evitageN — CS2 Stats

76561198010150373[U:1:49884645]✓ No bans

1,845Tracked matches55%Win rate2020Tracked since

CSDB Rating5.6 Solid

Premier CS Rating27,315Top 5% of 17,162 CSDB-tracked playersRed band · top ~1.9% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim56

Positioning48

Utility58

0–100 skill scores via Leetify.

Recent form

HOT56–38–6Last 10056%Win rateWWLWLWWWWT

Last 10 vs previous 10: +40pp win rate · +0.03 avg rating

Player DNA

Aim5.6

Aggression4.6

Utility5.8

Positioning4.8

Opening Duels0.4

Clutch3.2

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 85% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower opening-duel success; 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

T-side openings. Opening success drops from 44% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 617ms 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

Aim5.6

Positioning4.8

Utility5.8

Mechanics6.3

Opening Duels1.8

Win Impact6.7

Composite 5.6/10 (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 rating0.00+0.00

first ⅓ avg 0.00 → last ⅓ avg 0.00

Reaction time620ms+6ms

first ⅓ avg 614ms → last ⅓ avg 620ms

Headshot accuracy14.6%+1.0%

first ⅓ avg 13.6% → last ⅓ avg 14.6%

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

0.10Best rating — anubis 13–4

13–1Biggest win — inferno

7Longest win streak

W2Current streak

6–10In matches decided by ≤2 rounds

14Overtime games

Map breakdown

overpassBest map · 69% over 13anubisWeakest map · 46% over 24

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	27	16–11	59%	0.01
anubis	B	24	11–13	46%	-0.01
inferno	A	20	11–9	55%	-0.01
overpass	S	13	9–4	69%	0.01
mirage	A	9	5–4	56%	-0.01
ancient	—	4	2–2	50%	0.01
train	—	2	1–1	50%	-0.01
dust2	—	1	1–0	100%	0.08

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (46% over 24). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

935Matches

53%Win rate

0.97Avg K/D

71.1ADR

42%Headshot %

Clutches & streaks

36%1v1 clutch win

27%1v2 clutch win

11Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	127	68%	1.11	14.7
Inferno	124	50%	1.02	14.6
Anubis	62	48%	0.98	14.3
Overpass	57	60%	1.02	14.8
Vertigo	47	43%	0.96	14.6
Ancient	31	45%	0.89	14.7
Train	7	43%	0.81	12.4
Dust2	5	0%	0.85	13.8

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.

15.0%Headshot accuracy

33.5%Accuracy (enemy spotted)

37.9%Spray accuracy

78.1%Counter-strafing

11.4°Preaim

617msReaction time

19.5%T opening success

44.1%CT opening success

0.67Enemies flashed / flash

7.5%Flash assists

6.11HE damage / grenade

7.51Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.9922% — below the 15% mark we flag
Aim Training →
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 19.4618% — below the 40% mark we flag

