kas =DD — CS2 Stats

IT76561198017529317[U:1:57263589]Steam profile ↗

5,343Tracked matches39%Win rate2020Tracked since

CSDB Rating6.2 SolidAggressive Rifler

Ladder ranks via Leetify

Performance scores

Aim82

Positioning62

Utility51

0–100 skill scores via Leetify.

Recent form

STEADY47–48–5Last 10047%Win rateLWLLWWWLWL

Last 10 vs previous 10: +0pp win rate · -0.03 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.2

Aggression9.2

Utility5.1

Positioning6.2

Opening Duels3.3

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 jL 92% playstyle similarity

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

Where you differ: lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 563ms 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

Aim8.2

Positioning6.2

Utility5.1

Mechanics7.3

Opening Duels3.3

Win Impact1.4

Composite 6.2/10 (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+0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time567ms−22ms

first ⅓ avg 589ms → last ⅓ avg 567ms

Headshot accuracy17.2%+1.0%

first ⅓ avg 16.2% → last ⅓ avg 17.2%

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

0.21Best rating — cache 9–0

13–0Biggest win — dust2

6Longest win streak

5–5In matches decided by ≤2 rounds

10Overtime games

Map breakdown

ancientBest map · 61% over 18mirageWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
ancient	A	18	11–7	61%	0.01
dust2	B	14	7–7	50%	0.00
mirage	D	13	4–9	31%	-0.02
cache	B	13	7–6	54%	0.03
inferno	D	12	4–8	33%	0.00
nuke	B	11	5–6	45%	0.00
anubis	B	8	4–4	50%	0.02
vertigo	—	4	1–3	25%	0.03
train	—	3	3–0	100%	-0.00
overpass	—	3	1–2	33%	0.06
shelter	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

5,885Matches

52%Win rate

1.10Avg K/D

82.9ADR

36%Headshot %

Clutches & streaks

36%1v1 clutch win

19%1v2 clutch win

12Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	518	54%	1.10	16.2
Mirage	290	47%	1.06	15.3
Anubis	258	55%	1.05	15.3
Nuke	238	58%	1.17	15.8
Dust2	201	49%	1.12	16.4
Overpass	131	56%	1.05	15.7
Inferno	97	49%	1.03	15.0
Vertigo	91	49%	1.10	17.3

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.

16.9%Headshot accuracy

38.8%Accuracy (enemy spotted)

41.5%Spray accuracy

82.7%Counter-strafing

9.1°Preaim

563msReaction time

39.2%T opening success

47.5%CT opening success

0.55Enemies flashed / flash

8.5%Flash assists

9.70HE damage / grenade

5.13Flashes / 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 39.205% — below the 40% mark we flag

