Fin — CS2 Stats

76561198801128799[U:1:840863071]

1,011Tracked matches60%Win rate2020Tracked since

CSDB Rating4.9 DevelopingPassive Rifler

FaceitLevel 6 · 1,216 ELOTop 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim61

Positioning40

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY59–37–4Last 10059%Win rateLLWLLWLWLW

Last 10 vs previous 10: -50pp win rate · -0.04 avg rating

Player DNA

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

Aim6.1

Aggression1.8

Utility5.6

Positioning4.0

Opening Duels0.0

Clutch4.8

Strong CT-side openerEffective flashes

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 78% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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 36% on CT to 20% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 589ms 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

Aim6.1

Positioning4.0

Utility5.6

Mechanics6.9

Opening Duels0.7

Win Impact8.3

Composite 4.9/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.01

first ⅓ avg -0.02 → last ⅓ avg -0.03

Reaction time592ms−19ms

first ⅓ avg 611ms → last ⅓ avg 592ms

Headshot accuracy10.9%−2.1%

first ⅓ avg 13.0% → last ⅓ avg 10.9%

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

0.10Best rating — dust2 13–2

13–1Biggest win — mirage

9Longest win streak

L2Current streak

8–7In matches decided by ≤2 rounds

2Overtime games

Map breakdown

infernoBest map · 83% over 12dust2Weakest map · 46% over 13

Map	Grade	Played	Record	Win rate	Avg rating
cache	A	23	14–9	61%	-0.02
mirage	A	18	10–8	56%	-0.01
ancient	B	13	7–6	54%	-0.02
dust2	B	13	6–7	46%	-0.00
inferno	S	12	10–2	83%	-0.02
overpass	A	7	4–3	57%	-0.05
nuke	S	6	4–2	67%	-0.03
train	A	5	3–2	60%	-0.01
anubis	—	3	1–2	33%	-0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (46% over 13). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

225Matches

51%Win rate

0.77Avg K/D

67.2ADR

34%Headshot %

Clutches & streaks

44%1v1 clutch win

8%1v2 clutch win

6Longest win streak

Recent Faceit resultsWWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	15	60%	1.02	12.3
Dust2	8	25%	0.68	10.0
Train	7	57%	0.77	12.3
Nuke	7	86%	0.89	13.3
Inferno	7	29%	0.89	14.0
Ancient	3	67%	0.89	15.0
Overpass	1	100%	0.50	7.0

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.

10.7%Headshot accuracy

33.2%Accuracy (enemy spotted)

37.7%Spray accuracy

81.2%Counter-strafing

9.3°Preaim

589msReaction time

20.0%T opening success

35.9%CT opening success

0.71Enemies flashed / flash

4.1%Flash assists

6.04HE damage / grenade

7.99Flashes / 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 10.7051% — 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 19.9621% — below the 40% mark we flag

