NotaJag — CS2 Stats

76561198277161244[U:1:316895516]

1,396Tracked matches43%Win rate2020Tracked since

CSDB Rating3.8 Learning

Premier CS Rating11,442Blue band · top ~47.3% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim43

Positioning41

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY44–50–6Last 10044%Win rateWWLLWLLWWL

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

Aim4.3

Aggression5.1

Utility5.9

Positioning4.1

Opening Duels1.7

Clutch1.8

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 84% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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

Areas to improve

Reaction time. 622ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.3

Positioning4.1

Utility5.9

Mechanics4.0

Opening Duels1.7

Win Impact2.6

Composite 3.8/10 (Learning), 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 rating-0.02−0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time622ms−13ms

first ⅓ avg 635ms → last ⅓ avg 622ms

Headshot accuracy10.3%−0.6%

first ⅓ avg 10.8% → last ⅓ avg 10.3%

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

0.10Best rating — dust2 13–9

13–1Biggest win — cache

4Longest win streak

W2Current streak

7–5In matches decided by ≤2 rounds

10Overtime games

Map breakdown

dust2Best map · 53% over 15infernoWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	16	6–10	38%	-0.04
cache	B	16	8–8	50%	-0.03
dust2	B	15	8–7	53%	0.00
nuke	C	14	6–8	43%	-0.03
ancient	B	13	6–7	46%	-0.01
anubis	B	11	5–6	45%	-0.02
inferno	D	9	3–6	33%	-0.03
overpass	—	3	2–1	67%	0.00
vertigo	—	2	0–2	0%	-0.09
train	—	1	0–1	0%	0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

16Matches

50%Win rate

0.80Avg K/D

75.1ADR

38%Headshot %

Clutches & streaks

29%1v1 clutch win

0%1v2 clutch win

2Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	4	50%	0.84	14.3
Ancient	3	67%	0.79	15.3
Mirage	3	33%	0.84	14.0
Nuke	3	33%	0.79	12.0
Anubis	2	50%	0.76	12.5
Inferno	1	100%	0.72	13.0

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.

10.3%Headshot accuracy

34.8%Accuracy (enemy spotted)

36.8%Spray accuracy

68.2%Counter-strafing

11.0°Preaim

622msReaction time

35.7%T opening success

37.8%CT opening success

0.58Enemies flashed / flash

6.1%Flash assists

11.21HE damage / grenade

14.10Flashes / 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.

