joukinha — CS2 Stats

PT76561198245797094[U:1:285531366]Steam profile ↗✓ No bans

3,676Tracked matches69%Win rate2020Tracked since

CSDB Rating7.1 StrongAggressive Rifler

FaceitLevel 10 · 2,848 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim82

Positioning61

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY57–42–1Last 10057%Win rateLWWLWWLWLW

Last 10 vs previous 10: -20pp win rate · -0.02 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.2

Aggression7.2

Utility5.9

Positioning6.1

Opening Duels3.5

Clutch4.0

Strong CT-side opener

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 b1t 95% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

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 55% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 586ms 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

Aim8.2

Positioning6.1

Utility5.9

Mechanics6.8

Opening Duels3.5

Win Impact10.0

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.02

Reaction time589ms−34ms

first ⅓ avg 623ms → last ⅓ avg 589ms

Headshot accuracy23.1%−1.5%

first ⅓ avg 24.5% → last ⅓ avg 23.1%

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

0.12Best rating — cache 13–11

13–0Biggest win — vertigo

6Longest win streak

8–12In matches decided by ≤2 rounds

12Overtime games

Map breakdown

dust2Best map · 75% over 16nukeWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
ancient	A	23	13–10	57%	0.02
mirage	S	21	14–7	67%	0.01
dust2	S	16	12–4	75%	0.00
inferno	D	12	4–8	33%	-0.00
anubis	S	9	6–3	67%	0.04
nuke	D	7	2–5	29%	0.03
vertigo	—	4	3–1	75%	0.04
train	—	3	1–2	33%	0.04
cache	—	3	1–2	33%	0.00
overpass	—	2	1–1	50%	0.05

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,578Matches

51%Win rate

1.11Avg K/D

79.6ADR

53%Headshot %

Clutches & streaks

40%1v1 clutch win

22%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	1023	52%	1.15	16.6
Ancient	800	55%	1.15	16.8
Dust2	523	47%	1.05	15.5
Inferno	351	49%	1.11	16.2
Nuke	307	49%	1.06	16.1
Anubis	277	41%	1.03	15.3
Train	98	50%	1.10	16.6
Vertigo	75	53%	1.08	16.7

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.

23.0%Headshot accuracy

36.9%Accuracy (enemy spotted)

41.5%Spray accuracy

80.7%Counter-strafing

9.6°Preaim

586msReaction time

32.9%T opening success

55.4%CT opening success

0.62Enemies flashed / flash

10.5%Flash assists

6.17HE damage / grenade

9.22Flashes / 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
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 32.9243% — below the 40% mark we flag

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.

