Akashi — CS2 Stats

76561198112244631[U:1:151978903]Steam profile ↗✓ No bans

1,172Tracked matches40%Win rate2023Tracked since

CSDB Rating3.4 Learning

FaceitLevel 5 · 889 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim40

Positioning42

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY50–49–1Last 10050%Win rateWWLLLWWWLL

Last 10 vs previous 10: +30pp win rate · -0.02 avg rating

Player DNA

Aim4.0

Aggression5.3

Utility5.2

Positioning4.2

Opening Duels1.5

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 NiKo 81% playstyle similarity

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

Where you differ: lower positioning profile; 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

Reaction time. 608ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Aim4.0

Positioning4.2

Utility5.2

Mechanics4.1

Opening Duels1.5

Win Impact1.7

Composite 3.4/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time627ms−31ms

first ⅓ avg 658ms → last ⅓ avg 627ms

Headshot accuracy12.0%−1.7%

first ⅓ avg 13.6% → last ⅓ avg 12.0%

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

0.10Best rating — ancient 13–6

13–1Biggest win — dust2

8Longest win streak

W2Current streak

5–7In matches decided by ≤2 rounds

10Overtime games

Map breakdown

infernoBest map · 56% over 16anubisWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	28	15–13	54%	-0.01
mirage	B	27	13–14	48%	-0.02
inferno	A	16	9–7	56%	-0.03
ancient	C	12	5–7	42%	-0.01
anubis	C	10	4–6	40%	-0.02
cache	—	4	2–2	50%	-0.03
overpass	—	2	2–0	100%	0.04
italy	—	1	0–1	0%	-0.09

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

239Matches

50%Win rate

0.94Avg K/D

76.3ADR

35%Headshot %

Clutches & streaks

36%1v1 clutch win

23%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	74	59%	0.98	14.7
Mirage	70	46%	0.95	14.7
Inferno	42	50%	0.91	15.5
Ancient	22	36%	0.96	14.3
Nuke	11	73%	1.06	13.7
Cache	9	56%	0.86	12.3
Anubis	8	12%	0.66	14.4
Overpass	1	100%	1.38	22.0

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.

11.5%Headshot accuracy

32.6%Accuracy (enemy spotted)

35.7%Spray accuracy

68.4%Counter-strafing

11.7°Preaim

608msReaction time

29.3%T opening success

42.3%CT opening success

0.63Enemies flashed / flash

2.0%Flash assists

8.92HE damage / grenade

7.69Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 11.4581% — below the 15% mark we flag
Aim Training →
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 29.3436% — 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.

