Nonni — CS2 Stats

IS76561199048339673[U:1:1088073945]Steam profile ↗✓ No bans

6,676Tracked matches59%Win rate2020Tracked since

CSDB Rating6.9 SolidAggressive Rifler

FaceitLevel 10 · 2,593 ELOTop 12.4% of ranked FACEIT players

WingmanThe Global Elite

Ladder ranks via Leetify

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Performance scores

Aim85

Positioning50

Utility72

0–100 skill scores via Leetify.

Recent form

STEADY64–33–3Last 10064%Win rateLWWLWWLWWT

Last 10 vs previous 10: +10pp win rate · -0.03 avg rating

Player DNA

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

Aim8.5

Aggression6.7

Utility7.2

Positioning5.0

Opening Duels2.8

Clutch3.8

Sharp aimerStrong 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 Twistzz 95% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 49% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 603ms 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

Aim8.5

Positioning5.0

Utility7.2

Mechanics6.8

Opening Duels2.8

Win Impact8.1

Composite 6.9/10 (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 rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time608ms−61ms

first ⅓ avg 669ms → last ⅓ avg 608ms

Headshot accuracy25.9%+3.0%

first ⅓ avg 22.8% → last ⅓ avg 25.9%

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

0.13Best rating — cache 13–5

13–1Biggest win — inferno

11Longest win streak

17–4In matches decided by ≤2 rounds

8Overtime games

Map breakdown

vertigoBest map · 100% over 7ancientWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
cache	A	17	10–7	59%	0.01
anubis	A	16	9–7	56%	0.00
overpass	B	15	7–8	47%	-0.01
nuke	S	14	10–4	71%	0.01
inferno	S	8	6–2	75%	0.03
vertigo	S	7	7–0	100%	-0.00
train	S	6	5–1	83%	0.05
ancient	C	5	2–3	40%	-0.01
mirage	—	4	1–3	25%	-0.01
poseidon	—	3	2–1	67%	0.00
dust2	—	2	2–0	100%	0.04
warden	—	1	1–0	100%	0.04
alpine	—	1	1–0	100%	0.04
office	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6,051Matches

53%Win rate

1.01Avg K/D

72.0ADR

49%Headshot %

Clutches & streaks

39%1v1 clutch win

20%1v2 clutch win

12Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	973	57%	1.04	14.6
Nuke	893	60%	1.06	14.8
Ancient	527	53%	1.01	14.6
Dust2	461	46%	0.91	13.9
Overpass	276	53%	1.02	14.5
Train	272	65%	1.09	15.0
Vertigo	243	58%	1.00	14.5
Mirage	241	39%	0.95	13.6

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.

27.1%Headshot accuracy

37.5%Accuracy (enemy spotted)

40.1%Spray accuracy

80.7%Counter-strafing

9.3°Preaim

603msReaction time

33.7%T opening success

49.1%CT opening success

0.64Enemies flashed / flash

12.4%Flash assists

10.55HE damage / grenade

14.21Flashes / 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 33.7006% — 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.

