🍀Cootrtootr — CS2 Stats

76561198830578060[U:1:870312332]Steam profile ↗✓ No bans

3,898Tracked matches29%Win rate2020Tracked since

4,664Hours in CS36Hrs last 2 wks

CSDB Rating5.7 SolidAll-Rounder

FaceitLevel 2Top 97.9% of ranked FACEIT players

WingmanGold Nova III

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 8 Sep 2026 (39 days ago). Ranks are recorded once per day this page is viewed.

+55Tracked matches · now 3,898

−28.5ppWin rate · 57.7% → 29.2%

Rating over time

35Days played since 2026-08-03

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 2 among CSDB-tracked players (n=6,013), 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 2 median	Level 3 median	vs Level 3
Headshot rate	46.8%	41.3%	41.8%	above
Shot accuracy	11.7%	12.7%	12.2%	0.5% short
Kill/death ratio	0.98	0.95	0.98	meets
Match win rate	42.8%	42.6%	43.3%	meets

This profile matches the typical Level 3 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim67

Positioning60

Utility57

0–100 skill scores via Leetify.

Recent form

STEADY45–41–14Last 10045%Win rateLWLLWWTWTL

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · −0.5pp headshot accuracy · −17ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

2–3 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 24%
Avg reaction 542ms

Last 10

4–4–2 · 40% win rate
Avg rating -0.02
Avg headshot accuracy 21%
Avg reaction 555ms

Last 20

7–8–5 · 35% win rate
Avg rating -0.01
Avg headshot accuracy 22%
Avg reaction 563ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim6.7

Utility5.7

Positioning6.0

Opening Duels4.7

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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like jL 87% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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

Strengths

T openings. 62% T opening-duel success — entries that actually open the round.

Areas to improve

Reaction time. 564ms 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

Aim6.7

Positioning6.0

Utility5.7

Mechanics6.5

Opening Duels6.5

Win Impact0.0

Composite 5.7/10 (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 rating-0.01−0.03

first ⅓ avg 0.02 → last ⅓ avg -0.01

Reaction time583ms−57ms

first ⅓ avg 639ms → last ⅓ avg 583ms

Headshot accuracy21.2%−5.1%

first ⅓ avg 26.3% → last ⅓ avg 21.2%

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.

Personal bests

0.16Best match rating · 9–3 · vertigo, 6 Aug →

71%Best headshot accuracy · 8–8 · poseidon, 12 Aug →

406msFastest reaction time · 1–13 · inferno, 9 Oct →

13–0Biggest win · nuke, 28 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak

6–8In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 60% over 15trainWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	16	7–9	44%	-0.00
dust2	A	15	9–6	60%	-0.01
inferno	C	14	6–8	43%	-0.00
nuke	B	13	6–7	46%	-0.01
cache	D	11	3–8	27%	-0.02
train	D	8	2–6	25%	0.01
vertigo	A	7	4–3	57%	0.04
anubis	B	6	3–3	50%	0.00
ancient	—	4	2–2	50%	-0.00
office	—	3	1–2	33%	0.01
poseidon	—	1	0–1	0%	0.05
overpass	—	1	1–0	100%	0.10
debris	—	1	1–0	100%	0.15

Across the last 100 tracked matches.

Lifetime stats

112,252Lifetime kills

0.98K/D · Top 50% of Level 2 players

7,235Matches

42.8%Match win rate · Top 50% of Level 2 players

46.8%Headshot % · Top 25% of Level 2 players

11.7%Shot accuracy

17,691MVPs

2,358Hours (in match)

8,586Bombs planted

1,351Bombs defused

Most-used weapons

AK-4730,328

M4A4 / M4A1-S17,335

Desert Eagle13,898

AWP11,165

P2000 / USP-S7,753

Glock-186,043

Galil AR5,572

SSG 084,442

MP92,070

FAMAS2,003

Lifetime map wins

9,577inferno

8,949dust2

6,890nuke

4,802vertigo

3,397train

1,110office

333cbble

280italy

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

Faceit stats

Combat

301Matches

49%Win rate

0.88Avg K/D

—ADR

32%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

9Longest win streak

Recent Faceit resultsLWWLL

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.

21.1%Headshot accuracy

33.5%Accuracy (enemy spotted)

