T3RB0 — CS2 Stats

76561198186674902[U:1:226409174]Steam profile ↗

1,876Tracked matches40%Win rate2020Tracked since

CSDB Rating5.3 DevelopingPassive Rifler

Ladder ranks via Leetify

Performance scores

Aim87

Positioning45

Utility55

0–100 skill scores via Leetify.

Recent form

STEADY52–46–2Last 10052%Win rateWLWLLLWLLW

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

Player DNA

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

Aim8.7

Aggression4.2

Utility5.5

Positioning4.5

Opening Duels0.7

Clutch3.8

Sharp aimerExcellent counter-strafingStrong 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 NiKo 90% playstyle similarity

Most alike: opening-fight frequency, aim profile.

Where you differ: lower positioning 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 87 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 42 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 41% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 598ms 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

Aim8.7

Positioning4.5

Utility5.5

Mechanics8.5

Opening Duels1.4

Win Impact1.7

Composite 5.3/10 (Developing), 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-0.00−0.00

first ⅓ avg 0.00 → last ⅓ avg -0.00

Reaction time598ms−4ms

first ⅓ avg 603ms → last ⅓ avg 598ms

Headshot accuracy22.4%−2.0%

first ⅓ avg 24.4% → last ⅓ avg 22.4%

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

0.18Best rating — inferno 13–5

13–0Biggest win — mirage

7Longest win streak

11–4In matches decided by ≤2 rounds

6Overtime games

Map breakdown

overpassBest map · 80% over 5ancientWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	27	12–15	44%	0.01
inferno	B	21	11–10	52%	0.04
dust2	A	19	11–8	58%	-0.00
nuke	A	11	7–4	64%	-0.01
ancient	D	6	1–5	17%	-0.00
cache	C	5	2–3	40%	0.01
overpass	S	5	4–1	80%	-0.01
anubis	—	4	3–1	75%	-0.00
train	—	2	1–1	50%	-0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,903Matches

49%Win rate

0.90Avg K/D

70.1ADR

49%Headshot %

Clutches & streaks

39%1v1 clutch win

21%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	104	48%	0.99	15.1
Dust2	54	54%	1.07	14.7
Inferno	52	54%	0.93	13.6
Anubis	29	52%	1.09	16.0
Ancient	27	33%	0.85	13.1
Nuke	18	39%	0.87	13.4
Vertigo	2	50%	0.56	8.0
Train	2	50%	1.08	27.0

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.

22.5%Headshot accuracy

38.3%Accuracy (enemy spotted)

42.0%Spray accuracy

88.3%Counter-strafing

9.1°Preaim

598msReaction time

24.9%T opening success

41.0%CT opening success

0.57Enemies flashed / flash

8.7%Flash assists

9.39HE damage / grenade

8.77Flashes / 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 24.9186% — below the 40% mark we flag

