Nanon — CS2 Stats

DE76561198257591416[U:1:297325688]Steam profile ↗✓ No bans

2,626Tracked matches59%Win rate2020Tracked since

CSDB Rating6.8 SolidAggressive Rifler

Premier CS Rating21,444Top 50% of 17,162 CSDB-tracked playersPink band · top ~6.9% of ranked players (population est.)

CSDB Leaderboard#9614 of 29263 tracked

FaceitLevel 9Top 20.7% of ranked FACEIT players

WingmanMaster Guardian II

Ladder ranks via Leetify

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Performance scores

Aim87

Positioning58

Utility45

0–100 skill scores via Leetify.

Recent form

STEADY52–45–3Last 10052%Win rateLLWLWLWWWL

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

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

Aim8.7

Aggression10.0

Utility4.5

Positioning5.8

Opening Duels5.3

Clutch3.2

Sharp aimerLimited 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 90% playstyle similarity

Most alike: positioning profile, utility contribution.

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 87 — the mechanical foundation is a clear strength.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim8.7

Positioning5.8

Utility4.5

Mechanics6.3

Opening Duels5.3

Win Impact7.9

Composite 6.8/10 (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 0.01 → last ⅓ avg 0.03

Reaction time535ms−62ms

first ⅓ avg 596ms → last ⅓ avg 535ms

Headshot accuracy18.4%+4.9%

first ⅓ avg 13.6% → last ⅓ avg 18.4%

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

0.16Best rating — boulder 13–4

13–0Biggest win — fachwerk

6Longest win streak

L2Current streak

8–6In matches decided by ≤2 rounds

7Overtime games

Map breakdown

nukeBest map · 80% over 5ancientWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	18	7–11	39%	0.01
inferno	C	15	6–9	40%	0.01
dust2	B	14	7–7	50%	0.03
cache	S	12	8–4	67%	0.05
anubis	B	10	5–5	50%	0.01
train	S	7	5–2	71%	0.05
overpass	A	7	4–3	57%	0.05
ancient	D	6	2–4	33%	-0.02
nuke	S	5	4–1	80%	0.04
fachwerk	—	2	1–1	50%	0.03
office	—	1	1–0	100%	0.03
boulder	—	1	1–0	100%	0.16
shelter	—	1	1–0	100%	0.01
vertigo	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

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

Faceit stats

Combat

2,494Matches

51%Win rate

1.07Avg K/D

84.7ADR

41%Headshot %

Clutches & streaks

36%1v1 clutch win

17%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	212	45%	0.97	14.8
Anubis	115	53%	0.93	15.4
Ancient	76	55%	1.09	15.6
Dust2	62	29%	0.93	15.3
Inferno	56	57%	0.96	16.2
Vertigo	46	50%	0.98	14.8
Overpass	41	71%	1.07	15.1
Nuke	26	65%	0.93	14.4

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.

17.7%Headshot accuracy

40.7%Accuracy (enemy spotted)

41.8%Spray accuracy

78.6%Counter-strafing

7.1°Preaim

541msReaction time

47.6%T opening success

54.5%CT opening success

0.48Enemies flashed / flash

8.4%Flash assists

10.79HE damage / grenade

3.72Flashes / 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
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4818 — below the 0.5 mark we flag
Grenade Lineups →

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.