40% win rate across 5 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
overpass	3–9	-0.11	20%	28 Aug →
cache	13–11	-0.00	27%	26 Aug →
vertigo	9–3	0.04	7%	24 Aug →
overpass	2–9	-0.17	14%	24 Aug →
train	13–11	-0.00	30%	18 Aug →
dust2	13–4	-0.00	26%	17 Aug →
anubis	19–22	0.03	19%	16 Aug →
inferno	13–10	-0.02	18%	16 Aug →
poseidon	9–7	-0.02	42%	3 Aug →
cache	12–12	-0.01	38%	29 Jul →
vertigo	6–0	-0.04	0%	29 Jul →
anubis	13–3	0.12	36%	22 Jul →
anubis	8–13	-0.04	16%	8 Jul →
anubis	9–13	-0.03	15%	5 Jul →
nuke	4–13	-0.02	24%	30 Jun →
cache	12–12	-0.08	25%	30 Jun →
nuke	13–11	0.01	35%	30 Jun →
nuke	13–7	0.07	29%	28 Jun →
anubis	16–14	-0.00	25%	22 Jun →
train	9–13	0.08	32%	17 Jun →
nuke	13–4	0.07	38%	15 Jun →
nuke	22–20	0.01	29%	15 Jun →
anubis	13–11	-0.00	15%	11 Jun →
cache	13–3	0.09	34%	11 Jun →
cache	11–13	-0.01	25%	9 Jun →
mirage	8–13	0.03	31%	5 Jun →
cache	10–13	0.07	26%	4 Jun →
cache	13–5	0.05	42%	3 Jun →
vertigo	13–10	0.04	38%	3 Jun →
anubis	13–11	0.09	28%	30 May →
anubis	15–15	0.01	24%	28 May →
overpass	4–13	-0.10	11%	28 May →
anubis	7–13	-0.02	33%	28 May →
anubis	5–13	-0.03	36%	26 May →
cache	13–9	-0.01	30%	25 May →
overpass	13–8	0.07	20%	25 May →
dust2	13–4	0.08	33%	7 May →
cache	7–13	-0.05	16%	7 May →
cache	11–13	-0.03	10%	7 May →
cache	13–7	0.01	15%	6 May →
cache	13–9	0.03	47%	29 Apr →
cache	2–13	-0.06	36%	29 Apr →
cache	13–5	0.13	28%	29 Apr →
cache	13–7	0.01	31%	29 Apr →
cache	13–4	0.13	36%	28 Apr →
cache	13–11	-0.05	43%	28 Apr →
inferno	13–11	-0.00	22%	26 Apr →
train	13–6	0.09	35%	26 Apr →
mirage	13–16	-0.03	22%	25 Apr →
inferno	13–1	0.12	33%	25 Apr →
overpass	6–9	-0.02	23%	25 Apr →
poseidon	5–9	-0.04	33%	25 Apr →
inferno	13–16	-0.01	27%	22 Apr →
inferno	9–7	-0.09	12%	22 Apr →
nuke	13–1	0.03	56%	20 Apr →
anubis	13–10	-0.03	27%	17 Apr →
overpass	13–4	0.08	47%	17 Apr →
nuke	10–13	-0.02	34%	16 Apr →
mirage	6–13	-0.01	25%	15 Apr →
overpass	6–13	-0.05	13%	15 Apr →
nuke	13–10	0.00	33%	15 Apr →
ancient	8–13	-0.02	28%	13 Apr →
poseidon	9–5	0.06	47%	9 Apr →
vertigo	13–7	0.01	31%	9 Apr →
vertigo	13–2	0.02	16%	9 Apr →
train	13–3	0.04	55%	7 Apr →
warden	13–5	0.04	61%	7 Apr →
ancient	11–13	-0.03	25%	7 Apr →
overpass	19–17	-0.01	25%	4 Apr →
anubis	13–8	-0.03	22%	2 Apr →
anubis	7–13	0.01	27%	2 Apr →
overpass	13–11	0.00	18%	1 Apr →
nuke	15–19	0.04	29%	1 Apr →
overpass	13–2	0.08	28%	1 Apr →
ancient	13–2	0.03	21%	1 Apr →
ancient	13–7	-0.00	26%	29 Mar →
alpine	13–3	0.04	38%	26 Mar →
train	13–3	0.04	23%	26 Mar →
anubis	13–4	-0.01	41%	26 Mar →
train	13–9	0.07	19%	23 Mar →
office	13–6	0.04	28%	23 Mar →
nuke	13–11	-0.06	14%	19 Mar →
anubis	13–10	-0.05	11%	19 Mar →
mirage	13–10	-0.04	26%	19 Mar →
overpass	10–13	-0.03	16%	19 Mar →
nuke	10–13	-0.03	21%	18 Mar →
nuke	13–11	0.01	29%	13 Mar →
inferno	9–6	-0.01	16%	12 Mar →
vertigo	9–5	0.00	15%	12 Mar →
inferno	8–13	0.10	18%	12 Mar →
overpass	10–13	0.03	42%	12 Mar →
overpass	13–2	0.04	33%	12 Mar →
ancient	9–13	-0.01	15%	26 Feb →
anubis	13–10	-0.00	9%	26 Feb →
overpass	13–4	0.02	10%	26 Feb →
nuke	9–7	-0.02	13%	25 Feb →
nuke	9–2	0.12	23%	25 Feb →
inferno	9–7	0.12	23%	25 Feb →
vertigo	9–4	-0.08	33%	25 Feb →
overpass	11–13	-0.04	17%	21 Feb →