Spend your practice time on Ancient

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	13–8	0.12	23%	27 Aug →
cache	14–16	-0.06	29%	16 Aug →
mirage	13–0	-0.00	20%	16 Aug →
mirage	7–13	-0.05	9%	13 Aug →
ancient	4–13	0.02	28%	13 Aug →
mirage	3–13	-0.01	24%	6 Aug →
mirage	13–5	-0.03	20%	28 Jul →
mirage	10–13	-0.04	24%	19 Jul →
dust2	5–13	-0.04	10%	19 Jul →
mirage	13–7	0.06	23%	18 Jul →
mirage	13–11	0.05	18%	17 Jul →
inferno	13–11	0.03	25%	17 Jul →
mirage	9–13	-0.03	24%	17 Jul →
dust2	13–9	0.07	25%	17 Jul →
ancient	6–13	0.05	25%	14 Jul →
dust2	13–8	-0.05	31%	14 Jul →
inferno	13–11	0.03	9%	7 Jul →
ancient	7–13	-0.07	28%	7 Jul →
nuke	11–13	-0.03	21%	6 Jul →
mirage	7–13	0.03	21%	6 Jul →
mirage	7–13	0.01	20%	6 Jul →
inferno	11–13	-0.01	33%	30 Jun →
overpass	13–4	0.02	26%	30 Jun →
dust2	13–11	0.00	18%	30 Jun →
ancient	5–13	0.06	48%	29 Jun →
dust2	2–13	-0.08	23%	29 Jun →
mirage	13–9	0.02	22%	29 Jun →
nuke	7–13	-0.07	21%	28 Jun →
mirage	7–13	-0.04	18%	28 Jun →
dust2	7–13	0.01	14%	28 Jun →
inferno	13–10	0.02	13%	28 Jun →
mirage	13–10	0.00	26%	28 Jun →
nuke	13–9	-0.06	25%	27 Jun →
inferno	13–6	0.05	38%	27 Jun →
inferno	13–7	0.05	21%	27 Jun →
mirage	13–6	-0.06	26%	27 Jun →
dust2	13–6	0.02	38%	27 Jun →
overpass	7–13	-0.03	16%	27 Jun →
inferno	5–13	0.01	33%	27 Jun →
inferno	10–13	0.09	28%	27 Jun →
dust2	6–13	-0.00	21%	24 Jun →
ancient	10–13	-0.05	22%	23 Jun →
mirage	13–5	0.01	22%	23 Jun →
anubis	13–11	0.03	17%	23 Jun →
dust2	13–10	0.06	17%	23 Jun →
train	13–11	-0.04	27%	18 Jun →
cache	13–10	0.04	43%	18 Jun →
mirage	5–13	-0.05	15%	18 Jun →
dust2	13–6	-0.02	21%	18 Jun →
inferno	2–13	-0.05	16%	16 Jun →
cache	1–13	-0.06	18%	16 Jun →
overpass	13–11	-0.02	19%	8 Jun →
mirage	8–13	0.10	16%	8 Jun →
inferno	13–8	-0.02	43%	3 Jun →
inferno	8–13	0.08	29%	1 Jun →
cache	11–13	0.08	21%	30 May →
inferno	9–13	0.02	27%	30 May →
train	10–13	0.03	27%	30 May →
inferno	6–13	-0.05	33%	29 May →
mirage	13–6	0.05	33%	28 May →
nuke	13–7	0.01	33%	28 May →
mirage	13–6	0.13	26%	28 May →
mirage	13–7	0.11	23%	27 May →
dust2	13–4	0.07	26%	27 May →
nuke	9–13	0.02	18%	24 May →
inferno	9–13	0.05	47%	24 May →
inferno	13–7	0.04	23%	23 May →
mirage	4–13	-0.03	30%	21 May →
nuke	13–7	0.04	33%	20 May →
mirage	13–8	0.01	27%	20 May →
mirage	7–13	-0.03	23%	19 May →
dust2	13–3	0.04	20%	17 May →
inferno	13–5	0.18	22%	17 May →
nuke	13–9	0.04	23%	16 May →
dust2	8–13	-0.03	31%	13 May →
overpass	16–13	0.00	10%	13 May →
cache	13–4	0.04	21%	29 Apr →
anubis	16–14	0.01	17%	26 Apr →
dust2	7–13	-0.04	27%	25 Apr →
inferno	15–15	0.04	29%	25 Apr →
dust2	13–11	-0.03	28%	25 Apr →
mirage	9–13	-0.02	14%	25 Apr →
dust2	10–13	-0.04	17%	24 Apr →
nuke	13–10	-0.04	14%	24 Apr →
inferno	3–13	-0.01	42%	24 Apr →
anubis	16–14	0.01	34%	24 Apr →
nuke	9–13	-0.05	26%	16 Apr →
mirage	10–13	0.00	35%	16 Apr →
inferno	13–9	0.02	27%	16 Apr →
nuke	13–8	0.08	46%	16 Apr →
inferno	13–9	0.04	26%	13 Apr →
nuke	13–10	-0.03	18%	10 Apr →
mirage	10–13	-0.02	16%	10 Apr →
ancient	13–9	-0.02	22%	9 Apr →
dust2	8–13	-0.05	18%	8 Apr →
overpass	13–9	-0.02	21%	7 Apr →
dust2	13–11	0.01	24%	6 Apr →
dust2	13–8	0.02	18%	4 Apr →
anubis	15–15	-0.06	20%	31 Mar →
mirage	5–13	0.03	26%	31 Mar →