Juti — CS2 Stats

76561199262696768[U:1:1302431040]

711Tracked matches59%Win rate2022Tracked since

1,928Hours in CS

CSDB Rating6.5 SolidAggressive Rifler

WingmanThe Global Elite

Ladder ranks via Leetify

Performance scores

Aim86

Positioning54

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY57–39–4Last 10057%Win rateWLLLWWWLLL

Last 10 vs previous 10: -30pp win rate · +0.01 avg rating

Player DNA

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

Aim8.6

Aggression7.9

Utility4.9

Positioning5.4

Opening Duels3.4

Clutch3.8

Sharp aimerExcellent counter-strafingStrong 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 ropz 92% playstyle similarity

Most alike: utility contribution, positioning 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

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 32 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.

T-side openings. Opening success drops from 53% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 581ms 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

Aim8.6

Positioning5.4

Utility4.9

Mechanics8.5

Opening Duels3.4

Win Impact7.9

Composite 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time577ms+9ms

first ⅓ avg 568ms → last ⅓ avg 577ms

Headshot accuracy24.9%+1.1%

first ⅓ avg 23.7% → last ⅓ avg 24.9%

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

0.22Best rating — ancient 13–1

13–1Biggest win — ancient

5Longest win streak

4–7In matches decided by ≤2 rounds

4Overtime games

Map breakdown

ancientBest map · 83% over 6infernoWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	25	16–9	64%	0.04
nuke	A	20	11–9	55%	0.03
dust2	B	17	9–8	53%	0.01
inferno	C	10	4–6	40%	0.01
cache	A	9	5–4	56%	-0.01
ancient	S	6	5–1	83%	0.06
anubis	—	3	1–2	33%	-0.01
overpass	—	3	3–0	100%	0.04
office	—	3	1–2	33%	0.03
train	—	1	1–0	100%	-0.01
italy	—	1	0–1	0%	-0.03
warden	—	1	0–1	0%	0.08
alpine	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

59,349Lifetime kills

1.32K/D · Top 10% of tracked players

1,789Matches

47.5%Match win rate · Top 50% of tracked players

62.9%Headshot % · Top 5% of tracked players

6.2%Shot accuracy

7,116MVPs

1,928Hours (in match)

1,691Bombs planted

1,846Bombs defused

Most-used weapons

AK-4729,001

AWP6,035

M4A4 / M4A1-S5,970

Desert Eagle4,653

P2000 / USP-S3,198

Glock-181,650

SSG 08987

Galil AR973

MP9883

Knife799

Lifetime map wins

3,129dust2

2,971nuke

1,947inferno

1,569vertigo

428train

199lake

149office

43cbble

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

Faceit stats

Combat

323Matches

56%Win rate

1.12Avg K/D

79.7ADR

49%Headshot %

Clutches & streaks

39%1v1 clutch win

28%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	74	50%	1.15	15.7
Dust2	53	66%	1.29	15.7
Ancient	39	74%	1.17	16.1
Inferno	31	55%	1.07	15.9
Nuke	30	60%	1.20	16.9
Anubis	24	42%	1.02	15.6
Vertigo	19	58%	1.20	15.5
Overpass	5	60%	0.98	15.6

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.

25.0%Headshot accuracy

35.3%Accuracy (enemy spotted)

37.1%Spray accuracy

88.1%Counter-strafing

8.7°Preaim

581msReaction time

34.0%T opening success

53.5%CT opening success

0.52Enemies flashed / flash

3.5%Flash assists

5.45HE damage / grenade

11.02Flashes / 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 33.9593% — below the 40% mark we flag