40% win rate across 10 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
mirage	13–10	0.01	7%	19 Aug →
cache	13–10	-0.07	12%	18 Aug →
mirage	10–13	-0.03	11%	17 Aug →
dust2	7–13	-0.03	18%	17 Aug →
mirage	2–13	-0.08	0%	15 Aug →
inferno	13–5	-0.05	21%	15 Aug →
dust2	13–2	0.06	18%	15 Aug →
ancient	13–8	-0.02	16%	12 Aug →
mirage	9–13	-0.06	11%	8 Aug →
inferno	11–13	-0.04	11%	8 Aug →
ancient	4–13	0.01	19%	7 Aug →
ancient	5–13	-0.02	10%	6 Aug →
cache	4–13	-0.04	33%	5 Aug →
ancient	13–6	0.10	13%	5 Aug →
dust2	11–13	0.01	8%	30 Jul →
ancient	7–13	-0.07	3%	24 Jul →
mirage	13–10	-0.01	5%	22 Jul →
anubis	6–13	-0.06	3%	17 Jul →
inferno	11–13	0.03	14%	17 Jul →
ancient	3–13	-0.09	8%	10 Jul →
dust2	13–10	-0.03	13%	10 Jul →
cache	5–2	0.01	7%	1 Jul →
dust2	2–13	-0.06	8%	19 Jun →
mirage	0–10	-0.08	17%	19 Jun →
dust2	13–9	0.05	15%	19 Jun →
mirage	13–8	0.02	14%	19 Jun →
dust2	11–13	0.01	12%	18 Jun →
mirage	6–13	-0.05	7%	18 Jun →
dust2	11–13	-0.04	7%	31 May →
mirage	16–12	-0.01	9%	30 May →
overpass	13–8	0.04	15%	30 May →
ancient	13–9	0.03	17%	30 May →
inferno	13–10	-0.04	15%	30 May →
inferno	13–8	-0.03	9%	30 May →
inferno	10–13	-0.05	11%	29 May →
inferno	13–10	0.03	15%	29 May →
dust2	7–3	-0.00	29%	29 May →
mirage	6–13	-0.02	17%	25 May →
anubis	6–13	-0.05	11%	25 May →
mirage	5–13	-0.07	20%	25 May →
dust2	13–11	-0.01	15%	23 May →
anubis	7–13	-0.01	4%	19 May →
cache	8–13	-0.01	9%	2 May →
dust2	9–13	-0.02	14%	2 May →
inferno	8–13	-0.08	11%	29 Apr →
ancient	9–13	-0.12	50%	26 Apr →
anubis	5–1	-0.06	33%	10 Apr →
dust2	13–8	-0.02	4%	7 Apr →
anubis	8–13	-0.04	2%	6 Apr →
mirage	6–13	-0.02	13%	5 Apr →
dust2	7–13	-0.07	24%	5 Apr →
dust2	6–13	-0.05	3%	4 Apr →
dust2	13–8	0.02	9%	4 Apr →
dust2	10–13	-0.01	5%	3 Apr →
dust2	13–2	0.01	2%	3 Apr →
anubis	14–16	-0.01	14%	3 Apr →
inferno	9–13	0.01	20%	3 Apr →
dust2	13–7	-0.02	8%	3 Apr →
inferno	1–12	-0.07	7%	28 Mar →
dust2	1–13	-0.08	3%	28 Mar →
mirage	5–13	-0.04	14%	28 Mar →
ancient	10–13	0.00	24%	27 Mar →
inferno	13–10	-0.04	7%	27 Mar →
ancient	11–13	0.01	5%	27 Mar →
mirage	13–8	0.03	9%	27 Mar →
ancient	13–4	0.06	16%	23 Mar →
anubis	13–5	0.04	6%	23 Mar →
dust2	15–15	-0.01	10%	23 Mar →
dust2	9–13	0.02	9%	22 Mar →
inferno	13–6	-0.00	17%	22 Mar →
dust2	16–12	0.02	27%	22 Mar →
ancient	13–11	-0.01	10%	21 Mar →
inferno	13–6	-0.02	10%	21 Mar →
mirage	13–2	0.05	11%	21 Mar →
mirage	13–2	0.07	8%	21 Mar →
inferno	16–14	-0.02	14%	21 Mar →
inferno	16–13	-0.01	12%	20 Mar →
mirage	1–13	-0.10	17%	20 Mar →
dust2	16–14	0.03	4%	20 Mar →
mirage	13–10	0.01	12%	19 Mar →
dust2	13–10	0.07	12%	19 Mar →
anubis	13–5	0.05	11%	15 Mar →
italy	5–13	-0.09	11%	15 Mar →
dust2	13–9	-0.07	22%	5 Mar →
dust2	13–8	-0.02	18%	5 Mar →
mirage	6–13	-0.05	5%	26 Feb →
mirage	3–13	-0.09	9%	25 Feb →
mirage	13–16	-0.08	17%	23 Feb →
mirage	13–3	0.04	18%	23 Feb →
anubis	3–13	-0.04	9%	22 Feb →
mirage	13–4	0.03	5%	21 Feb →
mirage	13–8	-0.05	16%	20 Feb →
inferno	13–16	-0.05	17%	20 Feb →
dust2	13–1	0.08	22%	20 Feb →
mirage	5–13	-0.06	24%	20 Feb →
overpass	16–14	0.04	15%	19 Feb →
mirage	13–6	-0.01	4%	18 Feb →
dust2	8–13	-0.01	10%	17 Feb →
anubis	13–6	-0.01	23%	17 Feb →
mirage	13–9	0.00	20%	14 Feb →