kas — CS2 Stats

76561198886496332[U:1:926230604]Steam profile ↗

5,231Tracked matches50%Win rate2020Tracked since

CSDB Rating5.9 SolidHybrid Rifler

FaceitLevel 10 · 2,913 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim62

Positioning55

Utility69

0–100 skill scores via Leetify.

Recent form

STEADY42–56–2Last 10042%Win rateLLWLWWLWWW

Last 10 vs previous 10: +0pp win rate · -0.00 avg rating

Player DNA

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

Aim6.2

Aggression6.5

Utility6.9

Positioning5.5

Opening Duels3.4

Clutch4.0

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 Twistzz 90% playstyle similarity

Most alike: positioning profile, 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 55% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 583ms 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

Aim6.2

Positioning5.5

Utility6.9

Mechanics6.1

Opening Duels3.4

Win Impact5.0

Composite 5.9/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time581ms+31ms

first ⅓ avg 550ms → last ⅓ avg 581ms

Headshot accuracy20.6%+1.3%

first ⅓ avg 19.3% → last ⅓ avg 20.6%

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

0.22Best rating — inferno 9–4

13–3Biggest win — ancient

7Longest win streak

L2Current streak

9–7In matches decided by ≤2 rounds

13Overtime games

Map breakdown

overpassBest map · 67% over 6anubisWeakest map · 17% over 12

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	16	9–7	56%	0.02
ancient	C	16	7–9	44%	-0.01
mirage	C	16	7–9	44%	0.02
inferno	B	15	7–8	47%	0.04
anubis	D	12	2–10	17%	-0.02
overpass	S	6	4–2	67%	-0.01
dust2	C	5	2–3	40%	-0.00
cache	—	4	1–3	25%	0.04
train	—	4	1–3	25%	-0.01
grail	—	2	1–1	50%	0.04
jura	—	2	1–1	50%	0.06
vertigo	—	1	0–1	0%	0.19
agency	—	1	0–1	0%	-0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6,028Matches

51%Win rate

1.13Avg K/D

86.0ADR

49%Headshot %

Clutches & streaks

40%1v1 clutch win

23%1v2 clutch win

11Longest win streak

Recent Faceit resultsWWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	641	48%	1.17	17.2
Anubis	478	54%	1.22	17.3
Ancient	336	47%	1.12	16.4
Nuke	270	54%	1.16	16.9
Inferno	213	54%	1.26	17.0
Dust2	164	46%	1.04	15.4
Train	116	54%	1.25	17.0
Vertigo	73	56%	1.17	16.2

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.

21.1%Headshot accuracy

32.0%Accuracy (enemy spotted)

31.6%Spray accuracy

77.3%Counter-strafing

10.6°Preaim

583msReaction time

31.8%T opening success

55.3%CT opening success

0.66Enemies flashed / flash

9.4%Flash assists

9.64HE damage / grenade

14.04Flashes / 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 31.8385% — 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.