Spend your practice time on Inferno

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

40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–3	0.11	22%	11 Aug →
dust2	8–13	-0.01	31%	10 Aug →
nuke	10–13	0.02	20%	10 Aug →
cache	11–13	-0.06	21%	10 Aug →
mirage	16–13	-0.05	27%	18 Jul →
mirage	13–2	0.12	35%	5 Jul →
dust2	13–7	-0.04	46%	28 Jun →
inferno	7–13	0.01	17%	23 Jun →
nuke	7–13	-0.00	11%	23 Jun →
anubis	6–13	0.00	39%	22 Jun →
mirage	13–10	0.03	28%	22 Jun →
dust2	12–1	0.03	25%	22 Jun →
nuke	1–13	0.04	41%	22 Jun →
mirage	11–6	-0.02	17%	22 Jun →
mirage	13–7	0.07	32%	21 Jun →
train	13–6	-0.01	26%	21 Jun →
cache	13–8	-0.04	24%	21 Jun →
anubis	14–16	-0.03	7%	14 Jun →
inferno	13–4	-0.01	13%	14 Jun →
nuke	10–13	-0.06	26%	14 Jun →
nuke	10–6	0.04	38%	12 Jun →
inferno	11–13	-0.03	24%	10 Jun →
overpass	13–4	0.05	26%	10 Jun →
mirage	13–11	0.06	33%	8 Jun →
mirage	8–13	0.01	30%	5 Jun →
dust2	13–8	0.00	23%	5 Jun →
dust2	10–13	0.05	24%	5 Jun →
mirage	13–3	0.07	23%	4 Jun →
ancient	13–9	0.06	13%	4 Jun →
dust2	15–15	-0.02	23%	3 Jun →
mirage	13–7	0.05	13%	3 Jun →
mirage	13–2	0.09	19%	3 Jun →
mirage	13–3	0.13	24%	2 Jun →
nuke	13–6	0.04	17%	2 Jun →
ancient	13–11	0.11	21%	30 May →
nuke	1–13	-0.02	63%	29 May →
anubis	13–5	0.01	24%	28 May →
mirage	5–13	0.04	25%	27 May →
nuke	13–5	-0.02	24%	27 May →
mirage	13–3	0.06	11%	26 May →
dust2	9–13	-0.05	13%	25 May →
ancient	13–1	0.22	16%	25 May →
dust2	13–8	0.04	27%	25 May →
dust2	13–9	0.04	21%	25 May →
dust2	10–13	-0.02	16%	25 May →
nuke	13–7	-0.00	38%	24 May →
mirage	11–13	0.02	11%	24 May →
mirage	13–10	0.04	16%	23 May →
nuke	7–13	0.06	40%	23 May →
nuke	11–13	0.03	23%	23 May →
overpass	13–8	-0.05	14%	23 May →
mirage	13–3	0.07	20%	22 May →
dust2	13–3	-0.00	25%	22 May →
inferno	13–10	0.01	22%	22 May →
mirage	6–10	0.01	16%	22 May →
dust2	13–10	-0.02	29%	22 May →
mirage	3–13	-0.01	20%	22 May →
ancient	6–13	-0.01	15%	22 May →
mirage	13–4	0.04	26%	21 May →
inferno	13–4	0.02	23%	21 May →
dust2	13–9	0.11	29%	20 May →
inferno	5–9	0.02	33%	20 May →
mirage	6–13	-0.03	25%	20 May →
nuke	13–3	-0.09	23%	18 May →
nuke	13–11	0.04	32%	18 May →
office	11–13	-0.04	31%	17 May →
office	5–13	-0.00	57%	17 May →
office	13–7	0.14	38%	16 May →
dust2	13–16	0.06	14%	16 May →
mirage	13–10	0.05	27%	16 May →
inferno	8–13	0.07	18%	13 May →
nuke	8–13	-0.04	23%	13 May →
nuke	13–10	0.06	25%	13 May →
dust2	13–8	-0.02	32%	13 May →
mirage	10–13	0.04	31%	13 May →
nuke	12–12	0.09	22%	12 May →
italy	12–12	-0.03	34%	12 May →
warden	5–13	0.08	19%	12 May →
alpine	13–7	0.03	19%	12 May →
nuke	12–4	0.02	31%	12 May →
cache	8–13	-0.04	17%	12 May →
cache	13–8	0.01	27%	12 May →
mirage	3–13	0.02	25%	12 May →
inferno	10–13	-0.03	22%	11 May →
cache	13–4	0.14	20%	11 May →
cache	13–6	-0.02	19%	11 May →
cache	12–1	-0.03	56%	11 May →
nuke	13–11	0.11	16%	9 May →
inferno	11–13	0.00	11%	9 May →
dust2	9–13	0.04	26%	9 May →
cache	9–13	-0.07	35%	7 May →
ancient	13–10	-0.00	20%	7 May →
ancient	13–10	-0.00	21%	7 May →
mirage	13–4	0.01	26%	7 May →
inferno	13–6	0.04	18%	7 May →
overpass	13–6	0.11	25%	6 May →
dust2	7–13	0.00	0%	6 May →
mirage	9–13	-0.01	24%	6 May →
cache	12–12	-0.01	21%	5 May →
nuke	13–7	0.12	24%	5 May →