THEBror — CS2 Stats

NO76561198117666523[U:1:157400795]Steam profile ↗

2,098Tracked matches53%Win rate2020Tracked since

CSDB Rating5.7 SolidSupport

FaceitLevel 10 · 2,386 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim56

Positioning59

Utility72

0–100 skill scores via Leetify.

Recent form

HOT53–45–2Last 10053%Win rateWWWWLWLLWW

Last 10 vs previous 10: +40pp win rate · +0.04 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim5.6

Aggression4.8

Utility7.2

Positioning5.9

Opening Duels0.7

Clutch3.6

Effective flashes

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 88% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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. 597ms 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

Aim5.6

Positioning5.9

Utility7.2

Mechanics6.8

Opening Duels0.9

Win Impact6.1

Composite 5.7/10 (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-0.01−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time625ms+29ms

first ⅓ avg 596ms → last ⅓ avg 625ms

Headshot accuracy17.6%−7.6%

first ⅓ avg 25.2% → last ⅓ avg 17.6%

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

0.14Best rating — ancient 13–10

13–1Biggest win — train

8Longest win streak

W4Current streak

7–9In matches decided by ≤2 rounds

11Overtime games

Map breakdown

trainBest map · 79% over 14anubisWeakest map · 33% over 12

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	20	8–12	40%	-0.01
ancient	A	19	12–7	63%	0.01
overpass	B	15	8–7	53%	-0.02
train	S	14	11–3	79%	-0.01
anubis	D	12	4–8	33%	-0.02
nuke	—	3	2–1	67%	0.02
dust2	—	3	1–2	33%	-0.01
warden	—	3	2–1	67%	-0.02
cache	—	2	2–0	100%	0.02
poseidon	—	2	0–2	0%	-0.15
alpine	—	2	1–1	50%	0.02
stronghold	—	2	1–1	50%	-0.04
mirage	—	1	0–1	0%	-0.07
sanctum	—	1	1–0	100%	-0.04
agency	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,816Matches

52%Win rate

1.06Avg K/D

68.4ADR

49%Headshot %

Clutches & streaks

38%1v1 clutch win

12%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	195	53%	0.96	14.2
Anubis	194	53%	1.04	14.6
Inferno	176	48%	0.94	12.8
Overpass	80	61%	0.97	14.0
Mirage	59	39%	0.83	12.8
Train	53	57%	0.96	13.8
Nuke	18	44%	0.80	13.6
Dust2	10	10%	0.65	11.1

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.

17.5%Headshot accuracy

30.3%Accuracy (enemy spotted)

37.3%Spray accuracy

80.5%Counter-strafing

11.8°Preaim

597msReaction time

37.4%T opening success

28.0%CT opening success

0.74Enemies flashed / flash

21.3%Flash assists

11.22HE damage / grenade

6.17Flashes / 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 37.383% — 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.

