kotoamatsukami — CS2 Stats

TT76561199190988235[U:1:1230722507]Steam profile ↗

1,409Tracked matches60%Win rate2021Tracked since

CSDB Rating6.8 SolidHybrid Rifler

FaceitLevel 10 · 2,549 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning54

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY46–53–1Last 10046%Win rateWLLWLWWWLL

Last 10 vs previous 10: -20pp win rate · -0.02 avg rating

Player DNA

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

Aim8.6

Aggression5.8

Utility4.8

Positioning5.4

Opening Duels2.5

Clutch3.0

Sharp aimerStrong 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 92% playstyle similarity

Most alike: opening-duel success, positioning profile.

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

Strengths

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

Areas to improve

Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.

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

T-side openings. Opening success drops from 58% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

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

Positioning5.4

Utility4.8

Mechanics7.1

Opening Duels3.5

Win Impact8.3

Composite 6.8/10 (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 time537ms−60ms

first ⅓ avg 597ms → last ⅓ avg 537ms

Headshot accuracy24.9%−1.7%

first ⅓ avg 26.6% → last ⅓ avg 24.9%

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

0.16Best rating — ancient 13–1

13–1Biggest win — ancient

5Longest win streak

9–12In matches decided by ≤2 rounds

11Overtime games

Map breakdown

nukeBest map · 57% over 7infernoWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	26	14–12	54%	0.02
dust2	C	25	10–15	40%	0.00
ancient	B	17	8–9	47%	0.01
anubis	B	15	8–7	53%	0.01
inferno	D	8	2–6	25%	-0.02
nuke	A	7	4–3	57%	0.00
cache	—	1	0–1	0%	-0.07
train	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,712Matches

54%Win rate

1.23Avg K/D

90.7ADR

59%Headshot %

Clutches & streaks

35%1v1 clutch win

26%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	491	54%	1.23	19.6
Dust2	375	53%	1.26	18.9
Ancient	305	51%	1.22	18.9
Anubis	173	54%	1.17	18.2
Inferno	128	59%	1.32	19.1
Nuke	106	51%	1.15	18.2
Train	20	40%	1.08	18.6
Vertigo	16	62%	1.60	20.0

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.

25.3%Headshot accuracy

35.4%Accuracy (enemy spotted)

40.8%Spray accuracy

82.1%Counter-strafing

9.0°Preaim

547msReaction time

22.5%T opening success

57.9%CT opening success

0.47Enemies flashed / flash

6.1%Flash assists

6.62HE damage / grenade

7.60Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4661 — below the 0.5 mark we flag
Grenade Lineups →
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 22.4665% — 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.