Spend your practice time on Dust 2

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 13 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	5–13	-0.09	10%	23 Aug →
ancient	11–13	-0.02	5%	20 Aug →
mirage	13–5	0.04	11%	20 Aug →
anubis	2–13	-0.08	10%	19 Aug →
nuke	6–13	-0.05	11%	19 Aug →
inferno	13–11	-0.08	6%	12 Aug →
dust2	10–13	-0.02	14%	12 Aug →
inferno	13–8	0.03	14%	3 Aug →
inferno	13–16	-0.05	16%	29 Jul →
cache	13–9	-0.05	11%	29 Jul →
anubis	13–3	-0.01	2%	29 Jul →
mirage	13–1	0.03	11%	29 Jul →
cache	13–7	0.05	12%	29 Jul →
inferno	13–8	0.01	15%	29 Jul →
ancient	13–1	0.04	11%	29 Jul →
cache	13–10	0.02	16%	27 Jul →
dust2	13–10	-0.03	7%	27 Jul →
cache	13–11	0.03	13%	27 Jul →
train	6–13	-0.04	14%	27 Jul →
nuke	13–11	-0.01	8%	26 Jul →
mirage	9–13	-0.04	16%	15 Jul →
ancient	11–13	-0.01	11%	15 Jul →
nuke	2–9	-0.15	4%	8 Jul →
mirage	13–4	0.02	12%	8 Jul →
cache	13–5	-0.04	6%	7 Jul →
cache	13–3	-0.05	0%	6 Jul →
ancient	8–13	-0.07	13%	27 Jun →
cache	13–8	-0.03	2%	27 Jun →
dust2	10–13	-0.05	18%	27 Jun →
mirage	11–13	0.01	10%	27 Jun →
dust2	13–7	0.04	9%	20 Jun →
overpass	0–9	-0.24	28%	20 Jun →
inferno	13–10	0.01	13%	18 Jun →
mirage	13–1	0.08	14%	18 Jun →
ancient	13–10	-0.01	11%	15 Jun →
cache	9–13	-0.02	17%	14 Jun →
nuke	13–2	0.06	20%	14 Jun →
train	8–13	-0.03	6%	14 Jun →
anubis	7–13	-0.01	7%	8 Jun →
cache	13–5	0.00	8%	8 Jun →
cache	13–10	-0.06	9%	3 Jun →
cache	3–13	0.01	18%	3 Jun →
ancient	13–9	-0.01	16%	17 May →
mirage	13–7	-0.01	9%	15 May →
ancient	13–4	0.01	4%	13 May →
mirage	13–10	-0.00	24%	13 May →
dust2	10–13	-0.03	13%	6 May →
ancient	13–8	-0.02	15%	6 May →
nuke	13–5	0.04	13%	5 May →
overpass	8–13	-0.07	6%	3 May →
overpass	3–1	-0.08	9%	3 May →
cache	4–13	-0.09	8%	3 May →
ancient	13–5	0.04	18%	3 May →
cache	10–13	-0.08	13%	3 May →
cache	13–11	0.05	16%	3 May →
cache	10–13	-0.07	19%	2 May →
overpass	13–5	0.01	13%	2 May →
cache	3–13	-0.03	15%	30 Apr →
cache	13–1	0.04	8%	30 Apr →
cache	13–8	0.09	13%	30 Apr →
inferno	13–9	-0.05	16%	29 Apr →
cache	6–13	-0.06	11%	29 Apr →
cache	13–8	-0.03	18%	29 Apr →
cache	13–5	-0.01	31%	29 Apr →
cache	11–13	-0.04	17%	28 Apr →
mirage	13–6	-0.01	17%	28 Apr →
dust2	12–12	0.01	17%	28 Apr →
ancient	5–13	-0.06	11%	24 Apr →
inferno	13–9	-0.01	13%	23 Apr →
mirage	13–11	-0.05	10%	19 Apr →
mirage	4–13	-0.01	19%	19 Apr →
overpass	13–6	0.06	12%	18 Apr →
train	13–8	0.01	12%	18 Apr →
inferno	13–7	0.04	12%	15 Apr →
dust2	5–0	0.07	6%	15 Apr →
mirage	12–12	-0.04	2%	12 Apr →
ancient	13–7	0.03	17%	12 Apr →
dust2	8–13	0.03	26%	11 Apr →
mirage	13–6	-0.01	14%	8 Apr →
dust2	13–2	0.10	15%	7 Apr →
nuke	13–10	-0.06	4%	7 Apr →
mirage	3–13	-0.07	13%	7 Apr →
mirage	12–12	-0.02	24%	30 Mar →
dust2	13–2	-0.03	16%	29 Mar →
inferno	13–11	-0.04	24%	25 Mar →
train	13–9	-0.02	12%	25 Mar →
dust2	13–5	0.03	20%	24 Mar →
inferno	13–6	-0.03	15%	16 Mar →
inferno	13–10	-0.02	26%	14 Mar →
dust2	12–12	-0.06	12%	13 Mar →
overpass	6–13	-0.04	14%	13 Mar →
mirage	3–13	-0.06	12%	6 Mar →
ancient	14–16	-0.07	8%	5 Mar →
inferno	11–13	-0.08	6%	25 Feb →
overpass	13–9	-0.02	17%	25 Feb →
train	13–9	0.01	9%	23 Feb →
mirage	11–13	-0.08	7%	18 Feb →
dust2	6–13	-0.07	5%	14 Feb →
ancient	9–13	-0.04	8%	11 Feb →
mirage	13–11	-0.01	8%	11 Feb →