nesto — CS2 Stats

76561198314421726[U:1:354155998]Steam profile ↗✓ No bans

3,090Tracked matches57%Win rate2020Tracked since

CSDB Rating6.5 SolidSupport

FaceitLevel 10 · 3,441 ELOTop 12.4% of ranked FACEIT players

WingmanThe Global Elite

Ladder ranks via Leetify

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Performance scores

Aim74

Positioning50

Utility76

0–100 skill scores via Leetify.

Recent form

STEADY57–40–3Last 10057%Win rateWLLWWLTLTW

Last 10 vs previous 10: -40pp win rate · -0.07 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim7.4

Aggression3.9

Utility7.6

Positioning5.0

Opening Duels1.2

Clutch3.4

Strong CT-side openerEffective flashesHigh utility contribution

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 88% playstyle similarity

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

Where you differ: 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

Strengths

Utility. Utility score of 76 — grenade impact well above the norm.

Areas to improve

T-side openings. Opening success drops from 43% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 568ms 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

Aim7.4

Positioning5.0

Utility7.6

Mechanics6.0

Opening Duels1.7

Win Impact7.2

Composite 6.5/10 (Solid), 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 rating0.02+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.02

Reaction time576ms−28ms

first ⅓ avg 604ms → last ⅓ avg 576ms

Headshot accuracy30.2%−0.9%

first ⅓ avg 31.2% → last ⅓ avg 30.2%

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

0.20Best rating — vertigo 9–2

13–1Biggest win — inferno

5Longest win streak

7–11In matches decided by ≤2 rounds

8Overtime games

Map breakdown

anubisBest map · 89% over 9ancientWeakest map · 40% over 30

Map	Grade	Played	Record	Win rate	Avg rating
ancient	C	30	12–18	40%	0.00
inferno	S	21	14–7	67%	0.02
dust2	B	20	9–11	45%	-0.00
mirage	S	12	9–3	75%	0.03
anubis	S	9	8–1	89%	0.03
nuke	—	3	1–2	33%	-0.00
vertigo	—	2	2–0	100%	0.08
overpass	—	1	1–0	100%	0.18
poseidon	—	1	0–1	0%	0.04
train	—	1	1–0	100%	-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (40% over 30). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,562Matches

55%Win rate

1.13Avg K/D

79.7ADR

65%Headshot %

Clutches & streaks

37%1v1 clutch win

22%1v2 clutch win

11Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	641	54%	1.14	16.9
Ancient	619	53%	1.10	16.1
Dust2	506	54%	1.08	15.8
Anubis	492	58%	1.09	16.4
Inferno	199	64%	1.20	16.3
Vertigo	69	58%	1.05	15.0
Nuke	61	44%	0.92	14.7
Overpass	39	46%	0.99	15.3

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.

27.6%Headshot accuracy

33.1%Accuracy (enemy spotted)