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 10.306% — below the 15% mark we flag
Aim Training →
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 35.6755% — 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 9 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
inferno	13–9	-0.01	14%	29 Aug →
nuke	13–6	0.00	10%	29 Aug →
inferno	5–13	-0.03	15%	29 Aug →
mirage	4–13	-0.06	5%	28 Aug →
cache	13–6	-0.01	19%	23 Aug →
anubis	7–13	-0.04	7%	22 Aug →
cache	4–13	0.01	7%	21 Aug →
dust2	13–9	0.03	11%	21 Aug →
anubis	13–11	-0.05	10%	21 Aug →
nuke	11–13	-0.09	12%	20 Aug →
anubis	13–10	0.02	8%	20 Aug →
mirage	13–9	0.01	7%	20 Aug →
mirage	8–13	-0.01	5%	19 Aug →
ancient	6–13	-0.03	6%	19 Aug →
dust2	13–6	-0.05	5%	19 Aug →
cache	15–15	-0.06	7%	13 Aug →
dust2	13–3	0.03	27%	10 Aug →
nuke	8–13	-0.01	14%	10 Aug →
ancient	2–13	-0.02	17%	9 Aug →
ancient	13–3	0.10	7%	9 Aug →
anubis	13–16	-0.07	16%	9 Aug →
dust2	10–13	0.01	11%	8 Aug →
anubis	13–10	-0.03	6%	8 Aug →
vertigo	6–13	-0.11	0%	8 Aug →
vertigo	12–12	-0.07	11%	8 Aug →
dust2	10–13	-0.02	6%	8 Aug →
mirage	13–9	-0.03	9%	5 Aug →
nuke	6–13	-0.08	16%	5 Aug →
mirage	6–13	-0.03	9%	5 Aug →
dust2	11–13	-0.05	12%	5 Aug →
nuke	16–13	-0.03	10%	3 Aug →
inferno	10–13	0.03	7%	2 Aug →
ancient	13–9	0.00	10%	2 Aug →
cache	13–9	-0.05	13%	1 Aug →
dust2	6–13	-0.02	13%	1 Aug →
ancient	11–13	-0.06	11%	30 Jul →
mirage	7–13	-0.05	8%	27 Jul →
ancient	8–13	0.02	15%	27 Jul →
ancient	13–5	0.01	4%	27 Jul →
cache	12–12	-0.02	10%	26 Jul →
ancient	16–12	-0.03	7%	25 Jul →
mirage	13–9	-0.00	7%	25 Jul →
cache	13–1	0.01	13%	25 Jul →
nuke	13–11	0.06	15%	25 Jul →
mirage	6–13	-0.02	3%	24 Jul →
nuke	7–13	-0.06	17%	24 Jul →
dust2	7–13	-0.04	10%	24 Jul →
nuke	8–13	0.01	19%	24 Jul →
ancient	13–7	-0.02	7%	23 Jul →
nuke	13–7	-0.05	3%	22 Jul →
anubis	15–15	-0.02	13%	22 Jul →
cache	10–13	-0.09	6%	22 Jul →
cache	13–9	-0.02	18%	22 Jul →
anubis	13–11	-0.01	12%	22 Jul →
cache	13–9	-0.07	13%	22 Jul →
nuke	13–5	-0.04	20%	22 Jul →
dust2	10–13	-0.04	10%	21 Jul →
dust2	13–2	0.10	13%	21 Jul →
inferno	7–13	-0.00	13%	21 Jul →
cache	7–13	-0.03	10%	20 Jul →
mirage	8–13	-0.06	6%	20 Jul →
ancient	10–13	-0.04	11%	20 Jul →
inferno	10–13	-0.03	14%	19 Jul →
mirage	16–13	-0.08	13%	19 Jul →
cache	9–13	-0.01	21%	19 Jul →
cache	13–10	-0.01	14%	19 Jul →
inferno	15–15	-0.04	6%	19 Jul →
train	12–12	0.00	20%	16 Jul →
anubis	7–13	0.01	16%	16 Jul →
inferno	16–14	-0.08	11%	14 Jul →
dust2	14–16	-0.02	10%	14 Jul →
mirage	13–6	0.08	10%	13 Jul →
overpass	10–13	-0.04	6%	12 Jul →
cache	8–13	0.01	8%	12 Jul →
dust2	13–11	0.02	6%	11 Jul →
cache	4–13	-0.07	11%	11 Jul →
inferno	5–2	0.01	10%	11 Jul →
mirage	9–13	-0.07	12%	10 Jul →
dust2	13–9	0.10	21%	10 Jul →
nuke	13–8	0.03	15%	10 Jul →
anubis	5–13	-0.03	12%	10 Jul →
cache	13–7	-0.06	8%	10 Jul →
cache	13–6	-0.01	5%	9 Jul →
nuke	11–13	-0.05	9%	4 Jul →
dust2	13–4	0.05	14%	4 Jul →
ancient	1–13	-0.03	11%	4 Jul →
overpass	13–6	-0.02	5%	4 Jul →
anubis	8–13	-0.03	16%	3 Jul →
mirage	7–13	-0.04	18%	3 Jul →
nuke	5–13	-0.04	21%	3 Jul →
overpass	13–6	0.06	11%	2 Jul →
inferno	10–13	-0.07	11%	29 Jun →
ancient	13–11	-0.05	8%	29 Jun →
ancient	8–13	-0.02	9%	28 Jun →
anubis	13–6	0.05	2%	27 Jun →
mirage	8–13	-0.10	14%	20 Jun →
mirage	7–13	-0.09	5%	20 Jun →
mirage	16–14	-0.08	10%	18 Jun →
dust2	13–3	-0.05	9%	18 Jun →
nuke	0–13	-0.07	3%	6 Jun →