goffs — CS2 Stats

US76561198075254880[U:1:114989152]Steam profile ↗✓ No bans

114Tracked matches39%Win rate2022Tracked since

287Hours in CS1Hrs last 2 wks

CSDB Rating2.8 Learning

Ladder ranks via Leetify

Performance scores

Aim18

Positioning42

Utility31

0–100 skill scores via Leetify.

Recent form

COLD46–46–8Last 10046%Win rateLLLWLLLWLL

Last 10 vs previous 10: -10pp win rate · +0.01 avg rating

Player DNA

Aim1.8

Aggression2.3

Utility3.1

Positioning4.2

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 66% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

Reaction time. 722ms 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

Aim1.8

Positioning4.2

Utility3.1

Mechanics5.3

Opening Duels0.2

Win Impact1.4

Composite 2.8/10 (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-0.04−0.02

first ⅓ avg -0.02 → last ⅓ avg -0.04

Reaction time705ms+59ms

first ⅓ avg 646ms → last ⅓ avg 705ms

Headshot accuracy18.4%+3.5%

first ⅓ avg 14.9% → last ⅓ avg 18.4%

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

0.06Best rating — vertigo 13–6

13–2Biggest win — train

5Longest win streak

L3Current streak

6–3In matches decided by ≤2 rounds

1Overtime games

Map breakdown

trainBest map · 78% over 9dust2Weakest map · 31% over 16

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	16	5–11	31%	-0.04
vertigo	B	12	6–6	50%	-0.04
ancient	A	12	7–5	58%	-0.01
mirage	A	11	6–5	55%	-0.03
train	S	9	7–2	78%	-0.02
inferno	D	9	3–6	33%	-0.01
nuke	S	8	6–2	75%	-0.02
anubis	D	6	2–4	33%	-0.04
overpass	B	6	3–3	50%	-0.05
cache	—	3	0–3	0%	-0.07
mills	—	3	0–3	0%	-0.03
office	—	2	0–2	0%	-0.04
jura	—	1	0–1	0%	-0.09
grail	—	1	0–1	0%	-0.03
thera	—	1	1–0	100%	0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (31% over 16). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

6,533Lifetime kills

0.83K/D

551Matches

39.9%Match win rate

34.6%Headshot %

14.9%Shot accuracy · Top 50% of tracked players

702MVPs

147Hours (in match)

530Bombs planted

77Bombs defused

Most-used weapons

AK-471,125

M4A4 / M4A1-S858

AWP651

P2000 / USP-S416

Glock-18368

AUG344

Desert Eagle323

SG 553281

P90211

MP9167

Lifetime map wins

833dust2

277inferno

168vertigo

156train

152nuke

44office

35lake

30dust

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.

18.5%Headshot accuracy

25.3%Accuracy (enemy spotted)

27.9%Spray accuracy

74.0%Counter-strafing

15.2°Preaim

722msReaction time

22.0%T opening success

31.8%CT opening success

0.67Enemies flashed / flash

1.7%Flash assists

7.09HE damage / grenade

4.23Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 15.1927° — above the 12° 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 721.5296ms — above the 700ms mark we flag
Aim Training →

