✪b0. — CS2 Stats

76561198221512820[U:1:261247092]Steam profile ↗✓ No bans

4,361Tracked matches33%Win rate2022Tracked since

CSDB Rating5.9 SolidAggressive Rifler

CSDB Leaderboard#53322 of 60809 tracked

WingmanSupreme Master First Class

Ladder ranks via Leetify

Rating over time

2,232Peak Faceit ELO on CSDB

1Days observed since 2026-08-31

Faceit ELO

At peak — 2,232
Next: 2,500 ELO at 2,500 — 268 to go
Reached: Level 10 · Level 9 · Level 8 · Level 7
Level 10 first seen 2026-08-31
Level 9 first seen 2026-08-31

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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Performance scores

Aim79

Positioning59

Utility57

0–100 skill scores via Leetify.

Recent form

COLD42–58Last 10042%Win rateLWLLLWLLLL

Last 10 vs previous 10: +0pp win rate · +0.03 avg rating

Player DNA

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

Aim7.9

Aggression8.1

Utility5.7

Positioning5.9

Opening Duels3.5

Clutch3.8

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 donk 90% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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. 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

Aim7.9

Positioning5.9

Utility5.7

Mechanics7.3

Opening Duels3.5

Win Impact0.0

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.03

first ⅓ avg 0.02 → last ⅓ avg -0.02

Reaction time596ms−20ms

first ⅓ avg 616ms → last ⅓ avg 596ms

Headshot accuracy22.7%+1.1%

first ⅓ avg 21.7% → last ⅓ avg 22.7%

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

0.20Best rating — inferno 13–1

13–0Biggest win — dust2

4Longest win streak

12–14In matches decided by ≤2 rounds

9Overtime games

Map breakdown

ancientBest map · 56% over 25infernoWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	34	16–18	47%	0.01
ancient	A	25	14–11	56%	-0.00
mirage	D	23	7–16	30%	0.01
inferno	D	7	2–5	29%	0.03
anubis	—	4	1–3	25%	-0.00
cache	—	3	0–3	0%	-0.01
overpass	—	3	2–1	67%	0.01
nuke	—	1	0–1	0%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,331Matches

51%Win rate

1.13Avg K/D

79.2ADR

52%Headshot %

Clutches & streaks

39%1v1 clutch win

21%1v2 clutch win

10Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	820	53%	1.15	16.4
Mirage	798	47%	1.12	16.2
Ancient	795	53%	1.15	16.8
Anubis	442	50%	1.08	16.2
Inferno	368	49%	1.08	16.0
Overpass	113	57%	1.24	15.9
Vertigo	111	47%	1.07	16.2
Nuke	91	51%	1.14	16.1

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.

22.8%Headshot accuracy

35.2%Accuracy (enemy spotted)

35.9%Spray accuracy

82.9%Counter-strafing

8.7°Preaim

594msReaction time

39.1%T opening success

49.1%CT opening success

0.57Enemies flashed / flash

8.5%Flash assists

6.26HE damage / grenade

10.45Flashes / 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 39.1046% — 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.

