noah — CS2 Stats

76561198798171556[U:1:837905828]

2,957Tracked matches54%Win rate2020Tracked since

CSDB Rating5.8 SolidHybrid Rifler

Premier CS Rating22,341Top 50% of 29,473 CSDB-tracked playersPink band · top ~5.9% of ranked players (population est.)

CSDB Leaderboard#12251 of 47657 tracked

FaceitLevel 9 · 1,799 ELOTop 20.7% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim67

Positioning59

Utility29

0–100 skill scores via Leetify.

Recent form

STEADY54–41–5Last 10054%Win rateLWLLWWTLLW

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

Player DNA

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

Aim6.7

Aggression7.2

Utility2.9

Positioning5.9

Opening Duels4.3

Clutch3.0

Strong CT-side openerLimited utility dependence

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 88% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

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 56% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 645ms 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

Aim6.7

Positioning5.9

Utility2.9

Mechanics6.7

Opening Duels4.3

Win Impact6.2

Composite 5.8/10 (Solid), 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 rating0.03+0.02

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time638ms+50ms

first ⅓ avg 587ms → last ⅓ avg 638ms

Headshot accuracy23.9%+5.3%

first ⅓ avg 18.6% → last ⅓ avg 23.9%

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

0.29Best rating — mirage 13–5

13–0Biggest win — train

7Longest win streak

11–6In matches decided by ≤2 rounds

14Overtime games

Map breakdown

dust2Best map · 67% over 15ancientWeakest map · 42% over 26

Map	Grade	Played	Record	Win rate	Avg rating
ancient	C	26	11–15	42%	0.02
dust2	S	15	10–5	67%	0.02
overpass	A	15	9–6	60%	0.02
inferno	A	12	7–5	58%	0.05
mirage	B	11	5–6	45%	0.05
nuke	A	11	6–5	55%	0.03
train	B	6	3–3	50%	0.01
vertigo	—	2	2–0	100%	0.12
anubis	—	1	0–1	0%	0.08
office	—	1	1–0	100%	-0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (42% over 26). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

863Matches

51%Win rate

1.03Avg K/D

77.9ADR

38%Headshot %

Clutches & streaks

35%1v1 clutch win

26%1v2 clutch win

8Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	107	49%	1.04	16.2
Ancient	105	61%	1.03	15.9
Vertigo	71	61%	0.89	13.8
Mirage	61	33%	0.85	13.4
Inferno	46	46%	0.99	16.3
Dust2	37	38%	0.95	14.6
Overpass	17	59%	0.88	14.0
Nuke	17	53%	1.16	17.2

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.

23.6%Headshot accuracy

35.0%Accuracy (enemy spotted)

29.1%Spray accuracy

80.2%Counter-strafing

9.7°Preaim

645msReaction time

37.9%T opening success

56.2%CT opening success

0.54Enemies flashed / flash

13.6%Flash assists

1.88HE damage / grenade

3.13Flashes / 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.

Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.1276 — below the 4 mark we flag
Grenade Lineups →
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 37.9055% — below the 40% mark we flag