Spend your practice time on Dust 2

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 16 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	14–16	-0.04	17%	22 Aug →
cache	2–8	-0.13	50%	24 Jul →
cache	8–13	-0.01	24%	27 Jun →
train	13–11	-0.00	12%	21 Jun →
inferno	5–13	0.04	22%	17 Jun →
cache	4–13	-0.06	23%	25 May →
dust2	9–13	-0.04	27%	18 Mar →
dust2	13–8	-0.10	26%	16 Jan →
vertigo	6–13	-0.10	15%	22 Dec →
dust2	1–13	-0.03	18%	22 Dec →
vertigo	8–13	-0.15	5%	12 Jul →
overpass	12–12	-0.06	18%	12 Jul →
mirage	13–9	0.04	5%	23 May →
jura	11–13	-0.09	10%	17 May →
vertigo	12–12	-0.07	22%	17 May →
overpass	11–4	-0.06	10%	17 May →
nuke	13–10	-0.04	13%	17 May →
train	10–13	-0.03	23%	13 May →
grail	5–13	-0.03	22%	13 May →
overpass	1–13	-0.11	20%	13 May →
mirage	4–13	-0.08	17%	8 May →
nuke	13–8	-0.07	24%	8 May →
nuke	1–13	-0.07	13%	8 May →
nuke	13–5	0.04	27%	2 May →
train	13–2	-0.01	21%	2 May →
nuke	13–8	0.01	11%	2 May →
dust2	7–13	-0.00	16%	24 Apr →
dust2	13–10	-0.03	31%	24 Apr →
dust2	8–13	-0.03	13%	20 Apr →
dust2	13–4	0.01	18%	19 Apr →
nuke	13–3	-0.08	10%	15 Apr →
nuke	7–13	-0.01	18%	24 Mar →
train	13–11	-0.03	6%	21 Feb →
overpass	8–13	-0.03	21%	20 Feb →
office	6–13	-0.10	6%	16 Feb →
ancient	13–8	0.01	16%	16 Feb →
inferno	7–13	-0.03	8%	16 Feb →
train	13–6	-0.02	11%	16 Feb →
mirage	13–5	-0.02	19%	16 Feb →
dust2	13–8	-0.03	9%	16 Feb →
mirage	11–13	-0.04	14%	5 Feb →
ancient	13–3	-0.00	13%	16 Jan →
inferno	12–12	-0.02	15%	16 Jan →
ancient	13–2	0.06	25%	15 Jan →
mirage	8–13	-0.02	14%	15 Jan →
ancient	12–12	0.00	14%	15 Jan →
train	4–13	-0.01	24%	13 Jan →
ancient	13–3	-0.09	29%	11 Jan →
ancient	4–2	0.01	17%	11 Jan →
vertigo	13–7	-0.03	25%	11 Jan →
train	13–2	0.03	16%	11 Jan →
anubis	13–9	-0.04	11%	10 Jan →
vertigo	12–12	-0.06	22%	10 Jan →
train	13–11	-0.01	21%	10 Jan →
ancient	8–13	-0.01	13%	7 Jan →
office	5–13	0.01	14%	5 Jan →
ancient	3–13	-0.03	19%	5 Jan →
anubis	10–13	-0.07	10%	5 Jan →
dust2	5–13	-0.01	17%	5 Jan →
dust2	6–13	-0.08	9%	19 Dec →
inferno	10–13	-0.04	23%	19 Dec →
inferno	13–11	-0.00	12%	25 Nov →
vertigo	13–9	-0.02	16%	25 Nov →
train	13–9	-0.06	24%	19 Nov →
ancient	6–13	-0.03	11%	4 Nov →
inferno	13–8	0.02	12%	4 Nov →
mirage	13–7	-0.06	11%	4 Nov →
vertigo	13–6	0.06	23%	3 Nov →
ancient	13–10	-0.00	16%	3 Nov →
ancient	9–13	-0.05	12%	28 Oct →
dust2	9–13	-0.07	12%	27 Oct →
anubis	13–9	0.04	3%	22 Oct →
mirage	13–3	0.02	11%	22 Oct →
inferno	13–3	0.02	0%	22 Oct →
ancient	13–4	-0.00	14%	9 Oct →
overpass	13–7	-0.06	20%	9 Oct →
inferno	9–13	0.03	23%	8 Oct →
vertigo	5–13	-0.08	19%	8 Oct →
vertigo	13–5	-0.04	12%	2 Oct →
mirage	11–12	0.01	15%	25 Sept →
anubis	10–13	-0.02	20%	25 Sept →
vertigo	13–8	-0.01	14%	25 Sept →
mirage	5–13	-0.07	19%	25 Sept →
nuke	13–9	0.03	12%	25 Sept →
dust2	3–13	-0.10	10%	25 Sept →
dust2	12–12	0.02	17%	24 Sept →
dust2	7–13	-0.03	21%	18 Sept →
vertigo	9–13	-0.03	31%	17 Sept →
mirage	3–13	-0.05	11%	17 Sept →
mills	12–12	-0.00	8%	5 Sept →
mirage	13–5	-0.00	19%	30 Aug →
vertigo	13–4	-0.02	22%	30 Aug →
dust2	6–13	-0.05	21%	24 Aug →
mills	7–13	-0.03	9%	2 Aug →
dust2	13–8	-0.01	11%	1 Aug →
overpass	13–8	-0.00	16%	1 Aug →
anubis	3–13	-0.10	3%	29 Jul →
thera	13–8	0.05	15%	29 Jul →
mills	12–12	-0.05	24%	28 Jul →
inferno	5–13	-0.09	10%	28 Jul →