Jatt — CS2 Stats

76561199099653705[U:1:1139387977]

666Tracked matches66%Win rate2020Tracked since

CSDB Rating7.2 StrongHybrid Rifler

Premier CS Rating19,731Purple band · top ~9.6% of ranked players (population est.)

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning56

Utility55

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateLWWWWWLLWL

Last 10 vs previous 10: -10pp win rate · -0.05 avg rating

Player DNA

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

Aim8.6

Aggression5.5

Utility5.5

Positioning5.6

Opening Duels2.2

Clutch2.0

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 NiKo 94% playstyle similarity

Most alike: opening-duel success, 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.

Counter-strafing. 92% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

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 52% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 588ms 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

Positioning5.6

Utility5.5

Mechanics9.3

Opening Duels2.8

Win Impact10.0

Composite 7.2/10 (Strong), 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 rating0.01+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.01

Reaction time598ms−40ms

first ⅓ avg 638ms → last ⅓ avg 598ms

Headshot accuracy15.9%−3.4%

first ⅓ avg 19.4% → last ⅓ avg 15.9%

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

0.14Best rating — inferno 8–8

13–1Biggest win — cache

6Longest win streak

11–10In matches decided by ≤2 rounds

8Overtime games

Map breakdown

dust2Best map · 64% over 25infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	25	16–9	64%	0.01
mirage	C	23	10–13	43%	0.01
inferno	D	15	5–10	33%	0.02
anubis	B	13	7–6	54%	0.03
cache	A	12	7–5	58%	0.01
ancient	A	8	5–3	63%	0.00
nuke	—	4	2–2	50%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

95Matches

40%Win rate

1.03Avg K/D

78.3ADR

42%Headshot %

Clutches & streaks

30%1v1 clutch win

18%1v2 clutch win

4Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	22	45%	0.97	15.0
Ancient	12	8%	0.87	13.9
Dust2	9	11%	0.77	11.8
Inferno	8	50%	1.20	13.6
Overpass	6	67%	1.13	20.0
Nuke	6	50%	1.05	14.2
Anubis	4	75%	1.45	22.0
Train	2	50%	0.68	11.5

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.

15.3%Headshot accuracy

41.0%Accuracy (enemy spotted)

42.0%Spray accuracy

91.8%Counter-strafing

9.2°Preaim

588msReaction time

25.1%T opening success

52.4%CT opening success

0.60Enemies flashed / flash

5.8%Flash assists

8.08HE damage / grenade

8.95Flashes / 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 25.1124% — 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.

