kORNMAALER — CS2 Stats

DK76561198008619351[U:1:48353623]Steam profile ↗✓ No bans

1,304Tracked matches53%Win rate2020Tracked since

CSDB Rating5.3 DevelopingPassive Rifler

FaceitLevel 10 · 2,471 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim60

Positioning53

Utility63

0–100 skill scores via Leetify.

Recent form

STEADY44–55–1Last 10044%Win rateLWWLLWWLWW

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

Player DNA

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

Aim6.0

Aggression4.2

Utility6.3

Positioning5.3

Opening Duels1.3

Clutch3.6

Strong 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 NiKo 89% playstyle similarity

Most alike: utility contribution, 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

Areas to improve

T-side openings. Opening success drops from 47% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 587ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim6.0

Positioning5.3

Utility6.3

Mechanics4.4

Opening Duels2.1

Win Impact6.1

Composite 5.3/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.00

first ⅓ avg 0.02 → last ⅓ avg 0.02

Reaction time595ms+32ms

first ⅓ avg 563ms → last ⅓ avg 595ms

Headshot accuracy17.9%+0.8%

first ⅓ avg 17.1% → last ⅓ avg 17.9%

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

0.15Best rating — dust2 13–7

13–1Biggest win — ancient

4Longest win streak

7–8In matches decided by ≤2 rounds

11Overtime games

Map breakdown

overpassBest map · 67% over 12ancientWeakest map · 33% over 12

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	28	11–17	39%	0.02
anubis	B	19	10–9	53%	0.03
dust2	B	17	8–9	47%	0.01
ancient	D	12	4–8	33%	0.02
overpass	S	12	8–4	67%	0.02
nuke	C	5	2–3	40%	0.01
mirage	—	4	0–4	0%	0.03
sanctum	—	1	1–0	100%	0.14
poseidon	—	1	0–1	0%	-0.06
train	—	1	0–1	0%	0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,571Matches

51%Win rate

1.23Avg K/D

88.1ADR

41%Headshot %

Clutches & streaks

38%1v1 clutch win

27%1v2 clutch win

13Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	137	55%	1.29	16.6
Ancient	120	49%	1.21	18.3
Anubis	75	45%	1.25	17.9
Dust2	66	45%	1.20	16.6
Train	57	70%	1.42	18.2
Overpass	56	54%	1.28	18.0
Nuke	55	53%	1.25	17.1
Mirage	28	32%	1.01	15.4

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.

17.9%Headshot accuracy

34.1%Accuracy (enemy spotted)

39.4%Spray accuracy

69.8%Counter-strafing

10.7°Preaim

587msReaction time

23.8%T opening success

46.9%CT opening success

0.52Enemies flashed / flash

8.3%Flash assists

12.06HE damage / grenade

10.45Flashes / 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 23.831% — 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.

