itsKakuta0 — CS2 Stats

76561198070305383[U:1:110039655]

474Tracked matches40%Win rate2020Tracked since

4,454Hours in CS9Hrs last 2 wks

CSDB Rating6.1 SolidAggressive Rifler

Premier CS Rating14,588Blue band · top ~30.6% of ranked players (population est.)

CSDB Leaderboard#10273 of 15538 tracked

FaceitLevel 7 · 1,419 ELOTop 42.3% of ranked FACEIT players

WingmanMaster Guardian Elite

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning52

Utility60

0–100 skill scores via Leetify.

Recent form

STEADY42–54–4Last 10042%Win rateWLWLLLWWLW

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

Player DNA

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

Aim8.6

Aggression7.3

Utility6.0

Positioning5.2

Opening Duels3.2

Clutch4.0

Sharp aimerExcellent counter-strafing

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 b1t 93% playstyle similarity

Most alike: opening-duel success, 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

Strengths

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.

Reaction time. 594ms 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

Aim8.6

Positioning5.2

Utility6.0

Mechanics9.2

Opening Duels3.2

Win Impact1.7

Composite 6.1/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00−0.00

first ⅓ avg -0.00 → last ⅓ avg -0.00

Reaction time597ms−8ms

first ⅓ avg 605ms → last ⅓ avg 597ms

Headshot accuracy22.3%+1.0%

first ⅓ avg 21.3% → last ⅓ avg 22.3%

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

0.17Best rating — inferno 9–1

13–1Biggest win — train

3Longest win streak

7–12In matches decided by ≤2 rounds

8Overtime games

Map breakdown

overpassBest map · 60% over 5infernoWeakest map · 39% over 23

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	32	13–19	41%	-0.01
inferno	C	23	9–14	39%	0.02
mirage	C	19	8–11	42%	0.02
ancient	C	7	3–4	43%	-0.01
overpass	A	5	3–2	60%	-0.01
anubis	—	4	1–3	25%	0.00
nuke	—	3	2–1	67%	-0.01
cache	—	3	1–2	33%	-0.02
train	—	3	1–2	33%	0.05
vertigo	—	1	1–0	100%	0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (39% over 23). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

172,922Lifetime kills

1.04K/D

5,854Matches

48.4%Match win rate · Top 50% of tracked players

47.6%Headshot % · Top 50% of tracked players

18.7%Shot accuracy · Top 10% of tracked players

28,665MVPs

3,219Hours (in match)

4,388Bombs planted

3,201Bombs defused

Most-used weapons

AK-4762,530

M4A4 / M4A1-S30,831

AWP30,284

P2000 / USP-S12,926

Glock-188,159

Desert Eagle7,582

SG 5532,538

Galil AR1,804

FAMAS1,730

AUG1,539

Lifetime map wins

21,720dust2

14,459inferno

7,722train

5,675vertigo

4,055nuke

898cbble

161lake

76office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

364Matches

55%Win rate

1.41Avg K/D

71.1ADR

39%Headshot %

Clutches & streaks

40%1v1 clutch win

26%1v2 clutch win

8Longest win streak

Recent Faceit resultsWLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	13	69%	1.32	18.3
Inferno	7	43%	0.98	12.0
Overpass	4	75%	0.90	14.0
Mirage	4	75%	1.04	16.8
Nuke	3	100%	1.00	14.0
Ancient	2	50%	0.65	10.0

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.

22.1%Headshot accuracy

35.8%Accuracy (enemy spotted)

38.6%Spray accuracy

91.5%Counter-strafing

7.9°Preaim

594msReaction time

39.4%T opening success

46.1%CT opening success

0.53Enemies flashed / flash

6.1%Flash assists

7.99HE damage / grenade

16.10Flashes / 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 39.4076% — below the 40% mark we flag