33% win rate across 15 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
mirage	14–16	0.00	14%	21 Aug →
inferno	13–11	-0.01	19%	21 Aug →
dust2	13–11	-0.04	13%	21 Aug →
dust2	13–8	-0.05	12%	20 Aug →
dust2	13–5	-0.01	16%	20 Aug →
mirage	13–10	-0.00	11%	20 Aug →
inferno	6–13	-0.06	20%	19 Aug →
mirage	9–13	0.03	22%	19 Aug →
inferno	13–11	-0.01	16%	18 Aug →
cache	4–10	-0.07	13%	18 Aug →
mirage	13–2	0.13	19%	18 Aug →
anubis	13–5	0.02	17%	18 Aug →
anubis	13–9	-0.00	21%	17 Aug →
mirage	13–10	0.02	8%	17 Aug →
cache	13–6	-0.01	6%	17 Aug →
mirage	13–10	-0.01	20%	17 Aug →
inferno	8–8	0.14	19%	17 Aug →
inferno	7–9	-0.00	25%	17 Aug →
anubis	13–11	0.04	7%	15 Aug →
ancient	9–13	-0.05	13%	15 Aug →
mirage	15–15	0.03	19%	14 Aug →
dust2	7–13	-0.04	7%	14 Aug →
cache	13–7	0.06	15%	14 Aug →
dust2	13–3	0.11	20%	14 Aug →
ancient	11–13	-0.02	10%	14 Aug →
cache	13–10	0.09	26%	14 Aug →
dust2	9–13	0.02	14%	13 Aug →
mirage	4–13	0.03	17%	13 Aug →
ancient	13–11	-0.03	8%	13 Aug →
mirage	6–13	-0.03	18%	12 Aug →
dust2	13–7	0.01	26%	12 Aug →
dust2	16–14	-0.05	17%	11 Aug →
nuke	11–13	0.02	21%	11 Aug →
mirage	13–8	0.03	15%	11 Aug →
mirage	5–13	0.02	19%	11 Aug →
inferno	13–8	0.08	22%	10 Aug →
dust2	13–11	0.00	14%	10 Aug →
anubis	12–16	0.00	23%	10 Aug →
cache	6–13	0.03	25%	10 Aug →
ancient	13–5	0.10	17%	9 Aug →
dust2	13–11	0.13	15%	9 Aug →
inferno	8–13	0.03	15%	8 Aug →
anubis	6–13	-0.01	16%	8 Aug →
nuke	13–6	0.03	11%	8 Aug →
dust2	6–13	-0.02	13%	7 Aug →
mirage	13–11	0.05	15%	7 Aug →
inferno	15–15	0.04	13%	7 Aug →
dust2	2–13	-0.06	16%	7 Aug →
inferno	8–13	-0.01	18%	6 Aug →
ancient	13–6	-0.01	24%	6 Aug →
cache	13–1	0.05	28%	6 Aug →
dust2	11–13	0.07	23%	6 Aug →
cache	7–13	-0.01	18%	6 Aug →
anubis	5–13	0.04	15%	5 Aug →
dust2	13–10	0.00	19%	5 Aug →
mirage	13–11	0.03	21%	5 Aug →
anubis	13–8	0.13	21%	5 Aug →
dust2	13–10	0.08	30%	5 Aug →
inferno	11–13	0.06	20%	5 Aug →
dust2	13–8	0.02	18%	5 Aug →
dust2	3–13	-0.02	36%	30 Jul →
nuke	13–9	-0.01	18%	30 Jul →
ancient	13–3	0.03	14%	30 Jul →
dust2	13–2	0.11	28%	30 Jul →
mirage	10–13	-0.01	20%	29 Jul →
mirage	11–13	-0.02	20%	29 Jul →
dust2	13–8	0.02	19%	29 Jul →
dust2	2–13	-0.04	26%	27 Jul →
cache	13–7	0.01	17%	27 Jul →
mirage	8–13	0.00	13%	27 Jul →
inferno	9–13	-0.02	27%	24 Jul →
mirage	13–9	-0.04	9%	24 Jul →
cache	11–13	-0.03	19%	24 Jul →
mirage	6–13	-0.03	24%	24 Jul →
dust2	13–6	0.03	14%	24 Jul →
mirage	13–11	-0.03	14%	23 Jul →
cache	5–13	-0.06	26%	23 Jul →
inferno	8–13	0.06	27%	23 Jul →
anubis	13–7	0.06	17%	23 Jul →
dust2	9–13	0.00	12%	23 Jul →
inferno	13–9	-0.02	13%	23 Jul →
anubis	7–13	0.03	21%	23 Jul →
nuke	4–13	-0.02	23%	22 Jul →
cache	16–13	-0.00	14%	22 Jul →
dust2	11–13	-0.03	21%	22 Jul →
mirage	2–13	-0.02	22%	21 Jul →
cache	13–10	0.01	31%	21 Jul →
anubis	2–13	-0.04	26%	19 Jul →
dust2	13–8	0.02	22%	19 Jul →
inferno	11–13	0.01	8%	19 Jul →
anubis	16–12	0.01	12%	19 Jul →
dust2	13–9	0.02	17%	18 Jul →
anubis	13–8	0.04	38%	18 Jul →
ancient	13–5	0.00	19%	18 Jul →
mirage	13–6	0.01	15%	18 Jul →
mirage	5–13	-0.09	17%	17 Jul →
anubis	9–13	0.01	15%	17 Jul →
mirage	15–15	0.03	14%	17 Jul →
inferno	13–7	0.04	20%	17 Jul →
ancient	6–13	-0.02	27%	17 Jul →