Ace — CS2 Stats

76561199010267971[U:1:1050002243]✓ No bans

879Tracked matches39%Win rate2023Tracked since

CSDB Rating3.8 LearningPassive Rifler

Premier CS Rating13,134Blue band · top ~38.3% of ranked players (population est.)

FaceitLevel 3 · 780 ELOTop 90.6% of ranked FACEIT players

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim61

Positioning37

Utility29

0–100 skill scores via Leetify.

Recent form

COLD40–55–5Last 10040%Win rateWLLLLLLLLW

Last 10 vs previous 10: -40pp win rate · -0.02 avg rating

Player DNA

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

Aim6.1

Aggression3.7

Utility2.9

Positioning3.7

Opening Duels0.0

Clutch1.8

Limited utility dependence

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 72% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower aim profile; 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. 666ms 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

Aim6.1

Positioning3.7

Utility2.9

Mechanics5.5

Opening Duels0.0

Win Impact1.4

Composite 3.8/10 (Learning), 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-0.03+0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time672ms+22ms

first ⅓ avg 651ms → last ⅓ avg 672ms

Headshot accuracy17.4%+0.4%

first ⅓ avg 17.0% → last ⅓ avg 17.4%

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 — mirage 13–10

13–0Biggest win — anubis

4Longest win streak

7–11In matches decided by ≤2 rounds

7Overtime games

Map breakdown

trainBest map · 80% over 5nukeWeakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	31	11–20	35%	-0.03
mirage	C	22	8–14	36%	-0.03
ancient	B	13	6–7	46%	-0.03
nuke	D	11	3–8	27%	-0.02
inferno	D	9	3–6	33%	-0.02
anubis	A	7	4–3	57%	-0.02
train	S	5	4–1	80%	-0.06
office	—	2	1–1	50%	-0.06

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

48Matches

44%Win rate

0.74Avg K/D

63.0ADR

35%Headshot %

Clutches & streaks

29%1v1 clutch win

4%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	12	42%	0.70	12.9
Ancient	9	44%	0.78	12.8
Mirage	8	25%	0.57	10.6
Nuke	6	83%	0.84	15.2
Inferno	5	60%	0.89	12.4
Train	4	25%	0.78	11.5
Overpass	3	33%	0.66	11.0
Anubis	1	0%	1.06	19.0

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.

18.2%Headshot accuracy

36.1%Accuracy (enemy spotted)

38.6%Spray accuracy

74.7%Counter-strafing

10.2°Preaim

666msReaction time

25.3%T opening success

30.2%CT opening success

0.52Enemies flashed / flash

1.8%Flash assists

5.08HE damage / grenade

2.63Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.6349 — below the 4 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 25.3292% — below the 40% mark we flag