Spend your practice time on Inferno

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

39% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–8	-0.02	15%	28 Aug →
anubis	11–13	0.05	24%	28 Aug →
mirage	13–6	-0.01	28%	28 Aug →
inferno	11–13	0.03	17%	26 Aug →
inferno	11–13	0.04	20%	25 Aug →
nuke	5–13	-0.02	19%	25 Aug →
inferno	9–1	0.17	33%	25 Aug →
dust2	16–14	0.04	19%	16 Jul →
ancient	6–13	-0.12	25%	10 Jul →
dust2	13–8	-0.09	29%	10 Jul →
inferno	13–5	0.00	22%	9 Jul →
cache	14–16	0.01	14%	9 Jul →
dust2	13–5	0.01	29%	9 Jul →
cache	4–13	-0.03	23%	7 Jul →
mirage	13–8	0.05	17%	5 Jul →
nuke	13–3	0.00	23%	5 Jul →
dust2	10–13	-0.01	25%	4 Jul →
dust2	10–13	0.00	23%	23 Jun →
mirage	13–8	0.02	32%	19 Jun →
dust2	6–13	-0.02	35%	19 Jun →
overpass	14–16	-0.00	22%	17 Jun →
inferno	6–13	-0.08	27%	17 Jun →
mirage	11–13	-0.01	22%	16 Jun →
dust2	8–13	-0.00	29%	15 Jun →
anubis	2–13	-0.06	15%	5 May →
dust2	13–16	-0.03	15%	5 May →
cache	13–11	-0.05	14%	29 Apr →
dust2	13–10	0.04	27%	22 Apr →
mirage	13–10	0.02	18%	21 Apr →
inferno	3–13	-0.04	12%	20 Apr →
dust2	8–13	-0.03	33%	20 Apr →
anubis	7–13	0.04	14%	10 Apr →
dust2	5–13	0.05	19%	10 Apr →
overpass	9–13	0.02	28%	25 Mar →
dust2	13–7	0.05	25%	11 Feb →
dust2	6–13	-0.00	32%	11 Feb →
dust2	4–13	-0.04	18%	11 Feb →
inferno	13–10	0.05	23%	11 Feb →
dust2	13–16	0.01	21%	4 Feb →
inferno	13–11	0.13	30%	3 Feb →
overpass	13–6	-0.06	19%	19 Jan →
nuke	13–11	-0.02	40%	18 Jan →
mirage	11–13	0.01	22%	31 Dec →
inferno	3–13	0.00	29%	31 Dec →
train	13–1	-0.01	17%	31 Dec →
mirage	10–13	0.06	20%	28 Dec →
mirage	13–10	0.09	26%	28 Dec →
inferno	13–11	-0.02	12%	21 Dec →
dust2	13–7	0.01	30%	21 Dec →
mirage	12–12	0.10	38%	16 Dec →
dust2	13–11	0.04	33%	13 Dec →
inferno	13–11	0.05	26%	10 Dec →
ancient	13–5	0.07	34%	10 Dec →
inferno	8–13	0.02	28%	8 Dec →
dust2	10–13	-0.03	45%	8 Dec →
dust2	12–1	0.10	38%	8 Dec →
dust2	13–10	0.01	52%	4 Dec →
train	4–13	0.06	25%	4 Dec →
inferno	13–6	0.03	37%	1 Dec →
mirage	13–3	0.10	39%	1 Dec →
ancient	9–13	-0.04	8%	30 Nov →
dust2	7–13	-0.03	20%	30 Nov →
dust2	8–13	-0.06	36%	30 Nov →
overpass	13–6	-0.03	30%	29 Nov →
mirage	13–5	0.10	24%	20 Nov →
overpass	13–9	0.03	36%	19 Nov →
inferno	10–13	-0.06	12%	18 Nov →
ancient	13–9	0.04	21%	18 Nov →
mirage	11–13	-0.01	24%	18 Nov →
mirage	6–13	-0.01	11%	17 Nov →
dust2	13–9	0.00	35%	15 Nov →
inferno	6–13	-0.04	14%	13 Nov →
inferno	13–7	0.05	17%	9 Nov →
mirage	5–13	0.06	20%	9 Nov →
dust2	13–2	-0.01	17%	9 Nov →
inferno	11–13	0.02	22%	7 Nov →
inferno	13–16	-0.02	16%	5 Nov →
mirage	5–13	-0.03	38%	5 Nov →
inferno	13–7	0.08	15%	4 Nov →
inferno	9–13	0.05	25%	30 Oct →
ancient	8–13	0.00	14%	28 Oct →
dust2	11–13	-0.04	25%	26 Oct →
dust2	13–8	-0.01	26%	26 Oct →
dust2	7–13	-0.03	4%	26 Oct →
dust2	13–2	-0.02	25%	26 Oct →
inferno	9–13	0.02	22%	25 Oct →
dust2	8–13	0.07	15%	25 Oct →
mirage	9–13	-0.07	12%	24 Oct →
ancient	13–7	-0.02	22%	23 Oct →
mirage	15–15	-0.02	45%	23 Oct →
mirage	13–5	0.02	19%	23 Oct →
train	12–12	0.09	22%	22 Oct →
ancient	7–13	-0.01	24%	22 Oct →
vertigo	13–6	0.05	21%	22 Oct →
dust2	1–13	-0.10	20%	22 Oct →
inferno	11–13	-0.02	26%	22 Oct →
dust2	2–13	-0.07	33%	21 Oct →
dust2	4–13	-0.09	14%	21 Oct →
inferno	11–13	0.03	21%	19 Oct →
mirage	15–15	-0.03	17%	19 Oct →