fuqmyshitup — CS2 Stats

76561198010585369[U:1:50319641]

2,234Tracked matches54%Win rate2020Tracked since

4,955Hours in CS50Hrs last 2 wks

CSDB Rating5.8 SolidPassive Rifler

Premier CS Rating28,554Top 5% of 819 CSDB-tracked playersRed band · top ~1.3% of ranked players (population est.)

CSDB Leaderboard#267 of 16798 tracked

FaceitLevel 7 · 1,797 ELOTop 42.3% of ranked FACEIT players

WingmanGold Nova II

Ladder ranks via Leetify

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Performance scores

Aim76

Positioning41

Utility39

0–100 skill scores via Leetify.

Recent form

STEADY61–34–5Last 10061%Win rateLWLLLLWWWL

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

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim7.6

Aggression4.3

Utility3.9

Positioning4.1

Opening Duels0.8

Clutch3.0

Limited utility dependence

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 84% playstyle similarity

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

Where you differ: lower positioning profile; lower utility contribution.

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

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim7.6

Positioning4.1

Utility3.9

Mechanics7.6

Opening Duels0.8

Win Impact6.2

Composite 5.8/10 (Solid), 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 rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time520ms−30ms

first ⅓ avg 550ms → last ⅓ avg 520ms

Headshot accuracy13.2%+0.5%

first ⅓ avg 12.7% → last ⅓ avg 13.2%

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

0.12Best rating — cache 13–2

13–0Biggest win — train

9Longest win streak

6–8In matches decided by ≤2 rounds

6Overtime games

Map breakdown

trainBest map · 83% over 6ancientWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	S	25	18–7	72%	-0.00
inferno	A	17	10–7	59%	0.00
mirage	B	17	8–9	47%	0.00
cache	S	12	8–4	67%	0.00
anubis	S	9	7–2	78%	0.03
ancient	D	6	1–5	17%	0.00
train	S	6	5–1	83%	0.02
nuke	—	4	2–2	50%	0.02
vertigo	—	3	2–1	67%	0.05
office	—	1	0–1	0%	0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

213,605Lifetime kills

1.85K/D · Top 5% of tracked players

10,492Matches

64.7%Match win rate · Top 5% of tracked players

30.4%Headshot %

15.8%Shot accuracy · Top 25% of tracked players

17,283MVPs

3,295Hours (in match)

10,083Bombs planted

1,537Bombs defused

Most-used weapons

AK-4772,824

M4A4 / M4A1-S56,891

AWP29,289

Five-SeveN5,891

P2505,888

P2000 / USP-S5,189

Desert Eagle3,332

Glock-183,248

P903,082

Tec-92,725

Lifetime map wins

26,348dust2

10,221inferno

2,956train

2,535nuke

2,084vertigo

1,436cbble

809office

146lake

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

Faceit stats

Combat

231Matches

55%Win rate

1.12Avg K/D

78.3ADR

34%Headshot %

Clutches & streaks

35%1v1 clutch win

24%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	27	44%	1.11	14.1
Dust2	27	59%	1.09	16.1
Inferno	16	19%	0.90	12.6
Anubis	10	40%	0.93	13.8
Vertigo	9	67%	1.12	14.9
Ancient	5	40%	1.10	12.0
Nuke	5	80%	1.14	17.6
Cache	1	100%	1.13	17.0

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.

12.7%Headshot accuracy

34.8%Accuracy (enemy spotted)

37.8%Spray accuracy

84.4%Counter-strafing

8.6°Preaim

516msReaction time

32.5%T opening success

33.7%CT opening success

0.45Enemies flashed / flash

1.3%Flash assists

8.31HE damage / grenade

4.94Flashes / 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 12.658% — 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 0.4543 — 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 32.5034% — below the 40% mark we flag