29% win rate across 7 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	13–16	0.08	13%	24 Aug →
dust2	13–8	0.04	55%	22 Jul →
inferno	9–13	-0.05	24%	16 Jul →
mirage	14–16	-0.03	26%	16 Jul →
ancient	11–13	0.04	12%	8 Jul →
ancient	13–9	-0.00	25%	8 Jul →
anubis	5–13	-0.04	26%	24 Jun →
ancient	8–13	-0.04	16%	24 Jun →
ancient	11–13	0.03	28%	24 Jun →
dust2	10–13	-0.03	29%	24 Jun →
ancient	0–13	-0.05	21%	24 Jun →
mirage	11–13	0.04	27%	24 Jun →
mirage	7–13	-0.05	19%	24 Jun →
ancient	8–13	-0.05	16%	24 Jun →
mirage	11–13	-0.00	18%	24 Jun →
mirage	11–13	0.03	16%	24 Jun →
ancient	13–10	-0.03	9%	24 Jun →
dust2	2–13	-0.07	40%	24 Jun →
dust2	13–11	-0.04	42%	20 Jun →
ancient	6–13	-0.11	14%	20 Jun →
anubis	13–11	-0.03	19%	20 Jun →
dust2	13–10	-0.03	24%	19 Jun →
ancient	6–13	-0.05	10%	19 Jun →
mirage	14–16	0.01	21%	19 Jun →
dust2	8–13	-0.04	26%	19 Jun →
dust2	13–3	0.02	30%	18 Jun →
dust2	13–8	0.05	20%	18 Jun →
mirage	13–11	-0.01	25%	18 Jun →
ancient	16–13	-0.01	14%	17 Jun →
mirage	14–16	-0.03	26%	17 Jun →
mirage	13–10	0.00	16%	17 Jun →
dust2	9–13	-0.06	10%	17 Jun →
dust2	13–11	-0.01	33%	17 Jun →
ancient	13–11	0.01	34%	17 Jun →
mirage	13–3	0.09	33%	16 Jun →
mirage	8–13	-0.05	35%	16 Jun →
mirage	5–13	-0.02	21%	16 Jun →
inferno	13–1	0.20	22%	15 Jun →
dust2	13–10	0.04	25%	15 Jun →
mirage	8–13	-0.01	19%	15 Jun →
nuke	11–13	-0.01	18%	15 Jun →
dust2	6–13	-0.07	30%	15 Jun →
cache	11–13	-0.05	18%	15 Jun →
ancient	13–7	-0.02	18%	12 Jun →
ancient	16–13	0.04	36%	9 Jun →
mirage	4–13	0.01	25%	7 Jun →
dust2	13–8	-0.03	33%	5 Jun →
dust2	13–6	0.05	25%	2 Jun →
ancient	13–11	-0.02	37%	30 May →
ancient	13–9	-0.01	20%	27 May →
dust2	8–13	0.05	30%	23 May →
dust2	13–11	0.03	28%	20 May →
dust2	13–4	0.09	32%	20 May →
ancient	11–13	0.04	12%	20 May →
dust2	0–7	-0.05	50%	20 May →
overpass	7–13	-0.02	9%	19 May →
mirage	8–13	0.06	24%	19 May →
dust2	7–13	-0.01	22%	19 May →
inferno	5–13	0.05	31%	17 May →
dust2	13–7	0.06	31%	16 May →
mirage	13–8	0.06	12%	16 May →
cache	9–13	0.03	18%	15 May →
cache	4–13	-0.01	22%	9 May →
dust2	3–13	0.03	30%	6 May →
anubis	7–13	-0.02	12%	30 Apr →
overpass	13–10	-0.02	19%	30 Apr →
overpass	13–5	0.06	15%	30 Apr →
ancient	6–13	0.03	19%	28 Apr →
mirage	9–13	-0.03	14%	23 Apr →
dust2	6–13	-0.04	32%	22 Apr →
dust2	8–13	0.06	24%	21 Apr →
ancient	13–6	0.00	18%	20 Apr →
ancient	3–13	-0.01	24%	20 Apr →
inferno	8–13	0.07	27%	19 Apr →
dust2	9–13	-0.01	20%	18 Apr →
mirage	9–13	-0.02	17%	18 Apr →
ancient	13–7	-0.00	20%	17 Apr →
dust2	9–13	-0.01	21%	17 Apr →
dust2	13–0	0.15	18%	17 Apr →
inferno	14–16	-0.06	14%	14 Apr →
dust2	9–13	-0.03	23%	11 Apr →
mirage	13–1	0.15	35%	11 Apr →
mirage	4–13	-0.04	22%	10 Apr →
inferno	13–11	-0.01	28%	8 Apr →
dust2	11–13	-0.06	32%	7 Apr →
ancient	13–11	-0.03	14%	5 Apr →
mirage	13–11	0.05	19%	31 Mar →
dust2	13–10	0.07	21%	28 Mar →
ancient	5–13	-0.06	12%	28 Mar →
ancient	13–5	0.09	32%	21 Mar →
ancient	16–14	0.02	19%	18 Mar →
mirage	13–16	-0.00	22%	17 Mar →
dust2	10–13	-0.02	21%	14 Mar →
ancient	13–5	0.09	21%	13 Mar →
dust2	11–13	0.07	27%	13 Mar →
mirage	13–9	0.00	13%	12 Mar →
dust2	6–13	0.00	14%	11 Mar →
dust2	13–8	0.06	27%	10 Mar →
dust2	13–11	0.02	23%	5 Mar →
inferno	5–13	-0.02	24%	27 Feb →