Spend your practice time on Nuke

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–0	0.04	20%	19 Jul →
dust2	9–13	-0.05	20%	18 Jul →
mirage	6–13	-0.03	14%	2 Jul →
ancient	7–13	-0.09	10%	29 Jun →
dust2	2–8	-0.06	7%	18 Jun →
inferno	4–5	0.01	9%	18 Jun →
dust2	7–13	-0.07	25%	7 Jun →
mirage	7–13	-0.06	20%	11 Apr →
mirage	14–16	-0.07	12%	23 Mar →
dust2	16–13	-0.04	21%	23 Mar →
nuke	7–13	-0.05	43%	23 Mar →
dust2	12–12	-0.03	20%	22 Mar →
mirage	13–4	-0.02	23%	22 Mar →
dust2	1–13	-0.09	18%	22 Mar →
mirage	13–3	-0.03	12%	21 Mar →
nuke	12–12	-0.04	14%	21 Mar →
dust2	13–5	0.08	19%	21 Mar →
mirage	13–11	-0.01	21%	21 Mar →
dust2	13–5	-0.02	22%	21 Mar →
inferno	16–14	-0.06	18%	20 Mar →
dust2	14–16	-0.05	16%	20 Mar →
mirage	10–13	-0.00	20%	17 Mar →
ancient	6–13	-0.01	27%	17 Mar →
dust2	13–9	-0.05	16%	17 Mar →
anubis	2–13	-0.06	16%	9 Mar →
dust2	11–13	0.00	19%	7 Mar →
ancient	13–7	-0.01	17%	7 Mar →
inferno	9–13	-0.07	16%	7 Mar →
ancient	13–6	-0.05	13%	5 Mar →
nuke	9–13	0.07	13%	2 Mar →
dust2	13–9	0.00	18%	1 Mar →
anubis	13–3	-0.00	9%	1 Mar →
ancient	13–2	-0.03	9%	1 Mar →
mirage	6–13	-0.03	0%	28 Feb →
dust2	12–12	-0.08	12%	28 Feb →
mirage	9–13	-0.03	12%	27 Feb →
mirage	13–10	0.10	13%	23 Feb →
inferno	13–4	0.02	6%	23 Feb →
dust2	4–13	-0.04	18%	23 Feb →
inferno	13–3	0.02	16%	21 Feb →
mirage	16–14	-0.04	20%	20 Feb →
dust2	3–6	0.04	30%	20 Feb →
nuke	3–13	-0.08	15%	20 Feb →
dust2	13–7	-0.00	14%	20 Feb →
train	13–7	-0.03	14%	20 Feb →
dust2	13–11	-0.01	16%	18 Feb →
office	5–13	-0.13	11%	18 Feb →
dust2	13–10	-0.04	14%	17 Feb →
dust2	1–13	-0.08	0%	13 Feb →
dust2	10–13	-0.06	10%	12 Feb →
ancient	5–13	-0.07	21%	12 Feb →
nuke	9–13	-0.03	10%	12 Feb →
mirage	4–13	-0.06	18%	8 Feb →
nuke	13–8	-0.02	8%	8 Feb →
mirage	15–15	-0.06	16%	6 Feb →
mirage	13–5	-0.01	11%	5 Feb →
anubis	11–13	-0.07	14%	5 Feb →
mirage	13–7	-0.05	31%	5 Feb →
mirage	6–13	-0.03	21%	4 Feb →
dust2	8–13	0.02	24%	4 Feb →
ancient	10–13	-0.05	9%	2 Feb →
dust2	13–7	-0.04	16%	2 Feb →
mirage	10–13	0.06	25%	2 Feb →
inferno	9–13	-0.02	19%	30 Jan →
dust2	13–11	-0.04	33%	29 Jan →
ancient	11–13	-0.02	12%	29 Jan →
nuke	13–10	-0.01	17%	24 Jan →
ancient	13–2	0.01	6%	24 Jan →
dust2	9–13	-0.03	7%	15 Jan →
ancient	5–13	-0.05	27%	15 Jan →
dust2	5–13	-0.05	14%	14 Jan →
inferno	4–13	-0.06	18%	14 Jan →
ancient	10–13	-0.03	13%	14 Jan →
mirage	11–13	-0.07	16%	14 Jan →
train	13–11	-0.11	21%	13 Jan →
dust2	7–13	-0.08	12%	12 Jan →
train	13–9	-0.06	41%	12 Jan →
mirage	3–13	-0.03	26%	31 Dec →
train	13–10	-0.04	21%	31 Dec →
mirage	10–13	-0.06	16%	31 Dec →
dust2	13–5	-0.06	14%	31 Dec →
train	11–13	-0.08	11%	30 Dec →
anubis	13–9	-0.02	11%	30 Dec →
nuke	16–14	0.00	22%	28 Dec →
mirage	13–6	-0.06	13%	25 Dec →
ancient	13–1	0.10	15%	24 Dec →
anubis	10–13	-0.04	11%	24 Dec →
mirage	11–13	-0.05	17%	23 Dec →
dust2	12–12	0.03	27%	23 Dec →
dust2	6–13	-0.08	18%	22 Dec →
office	9–6	0.01	31%	22 Dec →
nuke	4–13	-0.03	18%	22 Dec →
ancient	13–8	-0.02	12%	21 Dec →
dust2	10–13	-0.03	13%	21 Dec →
nuke	11–13	-0.04	19%	19 Dec →
inferno	4–13	-0.02	15%	26 Oct →
dust2	10–13	0.01	14%	26 Oct →
inferno	5–13	-0.03	19%	22 Oct →
anubis	13–4	0.02	18%	16 Oct →
nuke	11–13	-0.05	6%	16 Oct →