Scared Koala — CS2 Stats

76561198011677436[U:1:51411708]✓ No bans

809Tracked matches46%Win rate2025Tracked since

CSDB Rating4.9 Developing

Premier CS Rating17,372Purple band · top ~19% of ranked players (population est.)

FaceitLevel 4 · 993 ELOTop 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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

Aim56

Positioning39

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateLTWWLLWWWW

Last 10 vs previous 10: +30pp win rate · +0.00 avg rating

Player DNA

Aim5.6

Aggression2.5

Utility5.9

Positioning3.9

Opening Duels0.0

Clutch4.8

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 79% playstyle similarity

Most alike: utility contribution, opening-duel success.

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. 684ms 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

Aim5.6

Positioning3.9

Utility5.9

Mechanics7.6

Opening Duels0.0

Win Impact3.8

Composite 4.9/10 (Developing), 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-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time678ms−2ms

first ⅓ avg 680ms → last ⅓ avg 678ms

Headshot accuracy10.9%−4.0%

first ⅓ avg 14.9% → last ⅓ avg 10.9%

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 — anubis 13–3

13–2Biggest win — mirage

7Longest win streak

5–5In matches decided by ≤2 rounds

10Overtime games

Map breakdown

cacheBest map · 67% over 6nukeWeakest map · 23% over 13

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	18	11–7	61%	-0.00
dust2	B	18	9–9	50%	-0.01
anubis	A	17	10–7	59%	0.01
ancient	A	14	9–5	64%	0.02
nuke	D	13	3–10	23%	-0.02
mirage	B	10	5–5	50%	0.01
cache	S	6	4–2	67%	-0.01
overpass	—	3	1–2	33%	-0.02
train	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (23% over 13). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

94Matches

54%Win rate

1.15Avg K/D

86.8ADR

37%Headshot %

Clutches & streaks

44%1v1 clutch win

21%1v2 clutch win

8Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	24	54%	1.27	18.0
Dust2	23	52%	1.00	14.7
Inferno	9	78%	1.67	17.7
Ancient	8	12%	0.85	16.9
Nuke	7	43%	1.18	18.6
Overpass	7	57%	1.16	16.3
Train	5	60%	1.27	18.8
Anubis	1	100%	1.09	24.0

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.

11.0%Headshot accuracy

38.9%Accuracy (enemy spotted)

39.6%Spray accuracy

84.3%Counter-strafing

12.2°Preaim

684msReaction time

27.3%T opening success

28.8%CT opening success

0.73Enemies flashed / flash

8.2%Flash assists

8.82HE damage / grenade

6.63Flashes / 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 12.2104° — above the 12° mark we flag
Aim Training →
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 11.0159% — below the 15% mark we flag
Aim Training →