Spend your practice time on Mirage

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

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	9–13	0.01	20%	6 Aug →
dust2	16–14	-0.08	11%	6 Aug →
inferno	9–13	0.04	19%	3 Aug →
ancient	7–13	0.10	13%	29 Jul →
mirage	16–13	-0.11	18%	29 Jul →
cache	13–1	0.11	13%	29 Jul →
dust2	13–10	-0.01	11%	29 Jul →
inferno	7–13	-0.01	14%	29 Jul →
mirage	13–5	0.01	31%	26 Jul →
dust2	14–16	0.04	17%	24 Jul →
vertigo	13–2	0.08	8%	22 Jul →
dust2	5–13	-0.07	14%	22 Jul →
ancient	13–1	0.03	24%	22 Jul →
cache	9–0	0.21	32%	22 Jul →
vertigo	9–13	0.05	22%	22 Jul →
dust2	10–13	0.04	17%	19 Jul →
dust2	13–8	0.10	10%	19 Jul →
ancient	13–6	0.08	22%	14 Jul →
dust2	7–13	-0.01	30%	12 Jul →
inferno	2–13	-0.05	26%	11 Jul →
cache	15–15	0.03	15%	9 Jul →
shelter	8–13	-0.05	16%	9 Jul →
ancient	13–1	0.02	27%	6 Jul →
dust2	1–5	-0.04	50%	6 Jul →
ancient	0–13	-0.07	0%	6 Jul →
nuke	15–15	0.00	16%	6 Jul →
mirage	10–13	-0.03	6%	3 Jul →
nuke	11–13	-0.01	14%	21 Jun →
ancient	9–13	-0.02	11%	15 Jun →
vertigo	8–13	-0.01	17%	15 Jun →
mirage	7–13	0.07	6%	15 Jun →
cache	13–11	0.05	12%	15 Jun →
nuke	4–13	-0.05	6%	15 Jun →
dust2	13–5	0.06	18%	12 Jun →
cache	6–13	-0.03	8%	11 Jun →
anubis	8–13	0.01	11%	11 Jun →
train	13–5	-0.05	11%	11 Jun →
nuke	12–12	0.03	14%	11 Jun →
cache	13–6	0.08	21%	9 Jun →
anubis	6–13	0.04	16%	8 Jun →
nuke	6–1	-0.03	27%	8 Jun →
mirage	6–13	-0.05	10%	8 Jun →
anubis	13–11	0.06	13%	8 Jun →
nuke	8–13	0.06	10%	7 Jun →
cache	6–13	-0.03	16%	7 Jun →
dust2	13–0	-0.00	0%	31 May →
mirage	10–13	0.01	25%	31 May →
inferno	7–9	0.01	23%	25 May →
nuke	13–7	0.04	12%	24 May →
ancient	10–13	-0.02	20%	23 May →
inferno	8–13	0.03	7%	23 May →
dust2	9–13	0.05	13%	22 May →
mirage	13–10	0.01	10%	21 May →
cache	6–2	-0.03	23%	17 May →
cache	10–13	-0.02	9%	17 May →
mirage	10–13	0.00	15%	17 May →
anubis	13–8	0.04	9%	15 May →
cache	13–3	0.02	25%	15 May →
ancient	4–13	-0.04	13%	15 May →
nuke	16–12	-0.01	21%	13 May →
anubis	6–13	-0.08	10%	13 May →
anubis	13–5	0.09	12%	10 May →
mirage	4–13	-0.03	13%	9 May →
ancient	13–4	-0.08	8%	7 May →
dust2	13–5	-0.02	19%	7 May →
nuke	13–10	-0.00	6%	7 May →
cache	5–13	-0.03	19%	7 May →
cache	10–13	0.04	16%	7 May →
inferno	16–12	0.07	16%	7 May →
ancient	13–3	0.01	11%	30 Apr →
cache	13–5	-0.01	22%	28 Apr →
train	13–2	0.03	17%	27 Apr →
dust2	13–4	-0.06	32%	26 Apr →
train	13–11	0.01	33%	25 Apr →
mirage	7–13	-0.03	7%	23 Apr →
vertigo	3–13	-0.02	17%	23 Apr →
anubis	15–15	0.05	29%	20 Apr →
mirage	10–13	-0.01	13%	20 Apr →
nuke	13–11	0.07	20%	20 Apr →
ancient	10–13	-0.01	11%	17 Apr →
inferno	13–8	0.00	15%	15 Apr →
ancient	16–12	0.03	17%	13 Apr →
ancient	13–8	0.02	10%	10 Apr →
ancient	13–7	0.03	17%	30 Mar →
nuke	2–13	-0.06	13%	19 Mar →
mirage	4–13	0.00	16%	19 Mar →
ancient	13–2	0.08	20%	19 Mar →
overpass	13–5	0.08	11%	19 Mar →
inferno	6–13	0.02	20%	19 Mar →
inferno	7–13	-0.05	14%	14 Mar →
ancient	14–16	0.02	10%	14 Mar →
overpass	11–13	0.00	7%	12 Mar →
overpass	12–12	0.09	12%	12 Mar →
inferno	5–13	0.06	17%	11 Mar →
inferno	13–8	-0.03	3%	10 Mar →
inferno	13–9	-0.03	8%	9 Mar →
ancient	13–6	0.02	10%	7 Mar →
ancient	13–10	0.01	24%	15 Feb →
anubis	13–10	-0.01	25%	11 Feb →
mirage	13–7	-0.07	24%	10 Feb →