34.0%Spray accuracy

79.3%Counter-strafing

11.2°Preaim

564msReaction time

61.8%T opening success

50.2%CT opening success

0.69Enemies flashed / flash

11.1%Flash assists

13.50HE damage / grenade

4.80Flashes / match

Recommended for you

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
vertigo	2–13	-0.06	29%	17 Oct →
train	13–9	0.00	21%	17 Oct →
mirage	3–13	0.00	21%	17 Oct →
cache	6–13	-0.03	32%	17 Oct →
inferno	13–10	-0.05	16%	17 Oct →
mirage	13–10	-0.01	9%	16 Oct →
ancient	12–12	-0.02	14%	16 Oct →
dust2	13–8	-0.00	20%	16 Oct →
dust2	12–12	0.01	28%	16 Oct →
inferno	1–13	-0.02	24%	14 Oct →
vertigo	12–12	0.04	17%	14 Oct →
vertigo	11–13	-0.00	28%	12 Oct →
cache	10–13	-0.05	20%	12 Oct →
inferno	13–7	0.07	23%	12 Oct →
nuke	12–12	0.04	22%	12 Oct →
train	12–12	-0.04	16%	11 Oct →
mirage	2–13	0.01	27%	11 Oct →
nuke	1–13	-0.10	33%	11 Oct →
mirage	13–9	-0.06	16%	11 Oct →
dust2	13–9	-0.00	16%	11 Oct →
mirage	8–13	-0.02	34%	10 Oct →
dust2	5–13	-0.04	22%	9 Oct →
inferno	1–13	0.02	16%	9 Oct →
office	10–13	0.03	14%	9 Oct →
nuke	4–13	0.01	23%	9 Oct →
cache	3–13	-0.01	16%	8 Oct →
train	9–13	0.06	17%	7 Oct →
train	12–12	0.02	24%	7 Oct →
train	5–13	-0.05	33%	7 Oct →
mirage	11–13	-0.06	16%	6 Oct →
mirage	12–12	-0.05	12%	5 Oct →
dust2	13–11	-0.02	18%	5 Oct →
anubis	3–13	-0.06	24%	4 Oct →
mirage	13–4	0.06	13%	4 Oct →
dust2	13–11	0.03	22%	4 Oct →
anubis	13–4	-0.04	10%	3 Oct →
train	11–13	0.03	16%	3 Oct →
mirage	13–7	0.08	16%	3 Oct →
inferno	13–2	-0.04	17%	3 Oct →
dust2	13–6	-0.03	20%	3 Oct →
dust2	13–9	-0.02	15%	2 Oct →
nuke	13–4	-0.02	22%	2 Oct →
inferno	4–13	0.02	35%	2 Oct →
mirage	11–13	0.04	24%	2 Oct →
mirage	7–13	0.02	25%	1 Oct →
inferno	10–13	-0.02	19%	1 Oct →
anubis	13–3	0.16	13%	1 Oct →
dust2	13–4	-0.03	18%	1 Oct →
inferno	13–8	-0.04	23%	28 Sept →
nuke	13–0	0.05	18%	28 Sept →
dust2	2–13	-0.05	29%	28 Sept →
ancient	13–3	-0.06	4%	28 Sept →
dust2	13–6	0.04	13%	25 Sept →
dust2	11–13	-0.02	20%	25 Sept →
ancient	13–3	-0.01	11%	23 Sept →
office	9–13	-0.05	31%	3 Sept →
mirage	13–5	-0.01	30%	2 Sept →
mirage	12–12	0.00	24%	31 Aug →
cache	13–11	0.02	24%	31 Aug →
dust2	9–13	-0.02	23%	31 Aug →
cache	13–5	-0.05	26%	30 Aug →
vertigo	13–4	0.07	27%	24 Aug →
mirage	13–6	-0.00	20%	24 Aug →
cache	3–13	-0.02	23%	24 Aug →
nuke	6–13	-0.07	14%	23 Aug →
cache	10–13	-0.04	12%	23 Aug →
vertigo	13–7	-0.01	36%	23 Aug →
anubis	13–2	-0.01	23%	23 Aug →
nuke	10–13	-0.07	18%	23 Aug →
ancient	8–13	0.07	17%	23 Aug →
cache	13–3	0.04	23%	22 Aug →
inferno	13–9	0.06	14%	22 Aug →
dust2	4–13	-0.04	18%	22 Aug →
inferno	8–8	0.04	63%	22 Aug →
nuke	7–9	-0.04	47%	20 Aug →
inferno	2–9	-0.18	63%	20 Aug →
train	12–12	-0.01	20%	15 Aug →
train	13–7	0.08	15%	15 Aug →
nuke	13–10	0.03	24%	14 Aug →
cache	7–13	0.03	25%	14 Aug →
anubis	12–12	-0.01	14%	14 Aug →
anubis	12–12	-0.02	14%	12 Aug →
cache	8–13	-0.01	20%	12 Aug →
poseidon	8–8	0.05	71%	12 Aug →
nuke	13–10	-0.08	6%	9 Aug →
cache	0–13	-0.07	27%	9 Aug →
inferno	13–2	0.13	28%	9 Aug →
dust2	13–11	-0.03	23%	9 Aug →
nuke	9–2	0.02	33%	9 Aug →
inferno	8–8	0.04	55%	8 Aug →
vertigo	9–3	0.16	42%	6 Aug →
overpass	13–3	0.10	16%	5 Aug →
mirage	13–11	0.02	27%	5 Aug →
debris	9–7	0.15	35%	5 Aug →
inferno	2–4	-0.05	14%	4 Aug →
mirage	10–13	-0.00	14%	4 Aug →
nuke	13–4	-0.00	11%	4 Aug →
office	13–5	0.06	15%	4 Aug →
vertigo	13–7	0.07	16%	3 Aug →
nuke	11–13	0.05	18%	3 Aug →