Spend your practice time on Nuke

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

23% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	8–13	-0.05	12%	14 Aug →
nuke	15–15	-0.01	12%	14 Aug →
ancient	13–8	0.06	17%	14 Aug →
inferno	13–8	0.01	5%	12 Aug →
anubis	7–13	-0.02	8%	7 Aug →
mirage	6–13	-0.07	7%	7 Aug →
inferno	13–8	0.05	15%	5 Aug →
dust2	13–5	-0.01	9%	4 Aug →
mirage	13–10	-0.03	9%	4 Aug →
ancient	13–6	0.01	4%	3 Aug →
nuke	10–13	-0.03	6%	3 Aug →
inferno	10–13	-0.03	8%	3 Aug →
dust2	9–13	-0.05	11%	3 Aug →
inferno	1–13	-0.09	15%	2 Aug →
cache	13–11	-0.03	21%	2 Aug →
cache	15–15	-0.00	14%	2 Aug →
cache	6–1	0.07	19%	2 Aug →
anubis	13–10	-0.02	10%	2 Aug →
mirage	9–13	0.08	11%	2 Aug →
dust2	11–13	0.01	13%	2 Aug →
anubis	10–13	-0.02	7%	31 Jul →
inferno	13–6	0.00	2%	31 Jul →
dust2	14–16	-0.05	16%	27 Jul →
ancient	7–13	0.04	10%	23 Jul →
anubis	10–13	-0.05	23%	18 Jul →
mirage	7–13	-0.02	14%	18 Jul →
mirage	13–2	0.08	10%	18 Jul →
dust2	13–8	-0.04	3%	18 Jul →
inferno	13–10	-0.07	7%	18 Jul →
dust2	9–13	-0.04	12%	18 Jul →
cache	7–13	-0.05	8%	18 Jul →
inferno	13–5	0.02	13%	17 Jul →
dust2	16–13	0.03	8%	17 Jul →
dust2	5–13	-0.06	28%	17 Jul →
inferno	13–5	0.11	11%	17 Jul →
ancient	13–9	0.00	9%	17 Jul →
mirage	13–10	0.01	11%	17 Jul →
ancient	13–10	0.01	8%	17 Jul →
inferno	2–13	-0.02	24%	17 Jul →
dust2	13–8	0.04	12%	17 Jul →
nuke	13–6	0.07	16%	17 Jul →
nuke	8–13	-0.03	13%	17 Jul →
ancient	5–13	-0.02	10%	15 Jul →
nuke	10–13	-0.01	9%	14 Jul →
mirage	7–13	-0.04	5%	14 Jul →
anubis	13–6	-0.00	6%	13 Jul →
dust2	9–13	-0.05	13%	12 Jul →
cache	13–9	-0.00	13%	12 Jul →
ancient	7–13	-0.01	16%	11 Jul →
dust2	13–11	-0.03	12%	11 Jul →
nuke	13–9	0.06	11%	11 Jul →
cache	13–11	-0.04	5%	11 Jul →
anubis	13–10	0.03	17%	10 Jul →
mirage	13–10	0.04	10%	5 Jul →
dust2	7–13	-0.01	13%	5 Jul →
inferno	5–13	0.03	17%	5 Jul →
dust2	7–13	-0.04	17%	3 Jul →
overpass	7–13	-0.09	17%	3 Jul →
nuke	3–13	-0.05	21%	6 Jun →
anubis	13–8	-0.05	15%	6 Jun →
dust2	13–8	0.04	20%	6 Jun →
anubis	16–13	0.03	16%	3 Mar →
ancient	13–3	0.06	13%	22 Feb →
nuke	13–9	0.01	11%	22 Feb →
dust2	13–7	0.07	26%	22 Feb →
overpass	13–8	0.07	29%	21 Feb →
ancient	0–13	-0.03	24%	9 Feb →
nuke	11–13	-0.06	21%	8 Feb →
inferno	10–13	-0.02	18%	6 Feb →
dust2	13–11	0.02	12%	5 Feb →
anubis	13–3	0.08	11%	5 Feb →
inferno	13–10	-0.03	8%	3 Feb →
inferno	10–13	0.03	10%	3 Feb →
anubis	2–13	-0.08	8%	3 Feb →
dust2	14–16	-0.02	23%	2 Feb →
inferno	13–7	0.03	18%	1 Feb →
mirage	16–13	0.02	14%	1 Feb →
ancient	13–9	0.04	11%	1 Feb →
anubis	10–13	0.03	17%	1 Feb →
ancient	13–10	0.03	15%	1 Feb →
inferno	13–3	0.00	24%	1 Feb →
anubis	13–11	0.00	13%	1 Feb →
nuke	6–13	-0.08	29%	1 Feb →
nuke	4–13	-0.09	11%	31 Jan →
inferno	13–7	0.04	14%	30 Jan →
overpass	11–13	-0.03	15%	30 Jan →
ancient	13–10	0.08	22%	30 Jan →
nuke	7–13	-0.05	11%	27 Jan →
inferno	13–10	-0.03	9%	27 Jan →
ancient	13–5	0.03	12%	27 Jan →
anubis	13–10	0.06	13%	25 Jan →
anubis	13–3	0.16	22%	24 Jan →
anubis	13–2	0.11	17%	19 Jan →
train	15–15	0.03	11%	19 Jan →
anubis	3–13	0.01	25%	18 Jan →
anubis	3–13	-0.06	7%	18 Jan →
mirage	15–15	0.04	9%	11 Jan →
inferno	9–13	-0.03	17%	10 Jan →
dust2	13–7	-0.02	9%	10 Jan →
ancient	13–16	-0.05	13%	4 Jan →