33% win rate across 6 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
anubis	11–13	0.02	11%	28 Aug →
mirage	12–16	0.00	11%	22 Aug →
cache	16–12	0.02	12%	14 Aug →
mirage	14–16	-0.00	9%	13 Aug →
train	13–5	0.05	33%	13 Aug →
anubis	8–13	-0.05	9%	10 Aug →
train	13–11	0.06	22%	10 Aug →
overpass	13–6	0.14	24%	10 Aug →
inferno	13–2	0.09	42%	10 Aug →
overpass	10–13	0.01	33%	10 Aug →
inferno	13–4	0.16	30%	10 Aug →
cache	7–13	0.07	19%	9 Aug →
fachwerk	11–13	-0.02	14%	6 Aug →
office	13–6	0.03	31%	6 Aug →
anubis	13–8	0.03	18%	4 Aug →
anubis	13–10	0.04	12%	3 Aug →
mirage	10–13	-0.02	25%	1 Aug →
cache	13–7	0.02	10%	25 Jul →
anubis	4–13	0.02	19%	22 Jul →
inferno	8–13	-0.04	17%	21 Jul →
cache	13–6	0.09	16%	21 Jul →
cache	13–5	-0.04	8%	20 Jul →
mirage	13–8	-0.03	11%	20 Jul →
inferno	13–10	0.00	12%	17 Jul →
mirage	9–13	-0.01	10%	17 Jul →
anubis	13–6	-0.02	28%	17 Jul →
mirage	13–5	0.07	17%	17 Jul →
cache	13–5	0.07	17%	17 Jul →
cache	4–13	0.10	20%	17 Jul →
cache	12–12	0.01	13%	17 Jul →
boulder	13–4	0.16	22%	17 Jul →
shelter	13–11	0.01	18%	17 Jul →
fachwerk	13–0	0.08	18%	17 Jul →
dust2	11–7	0.09	18%	17 Jul →
nuke	13–9	0.03	26%	16 Jul →
nuke	16–14	0.03	19%	16 Jul →
inferno	5–13	-0.01	7%	16 Jul →
inferno	11–13	0.02	22%	5 Jul →
dust2	13–6	-0.00	22%	5 Jul →
inferno	0–13	-0.02	33%	3 Jul →
mirage	2–13	-0.02	32%	3 Jul →
overpass	13–4	0.03	12%	1 Jul →
inferno	7–13	-0.02	19%	1 Jul →
mirage	8–13	0.10	25%	29 Jun →
overpass	9–13	0.01	15%	29 Jun →
cache	13–4	0.08	35%	28 Jun →
train	13–4	0.07	15%	28 Jun →
cache	13–9	0.12	44%	28 Jun →
train	5–13	-0.01	23%	18 Jun →
overpass	13–11	0.09	19%	18 Jun →
train	10–13	0.05	28%	18 Jun →
mirage	16–14	0.05	14%	10 Jun →
ancient	4–13	-0.05	12%	8 Jun →
mirage	13–4	0.05	24%	8 Jun →
ancient	11–13	-0.02	11%	7 Jun →
vertigo	5–13	-0.02	18%	4 Jun →
anubis	12–12	0.06	10%	27 May →
dust2	6–13	-0.03	13%	21 May →
dust2	3–13	0.00	28%	21 May →
dust2	9–13	-0.02	18%	16 May →
cache	5–13	-0.00	11%	11 May →
cache	13–5	0.09	11%	11 May →
train	13–4	0.07	26%	28 Apr →
train	13–6	0.05	9%	27 Apr →
inferno	10–13	-0.06	20%	24 Apr →
mirage	13–9	0.02	26%	23 Apr →
anubis	13–9	-0.04	10%	23 Apr →
mirage	8–13	-0.05	16%	23 Apr →
nuke	13–6	0.04	8%	17 Apr →
nuke	13–11	0.08	8%	17 Apr →
inferno	13–6	-0.03	15%	14 Apr →
ancient	7–13	-0.03	11%	14 Apr →
mirage	3–13	-0.07	18%	12 Apr →
mirage	10–13	0.00	7%	11 Apr →
overpass	8–13	-0.03	9%	11 Apr →
mirage	8–13	0.00	15%	10 Apr →
dust2	10–13	-0.00	14%	8 Apr →
ancient	8–13	0.00	16%	8 Apr →
mirage	13–10	0.04	12%	8 Apr →
dust2	0–9	-0.15	0%	30 Mar →
anubis	16–14	-0.06	9%	29 Mar →
ancient	13–10	-0.01	9%	28 Mar →
mirage	13–8	-0.02	12%	27 Mar →
dust2	13–3	-0.01	29%	27 Mar →
inferno	5–13	-0.05	29%	26 Mar →
ancient	13–8	-0.02	6%	26 Mar →
dust2	13–9	0.03	20%	25 Mar →
anubis	7–13	0.06	19%	25 Mar →
dust2	13–5	0.08	15%	25 Mar →
nuke	8–13	0.01	11%	25 Mar →
overpass	13–4	0.09	8%	24 Mar →
inferno	13–7	0.03	8%	24 Mar →
dust2	12–12	0.13	13%	23 Mar →
dust2	13–8	0.16	24%	23 Mar →
inferno	11–13	0.08	13%	23 Mar →
inferno	1–5	-0.02	29%	23 Mar →
dust2	13–8	0.14	11%	22 Mar →
mirage	9–13	0.09	23%	22 Mar →
dust2	2–13	-0.03	7%	22 Mar →
inferno	16–14	-0.00	3%	22 Mar →