25% win rate across 8 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
ancient	13–10	0.01	17%	21 Aug →
ancient	9–13	-0.00	23%	21 Aug →
mirage	6–13	-0.05	24%	17 Aug →
mirage	13–11	-0.00	29%	16 Aug →
anubis	9–13	0.03	30%	15 Aug →
ancient	13–7	0.05	35%	15 Aug →
anubis	16–13	-0.01	23%	14 Aug →
dust2	13–3	0.01	22%	13 Aug →
cache	4–13	-0.07	26%	12 Aug →
dust2	10–13	0.02	29%	25 Jul →
ancient	13–1	0.16	26%	25 Jul →
ancient	9–13	-0.06	26%	24 Jul →
dust2	13–6	0.03	24%	24 Jul →
anubis	8–13	-0.01	16%	21 Jul →
anubis	13–7	0.04	18%	21 Jul →
dust2	13–9	-0.02	27%	12 Jul →
mirage	13–11	-0.05	24%	12 Jul →
mirage	13–7	0.08	33%	11 Jul →
nuke	16–14	0.05	30%	10 Jul →
dust2	14–16	-0.02	24%	8 Jul →
anubis	10–13	-0.01	47%	6 Jul →
anubis	16–14	0.08	31%	4 Jul →
ancient	9–13	-0.00	24%	3 Jul →
mirage	13–11	0.10	14%	2 Jul →
dust2	13–10	0.00	25%	2 Jul →
dust2	8–13	0.00	17%	2 Jul →
mirage	11–13	0.05	19%	1 Jul →
mirage	13–9	-0.01	19%	1 Jul →
anubis	13–6	-0.02	26%	1 Jul →
anubis	13–5	0.01	27%	1 Jul →
mirage	13–9	0.01	25%	29 Jun →
mirage	13–5	0.03	21%	27 Jun →
ancient	11–13	-0.01	19%	17 Jun →
dust2	13–1	0.13	29%	17 Jun →
mirage	7–13	-0.03	19%	13 Jun →
mirage	4–13	-0.03	28%	9 Jun →
ancient	13–6	0.01	30%	7 Jun →
mirage	10–13	0.03	24%	3 Jun →
anubis	13–7	0.01	16%	2 Jun →
mirage	7–13	-0.01	22%	1 Jun →
anubis	11–13	-0.03	19%	29 May →
mirage	13–7	0.01	16%	28 May →
dust2	13–11	-0.08	21%	25 May →
ancient	9–13	-0.05	18%	24 May →
inferno	11–13	-0.03	27%	23 May →
nuke	11–13	0.00	25%	17 May →
dust2	10–13	-0.07	19%	7 Mar →
ancient	16–13	0.04	20%	2 Mar →
dust2	13–11	0.00	19%	28 Feb →
nuke	13–4	0.04	29%	27 Feb →
anubis	10–13	-0.03	20%	26 Feb →
dust2	10–13	-0.05	9%	19 Feb →
mirage	10–13	-0.00	25%	28 Nov →
dust2	10–13	-0.08	0%	22 Nov →
ancient	13–6	-0.05	19%	21 Nov →
dust2	8–13	-0.03	23%	19 Nov →
inferno	9–13	0.04	21%	19 Nov →
nuke	8–13	-0.02	18%	15 Oct →
nuke	5–13	-0.03	22%	29 Sept →
inferno	7–13	-0.03	20%	25 Sept →
dust2	11–13	0.05	30%	24 Sept →
ancient	13–5	0.10	16%	23 Sept →
mirage	13–8	0.00	18%	21 Sept →
ancient	5–13	-0.04	19%	12 Sept →
train	11–13	0.01	22%	11 Sept →
mirage	7–13	0.01	17%	30 Aug →
nuke	13–9	-0.03	23%	27 Aug →
dust2	10–13	-0.02	23%	26 Aug →
dust2	17–19	0.04	19%	25 Aug →
dust2	7–13	-0.00	18%	20 Aug →
mirage	13–5	0.05	26%	20 Aug →
ancient	13–11	0.04	21%	20 Aug →
mirage	13–9	0.11	33%	18 Aug →
anubis	7–13	0.06	37%	3 Jul →
dust2	10–13	0.00	14%	28 Jun →
dust2	13–10	-0.01	22%	28 Jun →
mirage	11–13	0.01	15%	23 Jun →
mirage	9–13	-0.05	13%	22 Jun →
inferno	8–13	-0.02	29%	21 Jun →
nuke	16–13	-0.00	19%	9 Jun →
ancient	11–13	-0.00	22%	2 Jun →
dust2	13–4	0.15	33%	2 Jun →
inferno	8–13	-0.05	26%	28 May →
mirage	9–13	0.04	28%	28 May →
dust2	9–13	-0.05	23%	14 May →
mirage	13–9	0.01	40%	12 May →
dust2	16–12	0.03	24%	10 May →
anubis	13–9	0.01	24%	6 May →
ancient	13–16	0.02	27%	2 Mar →
dust2	10–13	0.00	27%	1 Mar →
mirage	13–6	0.07	35%	28 Feb →
mirage	14–16	0.02	19%	24 Feb →
ancient	4–13	-0.06	24%	20 Feb →
inferno	13–9	-0.01	36%	19 Feb →
inferno	13–4	-0.02	52%	19 Feb →
anubis	15–15	0.10	27%	17 Feb →
mirage	13–8	0.05	27%	17 Feb →
dust2	6–13	0.01	21%	21 Jan →
inferno	6–13	-0.01	34%	19 Jan →
anubis	13–11	-0.01	39%	18 Jan →