shield — CS2 Stats

76561198253891911[U:1:293626183]Steam profile ↗✓ No bans

3,837Tracked matches53%Win rate2020Tracked since

CSDB Rating7.8 StrongAggressive Rifler

FaceitLevel 10 · 3,861 ELOTop 12.4% of ranked FACEIT players

WingmanThe Global Elite

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

Aim97

Positioning68

Utility69

0–100 skill scores via Leetify.

Recent form

STEADY55–45Last 10055%Win rateWLLLLWLLWW

Last 10 vs previous 10: -30pp win rate · +0.01 avg rating

Player DNA

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

Aim9.7

Aggression10.0

Utility6.9

Positioning6.8

Opening Duels5.2

Clutch4.0

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 sh1ro 97% playstyle similarity

Most alike: opening-fight frequency, 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

Strengths

Aim. Aim score of 97 — the mechanical foundation is a clear strength.

CT openings. 65% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 65% on CT to 36% 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

Aim9.7

Positioning6.8

Utility6.9

Mechanics6.7

Opening Duels5.2

Win Impact6.1

Composite 7.8/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.02

first ⅓ avg 0.01 → last ⅓ avg 0.02

Reaction time450ms+7ms

first ⅓ avg 442ms → last ⅓ avg 450ms

Headshot accuracy35.8%+13.0%

first ⅓ avg 22.8% → last ⅓ avg 35.8%

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

0.12Best rating — mirage 13–1

13–1Biggest win — anubis

8Longest win streak

6–7In matches decided by ≤2 rounds

9Overtime games

Map breakdown

mirageBest map · 73% over 11infernoWeakest map · 42% over 12

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	19	10–9	53%	0.02
anubis	A	18	10–8	56%	0.03
dust2	B	15	7–8	47%	0.01
overpass	S	14	10–4	71%	0.02
inferno	C	12	5–7	42%	0.00
mirage	S	11	8–3	73%	0.04
nuke	C	9	4–5	44%	0.01
cache	—	2	1–1	50%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6,738Matches

62%Win rate

1.45Avg K/D

84.5ADR

37%Headshot %

Clutches & streaks

40%1v1 clutch win

25%1v2 clutch win

21Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	687	59%	1.53	18.7
Anubis	494	65%	1.55	18.3
Ancient	450	60%	1.47	17.3
Dust2	301	61%	1.50	18.2
Nuke	108	54%	1.53	17.5
Inferno	87	59%	1.46	17.1
Vertigo	81	65%	1.30	17.2
Train	68	56%	1.48	16.7

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.

32.2%Headshot accuracy

41.9%Accuracy (enemy spotted)

39.0%Spray accuracy

80.3%Counter-strafing

7.1°Preaim

440msReaction time

36.4%T opening success

64.8%CT opening success

0.64Enemies flashed / flash

15.3%Flash assists

9.22HE damage / grenade

19.55Flashes / 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 36.4274% — 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.