37.2%Spray accuracy

77.1%Counter-strafing

11.4°Preaim

568msReaction time

26.3%T opening success

43.2%CT opening success

0.74Enemies flashed / flash

18.8%Flash assists

8.14HE damage / grenade

12.84Flashes / 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 26.2965% — 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 30 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
mirage	13–10	0.01	32%	28 Aug →
ancient	8–13	-0.10	26%	20 Aug →
anubis	5–13	0.02	25%	19 Aug →
anubis	13–3	0.06	22%	19 Aug →
dust2	13–10	0.05	32%	4 Aug →
dust2	4–13	0.01	24%	14 Jul →
inferno	8–8	-0.07	70%	7 Jul →
inferno	7–9	-0.09	18%	30 Jun →
inferno	8–8	-0.01	32%	30 Jun →
mirage	13–7	0.03	30%	26 Jun →
inferno	9–7	0.14	42%	20 Jun →
dust2	6–13	-0.03	26%	9 Jun →
inferno	9–4	0.10	46%	18 May →
overpass	9–5	0.18	44%	15 May →
poseidon	8–8	0.04	33%	15 May →
inferno	9–6	-0.00	28%	15 May →
inferno	9–3	0.11	20%	12 May →
dust2	13–8	0.00	24%	22 Apr →
inferno	13–5	-0.04	20%	2 Apr →
ancient	13–2	0.07	21%	1 Apr →
ancient	9–13	0.00	14%	31 Mar →
dust2	13–10	0.02	21%	26 Mar →
ancient	13–4	0.07	32%	18 Mar →
inferno	9–13	-0.06	30%	18 Mar →
anubis	13–7	0.00	45%	11 Mar →
mirage	9–13	0.01	36%	6 Mar →
ancient	13–9	0.04	20%	15 Feb →
dust2	13–7	-0.00	29%	15 Feb →
ancient	14–16	0.04	33%	14 Feb →
inferno	13–9	0.07	34%	14 Feb →
mirage	13–10	-0.02	31%	14 Feb →
nuke	11–13	-0.04	22%	9 Feb →
ancient	13–16	0.02	33%	5 Feb →
ancient	13–8	0.02	35%	24 Jan →
inferno	13–6	-0.02	15%	23 Jan →
ancient	4–13	-0.02	21%	3 Jan →
nuke	11–13	0.03	33%	30 Dec →
vertigo	9–7	-0.04	33%	28 Dec →
vertigo	9–2	0.20	42%	27 Dec →
inferno	10–13	0.05	19%	20 Dec →
nuke	13–9	0.00	40%	20 Dec →
ancient	4–13	-0.04	14%	20 Dec →
ancient	11–13	-0.03	31%	20 Dec →
inferno	9–13	-0.01	24%	20 Dec →
inferno	13–10	-0.00	38%	20 Dec →
inferno	9–1	0.12	47%	11 Dec →
inferno	9–3	0.09	33%	11 Dec →
ancient	5–13	-0.01	34%	21 Nov →
dust2	13–4	0.03	20%	8 Oct →
mirage	13–9	0.08	29%	29 Sept →
ancient	13–16	-0.02	42%	27 Sept →
dust2	10–13	-0.00	33%	25 Sept →
ancient	8–13	-0.08	28%	4 Sept →
ancient	7–13	-0.04	26%	21 Aug →
ancient	13–9	0.09	37%	16 Aug →
ancient	16–19	0.05	39%	9 Aug →
dust2	13–11	0.00	40%	9 Aug →
ancient	13–11	-0.02	30%	7 Aug →
ancient	13–9	0.05	38%	4 Aug →
inferno	13–10	0.05	28%	1 Aug →
ancient	13–11	0.01	31%	1 Aug →
mirage	10–13	0.07	20%	13 Jul →
anubis	13–9	0.04	27%	14 Jun →
ancient	23–25	-0.05	24%	21 May →
ancient	4–12	-0.03	42%	19 May →
dust2	13–9	-0.00	56%	17 May →
ancient	17–19	-0.03	21%	12 May →
dust2	11–13	-0.01	38%	4 May →
inferno	4–13	-0.04	25%	1 May →
dust2	4–13	-0.07	25%	18 Apr →
inferno	13–11	-0.02	29%	3 Apr →
mirage	13–6	0.10	41%	3 Apr →
mirage	13–8	-0.01	29%	27 Mar →
anubis	13–7	-0.03	17%	21 Mar →
dust2	11–13	0.01	31%	19 Mar →
anubis	13–9	0.04	19%	16 Mar →
ancient	13–2	0.03	13%	8 Mar →
anubis	13–6	0.05	27%	1 Mar →
mirage	13–7	0.08	20%	28 Feb →
ancient	5–13	-0.02	48%	22 Feb →
dust2	8–13	-0.01	21%	13 Feb →
anubis	13–8	0.03	50%	7 Feb →
dust2	7–13	0.02	25%	4 Feb →
ancient	13–5	-0.01	26%	28 Jan →
inferno	13–1	0.03	27%	18 Jan →
mirage	13–6	-0.01	41%	30 Dec →
dust2	17–19	-0.07	28%	18 Dec →
ancient	10–13	-0.04	34%	14 Dec →
train	13–10	-0.02	26%	15 Nov →
ancient	13–6	0.08	35%	30 Oct →
inferno	13–10	0.03	35%	22 Oct →
mirage	11–13	-0.02	38%	17 Oct →
mirage	13–8	-0.00	27%	23 Sept →
dust2	13–6	0.01	31%	20 Sept →
dust2	7–13	-0.05	41%	16 Sept →
ancient	10–13	0.02	38%	12 Sept →
dust2	16–14	-0.01	24%	8 Sept →
ancient	13–2	-0.04	39%	8 Sept →
dust2	8–13	0.03	39%	6 Sept →
anubis	13–6	0.03	41%	29 Aug →