filwat — CS2 Stats

76561199162325981[U:1:1202060253]Steam profile ↗

180Tracked matches43%Win rate2025Tracked since

391Hours in CS1Hrs last 2 wks

CSDB Rating2.1 Learning

WingmanGold Nova I

Ladder ranks via Leetify

Performance scores

Aim25

Positioning23

Utility8

0–100 skill scores via Leetify.

Recent form

STEADY49–39–12Last 10049%Win rateLLLLLWTWWW

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

Player DNA

Aim2.5

Aggression1.1

Utility0.8

Positioning2.3

Opening Duels0.0

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 56% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower utility contribution; 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 32% on CT to 16% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 675ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 63% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim2.5

Positioning2.3

Utility0.8

Mechanics3.0

Opening Duels0.3

Win Impact2.6

Composite 2.1/10 (Learning), 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 rating-0.02−0.02

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time673ms−13ms

first ⅓ avg 686ms → last ⅓ avg 673ms

Headshot accuracy8.1%−6.8%

first ⅓ avg 14.9% → last ⅓ avg 8.1%

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

0.16Best rating — overpass 13–3

13–1Biggest win — nuke

8Longest win streak

L5Current streak

5–4In matches decided by ≤2 rounds

1Overtime games

Map breakdown

dust2Best map · 58% over 19infernoWeakest map · 43% over 7

Map	Grade	Played	Record	Win rate	Avg rating
nuke	B	27	13–14	48%	-0.02
mirage	B	20	9–11	45%	-0.04
dust2	A	19	11–8	58%	-0.01
cache	A	9	5–4	56%	-0.00
inferno	C	7	3–4	43%	-0.04
anubis	—	3	2–1	67%	0.05
vertigo	—	3	2–1	67%	-0.03
alpine	—	2	1–1	50%	0.04
ancient	—	2	0–2	0%	-0.05
train	—	2	1–1	50%	-0.01
overpass	—	2	1–1	50%	0.10
italy	—	1	0–1	0%	-0.01
shelter	—	1	0–1	0%	-0.05
boulder	—	1	1–0	100%	-0.00
fachwerk	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (43% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

9,421Lifetime kills

0.70K/D

860Matches

40.1%Match win rate

34.1%Headshot %

0.0%Shot accuracy

1,305MVPs

227Hours (in match)

731Bombs planted

267Bombs defused

Most-used weapons

M4A4 / M4A1-S2,697

AK-472,656

Galil AR548

MAC-10493

P2000 / USP-S431

MP9321

Glock-18316

FAMAS299

AWP206

P90192

Lifetime map wins

1,040nuke

861dust2

685inferno

465vertigo

126train

45italy

7office

1ar_shoots

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

Skill profile

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

7.7%Headshot accuracy

30.5%Accuracy (enemy spotted)

38.1%Spray accuracy

63.4%Counter-strafing

11.4°Preaim

675msReaction time

15.9%T opening success

32.3%CT opening success

0.16Enemies flashed / flash

0.0%Flash assists

2.78HE damage / grenade

3.38Flashes / 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 7.7099% — below the 15% 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 0.1631 — below the 0.5 mark we flag
Grenade Lineups →
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 15.8895% — below the 40% mark we flag

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.