42% win rate across 12 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	19–15	0.04	30%	23 Aug →
inferno	15–19	0.03	11%	17 Aug →
anubis	11–13	-0.02	29%	17 Aug →
dust2	9–13	0.00	35%	16 Aug →
anubis	7–13	-0.02	37%	16 Aug →
ancient	13–6	0.11	33%	9 Aug →
mirage	11–13	0.05	20%	9 Aug →
cache	14–16	-0.01	29%	9 Aug →
anubis	13–1	0.11	30%	8 Aug →
cache	13–7	0.10	26%	8 Aug →
anubis	13–9	0.08	24%	8 Aug →
anubis	8–13	-0.06	50%	7 Aug →
nuke	10–13	0.08	35%	7 Aug →
dust2	13–6	0.06	40%	7 Aug →
inferno	13–5	0.03	40%	7 Aug →
mirage	13–10	0.01	11%	24 Jul →
mirage	13–1	0.12	31%	11 Jul →
anubis	13–9	0.03	13%	22 Jun →
mirage	13–3	-0.01	31%	22 Jun →
ancient	1–13	-0.05	55%	14 Jun →
dust2	3–13	0.01	33%	14 Jun →
overpass	13–9	0.07	41%	14 Jun →
ancient	1–13	-0.05	55%	14 Jun →
dust2	3–13	0.01	33%	14 Jun →
overpass	13–9	0.07	41%	14 Jun →
overpass	13–6	0.05	32%	14 Jun →
overpass	13–6	0.05	32%	14 Jun →
mirage	13–3	0.07	33%	14 Jun →
overpass	0–13	-0.07	71%	13 Jun →
inferno	3–13	-0.02	36%	13 Jun →
inferno	3–13	-0.02	36%	13 Jun →
overpass	0–13	-0.07	71%	13 Jun →
overpass	13–11	0.03	57%	13 Jun →
inferno	9–13	-0.04	24%	13 Jun →
anubis	13–9	0.10	6%	13 Jun →
anubis	13–9	0.10	6%	13 Jun →
inferno	9–13	-0.04	24%	13 Jun →
overpass	13–11	0.03	57%	13 Jun →
inferno	13–11	0.05	78%	13 Jun →
anubis	13–4	0.10	16%	13 Jun →
mirage	12–16	0.07	32%	13 Jun →
inferno	13–11	0.05	78%	13 Jun →
mirage	12–16	0.07	32%	13 Jun →
anubis	13–4	0.10	16%	13 Jun →
dust2	13–7	0.02	23%	12 Jun →
anubis	13–3	0.05	32%	12 Jun →
anubis	13–3	0.08	23%	12 Jun →
dust2	13–4	0.03	19%	12 Jun →
overpass	13–1	0.11	26%	12 Jun →
mirage	16–12	-0.04	21%	4 Jun →
ancient	16–12	0.02	14%	17 Apr →
ancient	4–13	-0.01	40%	9 Apr →
dust2	5–13	0.03	21%	30 Mar →
mirage	19–17	0.01	29%	25 Mar →
mirage	13–7	0.03	19%	19 Mar →
dust2	13–9	0.00	16%	15 Mar →
anubis	11–13	0.02	3%	9 Mar →
ancient	10–13	0.02	18%	9 Mar →
inferno	13–3	-0.04	21%	6 Mar →
overpass	7–13	-0.04	64%	28 Feb →
nuke	10–13	-0.08	6%	28 Feb →
nuke	8–13	0.02	29%	27 Feb →
ancient	9–13	0.01	31%	27 Feb →
dust2	13–9	0.07	24%	27 Feb →
anubis	13–6	0.02	16%	27 Feb →
ancient	13–11	0.06	29%	26 Feb →
nuke	13–8	0.00	21%	26 Feb →
inferno	7–13	0.01	20%	22 Feb →
inferno	7–13	0.01	20%	22 Feb →
ancient	13–8	0.04	27%	22 Feb →
ancient	13–8	0.04	27%	22 Feb →
dust2	6–13	-0.00	43%	22 Feb →
dust2	6–13	-0.00	43%	22 Feb →
anubis	4–13	-0.08	17%	22 Feb →
anubis	4–13	-0.08	17%	22 Feb →
ancient	13–2	0.06	36%	22 Feb →
ancient	13–2	0.06	36%	22 Feb →
dust2	9–13	-0.01	13%	14 Feb →
anubis	8–13	-0.00	11%	14 Feb →
ancient	13–5	0.03	18%	13 Feb →
overpass	13–4	-0.00	33%	13 Feb →
inferno	13–10	0.03	29%	12 Feb →
mirage	13–8	0.11	39%	11 Feb →
ancient	7–13	-0.03	22%	5 Feb →
nuke	13–6	0.02	18%	5 Feb →
overpass	5–13	-0.09	0%	5 Feb →
ancient	13–7	0.07	29%	4 Feb →
dust2	13–9	0.04	23%	4 Feb →
nuke	9–13	-0.00	22%	4 Feb →
ancient	7–13	-0.02	19%	4 Feb →
nuke	13–10	0.04	26%	2 Feb →
anubis	11–13	0.00	19%	2 Feb →
overpass	13–10	0.06	14%	2 Feb →
overpass	13–10	0.03	19%	23 Jan →
ancient	14–16	-0.04	23%	23 Jan →
nuke	6–11	-0.04	10%	23 Jan →
nuke	13–6	0.01	32%	22 Jan →
ancient	11–13	0.02	17%	22 Jan →
dust2	13–9	0.05	33%	22 Jan →
dust2	1–13	-0.08	0%	22 Jan →