No1r — CS2 Stats

DK76561199144028010[U:1:1183762282]Steam profile ↗✓ No bans

2,269Tracked matches45%Win rate2022Tracked since

CSDB Rating7.0 StrongAggressive Rifler

FaceitLevel 10 · 3,363 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim93

Positioning62

Utility53

0–100 skill scores via Leetify.

Recent form

STEADY49–47–4Last 10049%Win rateWLLLWLLWWW

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating

Player DNA

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

Aim9.3

Aggression6.6

Utility5.3

Positioning6.2

Opening Duels2.1

Clutch3.6

Sharp aimer

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: aim profile, positioning profile.

Where you differ: higher 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

Strengths

Aim. Aim score of 93 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 31 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.

Reaction time. 590ms 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

Aim9.3

Positioning6.2

Utility5.3

Mechanics8.4

Opening Duels2.1

Win Impact3.3

Composite 7.0/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03−0.01

first ⅓ avg 0.04 → last ⅓ avg 0.03

Reaction time580ms+8ms

first ⅓ avg 571ms → last ⅓ avg 580ms

Headshot accuracy37.1%+4.3%

first ⅓ avg 32.8% → last ⅓ avg 37.1%

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

0.37Best rating — overpass 9–0

13–1Biggest win — anubis

4Longest win streak

11–4In matches decided by ≤2 rounds

7Overtime games

Map breakdown

nukeBest map · 83% over 18infernoWeakest map · 25% over 16

Map	Grade	Played	Record	Win rate	Avg rating
anubis	B	20	9–11	45%	-0.00
nuke	S	18	15–3	83%	0.02
inferno	D	16	4–12	25%	0.02
ancient	C	14	5–9	36%	0.03
mirage	C	12	5–7	42%	0.01
cache	S	6	4–2	67%	0.04
overpass	S	6	5–1	83%	0.09
dust2	—	4	1–3	25%	0.05
vertigo	—	4	1–3	25%	0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,281Matches

54%Win rate

1.15Avg K/D

76.1ADR

67%Headshot %

Clutches & streaks

38%1v1 clutch win

23%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	606	56%	1.19	17.1
Anubis	459	55%	1.15	16.8
Nuke	389	53%	1.13	16.2
Inferno	216	50%	1.13	16.1
Mirage	154	49%	1.06	16.1
Vertigo	125	59%	1.24	18.4
Overpass	107	51%	1.14	16.1
Train	106	56%	1.09	16.0

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.

38.1%Headshot accuracy

35.0%Accuracy (enemy spotted)

38.5%Spray accuracy

87.7%Counter-strafing

8.9°Preaim

590msReaction time

40.6%T opening success

35.9%CT opening success

0.61Enemies flashed / flash

10.2%Flash assists

7.79HE damage / grenade

6.83Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 35.8962% — 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.