43% win rate across 7 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	-0.04	6%	28 Aug →
dust2	4–13	0.01	12%	28 Aug →
italy	6–13	-0.01	6%	30 Jul →
nuke	7–13	-0.02	6%	22 Jul →
shelter	11–13	-0.05	11%	18 Jul →
boulder	13–3	-0.00	5%	17 Jul →
fachwerk	12–12	-0.07	6%	9 Jul →
nuke	13–9	-0.04	7%	6 Jul →
alpine	13–5	0.04	20%	6 Jul →
dust2	13–10	0.04	6%	5 Jul →
mirage	13–8	-0.07	6%	4 Jul →
nuke	13–1	-0.07	6%	2 Jul →
cache	3–13	-0.03	7%	1 Jul →
ancient	12–12	-0.03	11%	26 Jun →
inferno	6–13	-0.07	0%	25 Jun →
nuke	10–5	0.04	9%	24 Jun →
dust2	5–8	-0.06	10%	24 Jun →
train	9–13	-0.01	11%	23 Jun →
anubis	13–9	0.03	5%	22 Jun →
mirage	5–13	-0.03	12%	22 Jun →
nuke	13–4	-0.04	7%	21 Jun →
mirage	6–13	-0.07	3%	20 Jun →
nuke	13–9	-0.02	5%	18 Jun →
dust2	7–13	-0.05	9%	17 Jun →
mirage	2–13	-0.03	5%	16 Jun →
nuke	8–13	-0.02	8%	15 Jun →
dust2	8–13	-0.02	10%	9 Jun →
nuke	13–11	-0.03	6%	8 Jun →
mirage	13–6	-0.03	4%	7 Jun →
nuke	6–13	0.04	15%	6 Jun →
dust2	13–7	-0.00	19%	5 Jun →
nuke	13–4	-0.02	9%	4 Jun →
mirage	12–12	-0.02	6%	3 Jun →
nuke	13–11	-0.08	14%	2 Jun →
cache	1–13	-0.02	7%	27 May →
nuke	12–12	0.01	6%	26 May →
dust2	10–13	-0.03	17%	24 May →
nuke	13–7	0.02	11%	23 May →
inferno	12–12	-0.17	33%	22 May →
dust2	3–13	-0.01	17%	21 May →
nuke	4–13	-0.06	13%	20 May →
mirage	9–13	-0.01	7%	19 May →
nuke	8–13	-0.05	19%	18 May →
mirage	12–12	-0.05	14%	17 May →
nuke	12–12	-0.02	15%	16 May →
vertigo	9–13	-0.06	10%	15 May →
mirage	5–13	-0.05	6%	14 May →
nuke	10–1	-0.03	25%	14 May →
cache	13–8	0.01	4%	13 May →
dust2	5–13	-0.06	11%	12 May →
mirage	13–5	-0.04	13%	11 May →
nuke	11–13	-0.03	14%	10 May →
cache	10–13	-0.02	13%	9 May →
cache	13–11	-0.01	15%	8 May →
nuke	11–13	-0.08	12%	5 May →
mirage	13–6	-0.10	18%	4 May →
nuke	13–10	-0.02	15%	3 May →
cache	7–13	0.02	15%	3 May →
cache	13–3	0.02	16%	1 May →
cache	13–4	-0.01	12%	29 Apr →
cache	13–4	0.01	20%	29 Apr →
train	13–10	-0.01	12%	27 Apr →
nuke	10–13	-0.03	6%	26 Apr →
mirage	13–11	-0.05	3%	25 Apr →
dust2	13–6	0.01	10%	25 Apr →
overpass	13–3	0.16	12%	24 Apr →
inferno	8–13	-0.00	7%	23 Apr →
dust2	13–5	-0.03	10%	23 Apr →
nuke	13–8	0.00	2%	22 Apr →
nuke	12–12	0.01	8%	20 Apr →
mirage	13–5	-0.01	12%	19 Apr →
dust2	13–5	-0.02	13%	19 Apr →
mirage	12–12	-0.08	11%	17 Apr →
dust2	7–13	-0.05	30%	16 Apr →
anubis	10–13	-0.01	5%	15 Apr →
overpass	12–12	0.04	10%	14 Apr →
inferno	9–13	0.01	12%	13 Apr →
dust2	13–11	-0.01	7%	12 Apr →
vertigo	13–6	0.02	18%	12 Apr →
nuke	11–13	-0.02	8%	12 Apr →
alpine	9–13	0.03	15%	11 Apr →
dust2	8–2	0.03	13%	11 Apr →
mirage	6–13	-0.04	10%	11 Apr →
mirage	13–8	0.01	12%	10 Apr →
mirage	15–15	-0.10	15%	9 Apr →
anubis	13–2	0.12	21%	8 Apr →
dust2	13–4	0.11	11%	8 Apr →
mirage	0–13	-0.03	17%	7 Apr →
inferno	13–6	-0.05	15%	6 Apr →
mirage	13–9	-0.03	12%	5 Apr →
mirage	13–4	0.10	13%	3 Apr →
dust2	13–10	-0.07	38%	1 Apr →
dust2	13–4	0.09	24%	31 Mar →
inferno	13–8	0.01	23%	30 Mar →
nuke	13–2	0.02	21%	27 Mar →
inferno	13–9	-0.03	16%	26 Mar →
nuke	12–12	-0.02	26%	22 Mar →
ancient	3–13	-0.07	8%	19 Mar →
dust2	13–5	-0.05	27%	18 Mar →
vertigo	13–10	-0.06	11%	16 Mar →