33% win rate across 12 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
inferno	19–16	0.03	18%	20 Aug →
ancient	16–13	-0.02	17%	20 Aug →
ancient	13–4	0.03	29%	23 Jul →
nuke	13–2	0.05	13%	23 Jul →
dust2	9–13	-0.01	24%	23 Jul →
ancient	13–9	0.09	20%	23 Jul →
ancient	16–19	-0.06	10%	2 Jun →
overpass	8–13	-0.04	20%	26 May →
cache	13–9	0.05	24%	24 May →
cache	13–8	0.00	29%	24 May →
overpass	7–13	-0.02	18%	23 May →
poseidon	5–9	-0.18	7%	9 May →
alpine	7–13	0.03	6%	18 Apr →
train	10–13	0.02	15%	18 Apr →
inferno	9–13	0.02	19%	16 Apr →
ancient	13–8	0.05	17%	6 Apr →
anubis	22–20	-0.01	17%	4 Apr →
overpass	13–10	-0.03	14%	4 Apr →
mirage	7–13	-0.07	19%	29 Mar →
ancient	8–13	-0.05	16%	29 Mar →
anubis	13–5	0.01	13%	29 Mar →
inferno	13–5	0.03	20%	29 Mar →
anubis	11–13	-0.02	20%	29 Mar →
inferno	11–13	0.01	19%	26 Mar →
overpass	13–6	0.02	20%	26 Mar →
overpass	13–7	-0.01	24%	19 Mar →
inferno	13–11	-0.02	15%	14 Mar →
inferno	5–13	-0.07	15%	14 Mar →
overpass	7–13	-0.02	11%	12 Mar →
overpass	13–8	-0.02	11%	9 Mar →
warden	9–13	-0.04	17%	26 Feb →
alpine	13–7	0.00	20%	26 Feb →
stronghold	5–13	-0.07	25%	26 Feb →
warden	13–8	0.02	20%	22 Feb →
stronghold	13–6	-0.00	8%	22 Feb →
sanctum	9–7	-0.04	37%	9 Feb →
poseidon	6–9	-0.13	21%	9 Feb →
warden	13–5	-0.03	19%	24 Jan →
dust2	7–13	-0.04	28%	24 Jan →
nuke	13–9	0.02	17%	22 Jan →
ancient	13–7	-0.02	14%	22 Jan →
anubis	8–13	-0.03	14%	22 Jan →
anubis	13–3	0.08	23%	22 Jan →
inferno	5–13	0.03	15%	12 Jan →
anubis	11–13	-0.06	26%	12 Jan →
nuke	15–15	-0.01	23%	3 Jan →
inferno	7–13	0.00	24%	3 Jan →
train	13–4	0.02	22%	3 Jan →
inferno	8–13	0.01	19%	3 Jan →
overpass	8–13	-0.04	16%	3 Jan →
overpass	13–8	-0.05	29%	21 Dec →
train	15–15	0.02	14%	1 Dec →
overpass	16–14	-0.02	14%	12 Nov →
ancient	11–13	0.02	34%	5 Nov →
overpass	5–13	-0.06	30%	3 Nov →
ancient	7–13	0.02	20%	27 Oct →
overpass	8–13	0.01	23%	27 Oct →
overpass	13–9	-0.00	12%	20 Oct →
inferno	13–9	-0.02	22%	23 Sept →
ancient	13–11	-0.01	23%	23 Sept →
train	10–13	-0.06	10%	6 Sept →
inferno	10–13	-0.02	38%	5 Sept →
dust2	13–5	0.00	18%	3 Sept →
overpass	13–10	-0.05	22%	31 Aug →
inferno	11–13	0.01	23%	31 Aug →
train	13–10	-0.00	27%	27 Aug →
train	13–3	-0.07	19%	26 Aug →
ancient	13–5	0.07	21%	31 Jul →
inferno	13–9	0.01	20%	26 Jul →
inferno	3–13	-0.03	31%	15 Jul →
anubis	14–16	-0.05	15%	14 Jul →
ancient	10–13	-0.05	15%	12 Jul →
inferno	13–5	0.00	26%	1 Jul →
ancient	3–13	-0.06	27%	1 Jul →
train	13–4	-0.04	32%	1 Jul →
inferno	9–2	0.08	50%	23 Jun →
inferno	13–11	-0.02	23%	9 Jun →
inferno	4–13	-0.09	13%	8 Jun →
agency	4–13	-0.06	29%	5 Jun →
overpass	7–13	0.03	16%	4 Jun →
anubis	14–16	-0.03	21%	29 May →
anubis	14–16	-0.03	28%	27 May →
anubis	13–16	-0.09	19%	24 May →
anubis	13–8	0.02	21%	12 May →
ancient	13–10	0.14	16%	12 May →
ancient	13–10	0.05	23%	12 May →
inferno	5–13	-0.05	23%	11 May →
anubis	9–13	-0.06	27%	8 May →
ancient	7–13	0.01	29%	8 May →
ancient	13–10	-0.02	33%	8 May →
ancient	13–11	-0.02	19%	2 Mar →
inferno	11–13	-0.05	21%	2 Mar →
train	13–9	-0.02	25%	2 Mar →
train	13–9	0.02	36%	27 Feb →
train	13–8	-0.02	24%	26 Feb →
ancient	13–2	0.04	28%	24 Feb →
train	13–10	-0.02	46%	23 Feb →
train	13–6	0.02	21%	23 Feb →
train	13–10	0.03	20%	23 Feb →
train	13–1	0.03	35%	23 Feb →