Spend your practice time on Ancient

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

42% win rate across 26 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	8–13	0.01	17%	11 Dec →
dust2	13–5	0.06	31%	11 Dec →
mirage	2–11	0.01	23%	11 Dec →
overpass	8–13	0.03	13%	10 Dec →
dust2	13–11	-0.01	29%	10 Dec →
mirage	13–2	-0.03	19%	10 Dec →
ancient	15–15	0.00	19%	24 Nov →
mirage	9–13	-0.04	13%	24 Nov →
dust2	4–13	-0.05	16%	24 Nov →
overpass	13–5	-0.01	13%	20 Nov →
nuke	5–13	0.02	18%	20 Nov →
inferno	13–7	-0.01	23%	2 Nov →
dust2	13–11	0.00	23%	2 Nov →
ancient	9–13	0.00	31%	2 Nov →
nuke	5–13	0.01	21%	2 Nov →
dust2	13–11	0.05	17%	2 Nov →
vertigo	13–8	0.13	17%	31 Oct →
nuke	13–4	0.02	24%	31 Oct →
overpass	9–13	0.01	23%	31 Oct →
ancient	13–2	0.12	29%	31 Oct →
ancient	7–13	0.02	26%	29 Oct →
mirage	13–5	0.29	29%	29 Oct →
dust2	7–13	0.04	27%	29 Oct →
vertigo	13–3	0.12	19%	29 Oct →
dust2	15–15	-0.01	27%	19 Oct →
train	13–9	0.04	27%	19 Oct →
ancient	16–14	-0.00	25%	19 Oct →
nuke	13–11	-0.01	42%	19 Oct →
inferno	6–13	0.00	29%	19 Oct →
overpass	12–16	0.00	33%	18 Oct →
ancient	13–7	0.07	28%	18 Oct →
nuke	11–13	0.12	36%	11 Oct →
ancient	12–12	0.10	24%	11 Oct →
inferno	6–13	0.05	24%	11 Oct →
dust2	1–13	-0.07	19%	11 Oct →
mirage	4–13	0.05	25%	11 Oct →
ancient	6–13	-0.05	23%	10 Oct →
dust2	16–14	-0.03	21%	10 Oct →
mirage	9–13	-0.02	26%	10 Oct →
overpass	13–9	0.03	16%	10 Oct →
ancient	13–4	0.01	32%	7 Oct →
mirage	13–2	-0.02	18%	7 Oct →
ancient	13–3	-0.04	26%	7 Oct →
dust2	13–9	0.10	23%	27 Sept →
inferno	9–13	0.19	24%	27 Sept →
anubis	4–13	0.08	18%	27 Sept →
overpass	13–8	0.05	15%	27 Sept →
mirage	13–8	0.19	24%	27 Sept →
ancient	7–13	0.06	16%	27 Sept →
mirage	6–13	0.02	38%	27 Sept →
dust2	12–12	0.07	30%	27 Sept →
inferno	9–6	0.15	22%	27 Sept →
inferno	13–10	-0.02	11%	24 Sept →
train	11–13	0.03	12%	24 Sept →
ancient	16–14	-0.03	18%	23 Sept →
overpass	16–14	0.03	16%	23 Sept →
nuke	10–13	0.09	35%	23 Sept →
inferno	13–6	0.16	32%	23 Sept →
nuke	13–4	-0.01	15%	23 Sept →
dust2	13–2	-0.01	16%	23 Sept →
ancient	13–11	0.05	21%	23 Sept →
nuke	16–14	0.03	20%	15 Sept →
mirage	13–7	0.01	18%	15 Sept →
train	13–0	0.08	32%	11 Sept →
train	4–13	-0.03	24%	10 Sept →
inferno	10–13	-0.01	29%	8 Sept →
overpass	13–9	0.04	26%	1 Sept →
ancient	13–10	0.07	21%	1 Sept →
inferno	16–12	0.04	31%	30 Aug →
ancient	11–13	0.06	25%	30 Aug →
dust2	13–8	0.03	9%	30 Aug →
inferno	7–9	0.04	20%	30 Aug →
office	13–4	-0.05	23%	29 Aug →
dust2	16–13	0.03	21%	29 Aug →
nuke	16–13	0.08	16%	29 Aug →
overpass	15–15	-0.02	20%	29 Aug →
nuke	11–13	0.06	17%	29 Aug →
inferno	13–10	-0.03	24%	29 Aug →
ancient	8–13	0.01	18%	21 Aug →
overpass	13–8	0.02	11%	21 Aug →
nuke	13–8	-0.04	19%	21 Aug →
dust2	13–9	0.03	16%	21 Aug →
ancient	13–10	-0.03	15%	20 Aug →
ancient	10–13	0.08	17%	19 Aug →
mirage	5–13	0.05	15%	19 Aug →
ancient	11–13	0.06	10%	19 Aug →
overpass	3–13	0.03	15%	16 Aug →
ancient	13–5	0.01	19%	16 Aug →
ancient	7–13	-0.02	24%	16 Aug →
inferno	19–16	0.07	11%	16 Aug →
ancient	10–13	-0.03	20%	15 Aug →
overpass	13–6	0.05	24%	15 Aug →
train	13–10	-0.02	11%	15 Aug →
overpass	6–13	0.04	23%	15 Aug →
overpass	13–10	0.02	21%	15 Aug →
ancient	13–7	0.04	27%	15 Aug →
train	8–13	-0.02	21%	12 Aug →
ancient	10–13	-0.04	13%	12 Aug →
overpass	16–14	-0.08	25%	12 Aug →
ancient	7–13	-0.03	12%	12 Aug →