Spend your practice time on Anubis

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

46% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
overpass	13–6	0.05	8%	27 Apr →
mirage	13–8	0.03	14%	27 Apr →
ancient	10–13	0.05	30%	27 Apr →
inferno	13–1	0.07	15%	27 Apr →
overpass	14–16	0.02	14%	26 Apr →
nuke	13–3	0.08	10%	26 Apr →
mirage	13–8	-0.09	5%	21 Apr →
mirage	13–3	0.04	17%	21 Apr →
ancient	13–10	-0.01	14%	21 Apr →
inferno	15–15	0.01	22%	21 Apr →
mirage	7–13	-0.04	16%	18 Apr →
overpass	14–16	-0.05	14%	18 Apr →
inferno	7–13	-0.02	18%	18 Apr →
anubis	13–10	0.02	14%	16 Apr →
inferno	13–9	-0.03	29%	16 Apr →
overpass	1–13	0.01	30%	13 Apr →
inferno	13–9	0.03	7%	13 Apr →
anubis	9–13	0.06	13%	10 Apr →
mirage	9–13	-0.03	20%	10 Apr →
nuke	4–13	-0.02	22%	4 Apr →
nuke	9–13	0.02	17%	4 Apr →
nuke	11–13	-0.01	7%	4 Apr →
anubis	8–13	-0.03	6%	4 Apr →
train	13–10	0.02	21%	1 Apr →
nuke	13–7	-0.03	17%	31 Mar →
inferno	13–8	-0.04	18%	30 Mar →
anubis	8–13	0.02	5%	30 Mar →
nuke	13–1	-0.02	5%	30 Mar →
nuke	13–8	0.08	18%	29 Mar →
inferno	13–4	-0.01	5%	29 Mar →
nuke	11–13	-0.05	7%	29 Mar →
inferno	13–4	0.05	15%	29 Mar →
nuke	8–13	-0.10	12%	25 Mar →
nuke	15–15	-0.03	10%	25 Mar →
nuke	13–8	-0.04	8%	24 Mar →
anubis	16–14	0.03	10%	24 Mar →
nuke	10–13	-0.01	6%	24 Mar →
overpass	13–5	0.02	28%	24 Mar →
nuke	13–8	-0.03	15%	23 Mar →
anubis	13–4	0.10	16%	23 Mar →
nuke	12–12	0.03	12%	23 Mar →
mirage	12–12	0.00	10%	22 Mar →
overpass	13–7	-0.04	13%	20 Mar →
overpass	13–3	0.01	11%	19 Mar →
anubis	13–6	-0.00	12%	19 Mar →
nuke	13–16	0.07	8%	19 Mar →
inferno	11–13	-0.02	23%	19 Mar →
mirage	16–12	-0.02	28%	19 Mar →
anubis	6–13	-0.05	11%	15 Mar →
anubis	2–9	-0.01	14%	15 Mar →
anubis	8–13	-0.05	8%	15 Mar →
overpass	13–11	0.03	18%	14 Mar →
inferno	7–13	-0.06	16%	9 Mar →
anubis	9–13	-0.03	10%	8 Mar →
nuke	13–3	0.06	11%	8 Mar →
anubis	16–14	-0.00	26%	8 Mar →
nuke	13–10	0.01	11%	7 Mar →
inferno	14–16	-0.03	22%	7 Mar →
nuke	13–5	0.08	9%	7 Mar →
nuke	13–10	0.03	22%	7 Mar →
anubis	4–13	-0.05	26%	7 Mar →
train	11–13	-0.05	16%	7 Mar →
mirage	13–8	0.04	10%	5 Mar →
anubis	13–4	0.01	28%	5 Mar →
inferno	8–13	-0.04	10%	3 Mar →
nuke	13–7	-0.02	13%	3 Mar →
inferno	13–1	0.03	31%	2 Mar →
nuke	13–6	-0.02	16%	2 Mar →
anubis	4–13	-0.05	7%	2 Mar →
overpass	7–13	-0.07	6%	1 Mar →
overpass	13–11	-0.00	12%	1 Mar →
inferno	15–15	-0.04	8%	1 Mar →
inferno	5–13	-0.04	11%	27 Feb →
anubis	13–7	-0.03	8%	27 Feb →
inferno	13–9	-0.02	23%	27 Feb →
anubis	13–11	0.02	16%	27 Feb →
overpass	13–10	0.04	8%	26 Feb →
anubis	13–7	0.01	16%	26 Feb →
inferno	13–11	-0.01	21%	25 Feb →
anubis	13–3	-0.01	22%	25 Feb →
anubis	12–12	0.03	17%	25 Feb →
inferno	13–9	-0.00	16%	24 Feb →
nuke	11–13	-0.00	16%	24 Feb →
nuke	13–3	0.03	16%	24 Feb →
nuke	13–16	-0.04	14%	24 Feb →
nuke	13–5	0.09	35%	24 Feb →
overpass	13–9	0.02	7%	23 Feb →
ancient	14–16	-0.01	4%	23 Feb →
anubis	7–13	-0.02	11%	23 Feb →
overpass	13–9	0.07	8%	23 Feb →
anubis	13–9	-0.02	14%	22 Feb →
ancient	13–3	0.01	14%	22 Feb →
inferno	13–16	-0.03	12%	22 Feb →
anubis	10–13	-0.10	8%	21 Feb →
nuke	13–4	0.09	10%	21 Feb →
nuke	13–5	-0.01	13%	21 Feb →
dust2	16–13	0.08	10%	20 Feb →
inferno	13–6	0.06	18%	20 Feb →
mirage	11–13	0.01	15%	20 Feb →
anubis	7–13	-0.02	17%	20 Feb →