33% win rate across 12 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	7–13	-0.04	11%	16 Mar →
ancient	13–1	0.06	17%	16 Mar →
overpass	13–7	-0.01	17%	15 Mar →
inferno	7–13	0.01	20%	15 Mar →
ancient	10–13	0.08	18%	15 Mar →
inferno	13–11	0.02	19%	14 Mar →
dust2	16–12	0.00	11%	13 Mar →
inferno	9–13	0.02	16%	13 Mar →
ancient	13–8	0.05	18%	13 Mar →
anubis	13–11	0.01	20%	13 Mar →
inferno	2–9	-0.04	23%	13 Mar →
inferno	16–13	0.04	28%	13 Mar →
ancient	13–8	0.01	14%	12 Mar →
inferno	13–8	0.03	10%	12 Mar →
dust2	11–13	-0.03	20%	12 Mar →
anubis	13–7	0.10	23%	12 Mar →
overpass	13–11	0.06	16%	10 Mar →
anubis	13–2	0.08	19%	10 Mar →
dust2	13–10	-0.02	20%	10 Mar →
ancient	8–13	-0.01	19%	10 Mar →
sanctum	9–4	0.14	11%	10 Mar →
poseidon	5–9	-0.06	20%	10 Mar →
inferno	9–13	0.00	22%	9 Mar →
dust2	13–11	-0.00	15%	9 Mar →
ancient	8–13	-0.01	30%	9 Mar →
anubis	13–9	0.07	15%	9 Mar →
overpass	11–13	-0.01	22%	8 Mar →
anubis	11–13	0.08	14%	8 Mar →
inferno	11–13	0.03	17%	1 Mar →
mirage	7–13	0.01	18%	28 Feb →
dust2	16–14	0.04	14%	28 Feb →
inferno	9–13	0.03	15%	28 Feb →
anubis	3–13	-0.07	19%	28 Feb →
inferno	3–13	-0.02	12%	28 Feb →
ancient	6–13	0.02	23%	28 Feb →
dust2	6–5	0.08	27%	28 Feb →
ancient	9–13	-0.01	9%	28 Feb →
overpass	13–8	0.02	26%	28 Feb →
inferno	10–13	0.07	28%	28 Feb →
dust2	4–13	0.01	9%	28 Feb →
anubis	8–13	0.02	18%	28 Feb →
mirage	9–13	0.03	15%	28 Feb →
overpass	13–4	0.05	11%	28 Feb →
inferno	10–13	0.04	17%	28 Feb →
nuke	6–13	-0.08	8%	27 Feb →
ancient	13–4	0.08	20%	27 Feb →
nuke	7–13	0.01	23%	27 Feb →
inferno	8–13	-0.03	16%	27 Feb →
inferno	13–8	0.06	16%	27 Feb →
mirage	5–13	0.07	27%	27 Feb →
nuke	13–5	0.05	20%	27 Feb →
overpass	13–3	0.11	13%	27 Feb →
anubis	10–13	0.03	20%	27 Feb →
ancient	16–19	0.03	12%	27 Feb →
anubis	13–7	0.04	21%	25 Feb →
anubis	13–16	-0.03	24%	25 Feb →
dust2	9–13	-0.04	23%	23 Feb →
inferno	8–13	-0.06	15%	23 Feb →
anubis	11–13	0.04	15%	18 Feb →
overpass	13–10	-0.01	20%	17 Feb →
inferno	13–9	0.04	19%	17 Feb →
overpass	13–6	0.01	17%	16 Feb →
inferno	3–13	-0.07	19%	16 Feb →
mirage	13–16	0.01	18%	16 Feb →
anubis	13–11	0.02	11%	12 Feb →
dust2	12–12	0.05	25%	12 Feb →
inferno	8–13	-0.09	14%	11 Feb →
dust2	13–6	0.04	14%	11 Feb →
inferno	7–13	-0.02	11%	11 Feb →
inferno	10–0	0.01	21%	10 Feb →
dust2	13–8	-0.01	13%	10 Feb →
nuke	13–7	0.02	13%	10 Feb →
dust2	2–13	-0.05	21%	9 Feb →
anubis	16–13	0.02	14%	9 Feb →
nuke	11–13	0.02	19%	6 Feb →
dust2	1–13	-0.07	9%	6 Feb →
inferno	13–9	-0.01	15%	6 Feb →
overpass	9–13	-0.03	16%	6 Feb →
dust2	9–13	0.01	15%	4 Feb →
inferno	13–5	0.07	13%	4 Feb →
overpass	13–8	0.03	22%	4 Feb →
ancient	2–13	-0.04	21%	2 Feb →
inferno	13–6	0.12	30%	2 Feb →
dust2	16–13	-0.01	24%	30 Jan →
ancient	17–19	-0.05	16%	30 Jan →
anubis	3–13	-0.07	11%	30 Jan →
overpass	9–13	0.04	11%	30 Jan →
anubis	9–13	0.03	24%	28 Jan →
inferno	13–16	0.02	19%	27 Jan →
inferno	6–13	0.01	18%	23 Jan →
inferno	3–13	0.09	8%	23 Jan →
dust2	13–7	0.15	17%	23 Jan →
anubis	13–10	0.12	15%	23 Jan →
overpass	10–13	-0.04	20%	19 Jan →
inferno	13–6	0.07	20%	19 Jan →
anubis	13–9	-0.00	10%	16 Jan →
anubis	22–19	0.03	18%	16 Jan →
dust2	9–13	-0.02	27%	16 Jan →
inferno	13–11	0.04	16%	14 Jan →
train	7–13	0.02	24%	14 Jan →