Spend your practice time on Ancient

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	4–13	-0.06	10%	27 Aug →
nuke	13–6	0.03	10%	25 Aug →
mirage	7–13	-0.01	29%	25 Aug →
dust2	20–22	-0.04	12%	25 Aug →
nuke	8–13	0.03	13%	23 Aug →
inferno	7–13	-0.04	23%	23 Aug →
mirage	13–6	0.05	13%	21 Aug →
dust2	13–4	0.05	11%	21 Aug →
anubis	16–14	-0.03	9%	19 Aug →
ancient	11–13	-0.02	15%	18 Aug →
dust2	13–16	-0.04	9%	18 Aug →
mirage	13–6	0.00	23%	16 Aug →
vertigo	12–12	0.07	10%	16 Aug →
inferno	7–2	0.02	42%	16 Aug →
vertigo	13–4	0.05	9%	15 Aug →
inferno	2–13	-0.09	11%	15 Aug →
dust2	2–13	-0.01	13%	15 Aug →
dust2	10–13	-0.05	5%	14 Aug →
train	13–9	-0.06	11%	14 Aug →
dust2	13–10	-0.04	11%	14 Aug →
ancient	10–13	0.07	11%	14 Aug →
train	13–4	0.05	11%	12 Aug →
dust2	13–10	-0.05	8%	12 Aug →
mirage	8–13	-0.05	11%	12 Aug →
cache	11–13	-0.03	8%	12 Aug →
inferno	13–7	0.11	16%	12 Aug →
train	13–0	0.10	9%	12 Aug →
dust2	13–10	0.01	12%	12 Aug →
inferno	12–12	0.03	12%	12 Aug →
inferno	13–3	0.01	11%	11 Aug →
train	13–2	0.04	5%	11 Aug →
inferno	12–12	-0.01	11%	10 Aug →
mirage	13–9	-0.03	17%	10 Aug →
dust2	13–2	-0.00	14%	9 Aug →
inferno	2–0	0.00	0%	9 Aug →
dust2	13–3	-0.07	5%	9 Aug →
inferno	2–0	-0.07	0%	9 Aug →
cache	13–0	0.00	0%	9 Aug →
anubis	13–0	0.00	0%	9 Aug →
dust2	13–2	-0.02	10%	9 Aug →
dust2	13–3	0.07	22%	8 Aug →
cache	11–13	0.01	14%	8 Aug →
dust2	13–6	-0.01	18%	8 Aug →
inferno	13–3	0.06	9%	7 Aug →
inferno	13–2	-0.02	10%	6 Aug →
anubis	13–0	0.09	30%	6 Aug →
mirage	3–13	-0.04	12%	5 Aug →
mirage	6–13	-0.05	11%	5 Aug →
dust2	13–10	0.00	11%	5 Aug →
cache	10–13	0.01	9%	5 Aug →
nuke	9–13	0.01	21%	4 Aug →
cache	13–5	-0.01	3%	4 Aug →
mirage	13–11	0.03	4%	3 Aug →
dust2	13–5	0.06	14%	3 Aug →
cache	13–6	-0.04	9%	3 Aug →
mirage	10–2	0.04	18%	3 Aug →
mirage	9–13	0.01	5%	1 Aug →
dust2	13–8	0.00	2%	1 Aug →
cache	13–7	0.05	8%	1 Aug →
dust2	7–1	-0.00	0%	1 Aug →
ancient	13–4	0.06	13%	31 Jul →
mirage	13–2	0.06	13%	31 Jul →
cache	13–5	0.04	7%	31 Jul →
dust2	2–13	-0.06	10%	31 Jul →
ancient	0–2	-0.03	100%	30 Jul →
train	13–7	0.03	12%	28 Jul →
office	5–13	0.00	10%	27 Jul →
ancient	5–13	-0.05	15%	26 Jul →
anubis	13–4	0.07	8%	26 Jul →
dust2	13–6	0.05	16%	26 Jul →
inferno	13–9	0.04	9%	26 Jul →
anubis	14–16	-0.02	10%	24 Jul →
cache	16–12	-0.07	11%	24 Jul →
anubis	13–11	0.04	12%	21 Jul →
inferno	13–4	0.05	11%	20 Jul →
mirage	13–5	0.02	6%	20 Jul →
cache	13–2	0.12	26%	20 Jul →
dust2	1–12	-0.01	50%	20 Jul →
anubis	13–2	0.08	8%	20 Jul →
mirage	0–13	-0.02	0%	20 Jul →
nuke	13–8	0.03	15%	20 Jul →
mirage	13–1	0.04	7%	20 Jul →
train	4–13	-0.02	9%	20 Jul →
mirage	8–13	-0.02	7%	18 Jul →
cache	11–13	-0.04	10%	18 Jul →
dust2	13–11	0.02	9%	18 Jul →
inferno	13–6	0.01	24%	18 Jul →
mirage	4–13	0.00	18%	18 Jul →
dust2	13–9	-0.03	12%	17 Jul →
dust2	15–15	0.02	4%	17 Jul →
ancient	10–13	-0.01	9%	16 Jul →
inferno	11–13	0.04	11%	16 Jul →
anubis	3–13	-0.04	13%	15 Jul →
cache	13–3	-0.00	7%	15 Jul →
dust2	13–1	0.10	18%	15 Jul →
anubis	13–10	0.05	22%	14 Jul →
vertigo	13–6	0.02	8%	14 Jul →
mirage	10–13	-0.05	9%	14 Jul →
inferno	12–12	-0.03	11%	14 Jul →
dust2	13–4	0.02	14%	13 Jul →