17% win rate across 12 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
cache	10–13	0.02	13%	19 Aug →
nuke	8–13	-0.03	26%	17 Aug →
inferno	19–16	0.03	23%	16 Aug →
anubis	5–13	-0.07	17%	13 Aug →
nuke	13–10	0.01	32%	7 Aug →
nuke	13–4	0.09	30%	7 Aug →
anubis	7–13	-0.05	18%	7 Aug →
cache	13–8	0.07	38%	5 Aug →
inferno	13–7	0.06	30%	31 Jul →
ancient	13–9	0.04	18%	31 Jul →
inferno	13–6	0.05	27%	13 Jun →
ancient	13–8	0.04	17%	13 Jun →
anubis	13–11	-0.00	20%	13 Jun →
nuke	13–9	0.07	16%	13 Jun →
mirage	11–13	-0.03	17%	25 May →
anubis	8–13	-0.00	28%	18 May →
cache	8–13	-0.02	25%	12 May →
nuke	16–12	0.03	22%	6 May →
nuke	13–11	0.02	12%	4 May →
cache	10–13	0.07	26%	4 May →
mirage	6–13	-0.01	14%	28 Apr →
mirage	13–10	0.05	29%	14 Apr →
overpass	13–11	-0.02	20%	12 Mar →
anubis	9–13	-0.07	19%	1 Feb →
nuke	2–13	0.04	16%	19 Jan →
anubis	7–13	0.05	22%	18 Jan →
inferno	3–13	-0.04	4%	13 Jan →
mirage	10–13	0.02	14%	4 Jan →
dust2	13–9	0.02	20%	4 Jan →
train	5–13	-0.04	11%	26 Dec →
mirage	13–16	-0.04	10%	20 Dec →
mirage	13–5	0.01	25%	19 Dec →
dust2	13–11	-0.01	18%	19 Dec →
mirage	13–11	0.01	12%	16 Dec →
dust2	9–13	-0.04	15%	13 Dec →
mirage	12–16	0.15	27%	7 Dec →
inferno	8–13	-0.07	28%	28 Nov →
ancient	13–4	0.01	22%	23 Nov →
dust2	6–13	-0.04	19%	18 Nov →
nuke	13–7	0.02	19%	18 Nov →
overpass	13–6	-0.02	15%	17 Nov →
inferno	9–13	0.01	28%	17 Nov →
mirage	3–13	0.03	13%	16 Nov →
overpass	9–13	-0.00	12%	11 Nov →
ancient	9–13	-0.06	19%	7 Nov →
ancient	13–5	-0.03	21%	7 Nov →
overpass	13–4	-0.06	12%	31 Oct →
inferno	13–11	0.04	18%	19 Oct →
ancient	13–3	-0.02	22%	16 Oct →
ancient	3–13	-0.02	26%	15 Oct →
inferno	10–13	0.05	12%	15 Oct →
mirage	6–13	-0.04	11%	15 Oct →
mirage	13–6	0.05	25%	5 Oct →
mirage	13–11	0.10	15%	5 Oct →
overpass	13–10	0.03	15%	1 Oct →
ancient	11–13	0.02	25%	1 Oct →
mirage	13–4	0.04	30%	1 Oct →
nuke	5–12	-0.04	25%	1 Oct →
inferno	11–13	0.03	16%	30 Sept →
ancient	20–22	-0.03	15%	30 Sept →
nuke	13–4	0.10	17%	30 Sept →
inferno	9–4	0.22	50%	25 Sept →
ancient	3–13	-0.04	20%	23 Sept →
ancient	5–13	-0.04	24%	20 Sept →
inferno	10–13	0.16	22%	18 Sept →
nuke	16–13	-0.02	21%	18 Sept →
overpass	14–16	0.02	21%	15 Sept →
nuke	22–19	0.03	19%	15 Sept →
inferno	16–14	0.01	20%	15 Sept →
ancient	13–10	-0.00	24%	14 Sept →
ancient	1–13	-0.06	24%	7 Sept →
nuke	5–13	-0.03	17%	29 Aug →
mirage	8–13	0.03	26%	28 Aug →
inferno	13–9	0.01	20%	22 Aug →
mirage	19–15	0.02	19%	18 Aug →
vertigo	6–13	0.19	25%	8 Aug →
ancient	2–13	0.04	36%	8 Aug →
nuke	8–13	-0.02	19%	7 Aug →
ancient	13–11	-0.03	17%	7 Aug →
grail	12–12	0.03	20%	6 Jul →
grail	13–3	0.06	18%	6 Jul →
inferno	9–13	0.01	16%	3 Jul →
ancient	10–13	0.07	19%	3 Jul →
mirage	4–13	-0.03	20%	27 Jun →
train	13–3	0.07	17%	13 Jun →
anubis	14–16	0.01	19%	10 Jun →
anubis	10–13	0.01	19%	10 Jun →
jura	6–0	0.14	14%	7 Jun →
jura	10–13	-0.02	16%	7 Jun →
anubis	8–13	0.00	22%	5 Jun →
anubis	13–5	-0.05	11%	5 Jun →
nuke	10–13	0.06	13%	2 Jun →
anubis	6–13	-0.06	12%	2 Jun →
nuke	11–13	0.02	11%	31 May →
dust2	13–16	0.07	30%	31 May →
agency	12–12	-0.00	28%	26 May →
anubis	12–16	0.01	15%	25 May →
train	5–13	0.03	26%	23 May →
train	0–5	-0.09	0%	23 May →
inferno	10–13	0.02	22%	21 May →