05	27%	15 Feb →
overpass	8–13	0.02	9%	10 Feb →
overpass	13–6	0.04	22%	10 Feb →
ancient	16–13	-0.01	24%	10 Feb →
vertigo	8–13	-0.01	21%	8 Feb →
ancient	13–11	0.01	15%	6 Feb →
vertigo	13–10	0.01	23%	6 Feb →
overpass	3–13	-0.04	33%	3 Feb →
vertigo	13–5	0.05	20%	3 Feb →
ancient	13–4	0.06	17%	3 Feb →
anubis	10–13	-0.01	25%	2 Feb →
anubis	16–13	0.05	24%	1 Feb →
ancient	11–13	0.03	19%	1 Feb →
ancient	3–13	-0.09	29%	31 Jan →
overpass	13–5	0.03	26%	31 Jan →