29% win rate across 7 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
inferno	7–13	0.05	29%	29 Aug →
dust2	13–6	0.03	26%	28 Aug →
dust2	13–8	-0.03	19%	27 Aug →
inferno	4–13	-0.07	15%	25 Aug →
mirage	13–7	0.00	34%	18 Aug →
dust2	13–8	0.02	17%	15 Aug →
ancient	6–13	-0.02	12%	13 Aug →
mirage	13–4	-0.04	13%	6 Aug →
inferno	4–13	0.00	32%	4 Aug →
vertigo	13–0	0.03	7%	30 Jul →
mirage	13–5	-0.02	26%	29 Jul →
dust2	16–12	0.04	19%	29 Jul →
anubis	13–8	0.11	37%	22 Jul →
ancient	13–4	0.05	30%	21 Jul →
anubis	9–13	-0.01	29%	20 Jul →
mirage	17–19	-0.01	26%	18 Jul →
inferno	13–4	0.05	36%	10 Jul →
dust2	13–6	-0.03	35%	3 Jul →
ancient	13–6	0.05	24%	29 Jun →
inferno	13–6	-0.01	13%	29 Jun →
ancient	13–5	0.05	22%	29 Jun →
nuke	8–13	0.05	19%	26 Jun →
train	12–12	0.03	9%	19 Jun →
dust2	7–13	-0.05	11%	14 Jun →
ancient	13–5	0.09	25%	13 Jun →
vertigo	13–5	0.04	32%	3 Jun →
anubis	13–8	0.09	34%	29 May →
mirage	10–13	-0.01	30%	27 May →
ancient	13–7	0.03	9%	23 May →
mirage	13–7	0.07	17%	22 May →
inferno	11–13	0.01	23%	14 May →
ancient	16–13	0.09	27%	13 May →
overpass	11–13	0.05	25%	13 May →
cache	13–11	0.12	18%	11 May →
nuke	5–13	0.00	48%	10 May →
dust2	11–13	-0.08	19%	10 May →
dust2	13–11	0.03	29%	8 May →
nuke	13–11	0.04	28%	4 May →
nuke	13–9	0.05	32%	3 May →
dust2	16–13	0.03	35%	30 Apr →
cache	7–13	-0.05	22%	30 Apr →
train	11–13	0.06	20%	27 Apr →
cache	4–13	-0.06	23%	25 Apr →
ancient	14–16	-0.03	20%	17 Apr →
dust2	10–13	0.03	55%	15 Apr →
vertigo	13–5	0.05	25%	8 Apr →
anubis	13–10	0.01	25%	8 Apr →
anubis	13–10	0.06	18%	1 Apr →
ancient	6–13	0.03	27%	31 Mar →
mirage	13–10	0.05	39%	29 Mar →
mirage	13–2	0.04	20%	27 Mar →
anubis	11–13	0.02	22%	26 Mar →
ancient	11–13	-0.05	6%	25 Mar →
ancient	13–11	-0.01	29%	25 Mar →
ancient	7–13	-0.01	12%	18 Mar →
ancient	13–6	0.11	26%	18 Mar →
inferno	2–13	-0.07	37%	3 Mar →
mirage	19–16	0.02	21%	2 Mar →
dust2	7–13	-0.04	11%	2 Mar →
mirage	5–13	-0.05	21%	26 Feb →
overpass	13–9	0.04	21%	22 Feb →
dust2	13–10	-0.01	29%	22 Feb →
nuke	8–13	0.03	19%	22 Feb →
ancient	2–9	0.03	35%	18 Feb →
mirage	13–11	0.04	35%	17 Feb →
nuke	10–13	-0.00	31%	8 Feb →
dust2	13–10	0.09	34%	2 Feb →
mirage	7–13	0.02	17%	28 Jan →
anubis	13–2	0.12	35%	26 Jan →
nuke	13–16	0.00	11%	25 Jan →
ancient	13–5	0.03	26%	25 Jan →
anubis	16–12	-0.04	13%	23 Jan →
mirage	10–13	0.06	23%	21 Jan →
anubis	8–13	0.01	18%	19 Jan →
mirage	5–13	-0.04	39%	6 Jan →
mirage	13–6	-0.02	29%	5 Jan →
train	13–4	0.02	24%	5 Jan →
mirage	16–13	0.00	28%	3 Jan →
inferno	9–13	-0.00	28%	30 Dec →
dust2	19–17	-0.00	34%	23 Dec →
inferno	8–13	-0.04	23%	21 Dec →
mirage	13–10	0.00	23%	20 Dec →
ancient	13–5	0.02	16%	15 Dec →
mirage	13–8	0.04	29%	11 Dec →
ancient	13–4	-0.03	18%	27 Nov →
inferno	16–14	0.01	16%	19 Nov →
ancient	13–11	0.02	28%	15 Nov →
mirage	11–13	0.02	24%	12 Nov →
ancient	1–13	-0.04	40%	11 Nov →
inferno	13–10	-0.07	33%	11 Nov →
dust2	13–7	0.01	33%	11 Nov →
mirage	13–7	0.04	21%	5 Nov →
dust2	13–10	-0.03	27%	30 Oct →
ancient	13–16	0.04	12%	20 Oct →
inferno	7–9	0.08	21%	15 Oct →
vertigo	4–9	0.05	17%	15 Oct →
mirage	13–6	0.06	39%	15 Oct →
ancient	11–13	0.01	23%	14 Oct →
ancient	13–8	0.01	19%	13 Oct →
ancient	11–13	0.01	20%	10 Oct →