25% win rate across 16 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	13–6	0.05	39%	22 Aug →
anubis	8–13	-0.05	41%	6 Aug →
inferno	6–9	0.02	34%	6 Aug →
inferno	7–13	0.01	50%	5 Aug →
mirage	13–10	0.06	77%	5 Aug →
mirage	8–13	-0.03	37%	5 Aug →
ancient	7–13	0.12	45%	4 Aug →
ancient	13–6	0.20	36%	4 Aug →
mirage	13–10	0.03	25%	1 Aug →
anubis	13–1	0.07	42%	1 Aug →
nuke	0–13	-0.06	23%	1 Aug →
mirage	8–13	-0.01	29%	31 Jul →
cache	3–13	0.08	30%	27 Jul →
anubis	12–12	-0.01	35%	25 Jul →
anubis	13–2	-0.05	33%	25 Jul →
nuke	13–7	0.02	24%	24 Jul →
anubis	7–13	-0.09	35%	22 Jul →
inferno	9–13	0.08	38%	15 Jul →
nuke	13–11	0.08	40%	12 Jul →
dust2	6–13	0.06	38%	9 Jul →
dust2	13–7	0.14	26%	9 Jul →
cache	13–6	0.12	48%	8 Jul →
cache	13–11	0.01	40%	7 Jul →
cache	10–13	0.05	75%	7 Jul →
dust2	3–13	-0.02	38%	1 Jul →
ancient	10–13	0.05	35%	30 Jun →
mirage	5–13	0.01	38%	29 Jun →
vertigo	8–13	0.01	36%	29 Jun →
mirage	11–13	-0.02	31%	27 Jun →
anubis	13–9	-0.05	28%	27 Jun →
nuke	13–11	-0.05	21%	22 Jun →
inferno	16–14	0.02	32%	17 Jun →
anubis	16–14	0.02	23%	16 Jun →
nuke	8–13	-0.05	28%	15 Jun →
ancient	10–13	-0.04	32%	12 Jun →
vertigo	12–12	0.01	34%	9 Jun →
vertigo	9–4	0.22	34%	7 Jun →
inferno	8–8	0.09	35%	7 Jun →
nuke	8–8	0.04	21%	7 Jun →
overpass	13–4	0.03	27%	7 Jun →
ancient	14–16	-0.00	33%	6 Jun →
mirage	13–5	0.11	27%	1 Jun →
ancient	13–1	0.09	33%	30 May →
cache	13–10	0.01	32%	16 May →
ancient	9–13	-0.00	28%	14 May →
ancient	13–10	-0.03	27%	14 May →
cache	13–10	-0.03	18%	13 May →
ancient	8–13	0.01	45%	18 Apr →
nuke	16–14	-0.02	30%	14 Apr →
anubis	2–13	-0.03	14%	11 Apr →
nuke	13–11	-0.00	38%	11 Apr →
inferno	7–13	-0.02	14%	11 Apr →
inferno	7–13	-0.02	14%	11 Apr →
anubis	2–13	-0.03	14%	11 Apr →
nuke	13–11	-0.00	38%	11 Apr →
mirage	6–13	-0.04	26%	11 Apr →
anubis	8–13	-0.01	16%	11 Apr →
mirage	6–13	-0.04	26%	11 Apr →
anubis	8–13	-0.01	16%	11 Apr →
inferno	5–13	-0.05	29%	10 Apr →
inferno	8–13	0.09	35%	10 Apr →
nuke	13–1	0.11	34%	10 Apr →
anubis	13–9	0.03	32%	10 Apr →
nuke	13–11	-0.02	34%	6 Apr →
inferno	6–13	-0.02	43%	6 Apr →
vertigo	6–13	0.07	29%	4 Apr →
anubis	14–16	-0.01	40%	4 Apr →
overpass	13–10	0.01	29%	3 Apr →
anubis	6–13	-0.04	39%	2 Apr →
overpass	6–13	-0.02	31%	28 Mar →
inferno	2–13	-0.10	41%	28 Mar →
nuke	13–7	0.09	35%	18 Mar →
mirage	16–13	-0.01	35%	12 Mar →
inferno	5–9	-0.00	21%	11 Mar →
inferno	13–9	0.06	33%	7 Mar →
overpass	9–0	0.37	62%	6 Mar →
nuke	13–3	-0.00	32%	2 Mar →
nuke	8–2	0.11	29%	2 Mar →
anubis	7–13	0.01	30%	2 Mar →
overpass	13–9	0.06	26%	2 Mar →
anubis	13–1	0.07	32%	28 Feb →
ancient	13–7	0.05	36%	28 Feb →
anubis	5–13	0.02	12%	21 Feb →
inferno	7–13	-0.01	41%	8 Feb →
mirage	13–9	-0.00	50%	8 Feb →
anubis	13–5	0.05	32%	8 Feb →
ancient	9–13	-0.05	48%	5 Feb →
dust2	10–13	0.03	30%	5 Feb →
inferno	13–4	0.01	26%	5 Feb →
anubis	13–10	0.00	29%	5 Feb →
nuke	13–6	0.02	55%	31 Jan →
ancient	7–13	0.03	53%	31 Jan →
ancient	13–10	0.06	30%	31 Jan →
mirage	10–13	0.04	36%	30 Jan →
nuke	13–7	0.04	38%	30 Jan →
anubis	13–11	0.08	40%	30 Jan →
ancient	14–16	-0.05	28%	30 Jan →
nuke	13–11	-0.00	24%	25 Jan →
overpass	9–5	0.09	0%	24 Jan →
inferno	9–0	0.17	0%	24 Jan →