Burning Cyclone — CS2 Stats

BD76561198036605405[U:1:76339677]Steam profile ↗VAC banned

1,540Tracked matches48%Win rate2020Tracked since

CSDB Rating6.3 SolidAggressive Rifler

Premier CS Rating17,001Purple band · top ~20.4% of ranked players (population est.)

CSDB Leaderboard#10727 of 18565 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim90

Positioning53

Utility52

0–100 skill scores via Leetify.

Recent form

COLD55–43–2Last 10055%Win rateTWWLLLLLLW

Last 10 vs previous 10: -40pp win rate · +0.00 avg rating

Player DNA

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

Aim9.0

Aggression9.2

Utility5.2

Positioning5.3

Opening Duels4.3

Clutch0.0

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 jL 93% playstyle similarity

Most alike: opening-fight frequency, aim profile.

Where you differ: 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

Strengths

Aim. Aim score of 90 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 37 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 55% on CT to 39% 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

Aim9.0

Positioning5.3

Utility5.2

Mechanics6.0

Opening Duels4.3

Win Impact4.4

Composite 6.3/10 (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 rating0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg 0.00

Reaction time531ms−62ms

first ⅓ avg 593ms → last ⅓ avg 531ms

Headshot accuracy35.7%−0.5%

first ⅓ avg 36.2% → last ⅓ avg 35.7%

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

0.15Best rating — dust2 13–5

13–0Biggest win — dust2

10Longest win streak

3–6In matches decided by ≤2 rounds

3Overtime games

Map breakdown

ancientBest map · 76% over 17infernoWeakest map · 43% over 28

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	31	19–12	61%	-0.00
inferno	C	28	12–16	43%	-0.01
ancient	S	17	13–4	76%	0.00
nuke	B	17	8–9	47%	-0.02
cache	—	4	3–1	75%	-0.01
mirage	—	2	0–2	0%	-0.04
anubis	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (43% over 28). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

238Matches

48%Win rate

1.34Avg K/D

67.2ADR

44%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	35	66%	1.24	18.1
Nuke	22	82%	1.00	14.3
Ancient	16	75%	1.07	14.8
Mirage	11	36%	0.80	11.8
Anubis	6	17%	0.73	13.3
Overpass	1	100%	0.44	7.0

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.

36.2%Headshot accuracy

34.3%Accuracy (enemy spotted)

28.8%Spray accuracy

77.1%Counter-strafing

7.3°Preaim

519msReaction time

39.2%T opening success

55.3%CT opening success

0.59Enemies flashed / flash

3.9%Flash assists

9.38HE damage / grenade

6.12Flashes / 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 39.2009% — 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.

43% win rate across 28 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
inferno	15–15	-0.03	39%	28 Aug →
dust2	13–5	0.15	65%	27 Aug →
ancient	13–10	-0.04	26%	27 Aug →
dust2	8–13	0.02	23%	24 Aug →
anubis	9–13	0.03	29%	23 Aug →
inferno	5–13	-0.07	25%	23 Aug →
inferno	3–13	-0.10	16%	22 Aug →
nuke	10–13	-0.03	67%	20 Aug →
inferno	9–13	0.03	33%	20 Aug →
ancient	13–3	0.08	31%	20 Aug →
inferno	2–13	-0.09	33%	20 Aug →
nuke	13–3	0.07	80%	19 Aug →
inferno	7–13	-0.02	60%	17 Aug →
ancient	13–2	0.05	26%	16 Aug →
ancient	13–9	-0.03	16%	15 Aug →
ancient	13–4	-0.01	50%	14 Aug →
dust2	13–4	0.02	38%	14 Aug →
nuke	13–6	0.03	50%	13 Aug →
nuke	5–13	0.05	47%	13 Aug →
dust2	13–10	-0.05	5%	12 Aug →
dust2	13–7	-0.00	35%	11 Aug →
inferno	13–7	0.12	30%	11 Aug →
ancient	13–8	0.04	31%	10 Aug →
inferno	5–13	-0.09	25%	9 Aug →
nuke	3–13	0.01	78%	8 Aug →
dust2	7–13	-0.01	16%	8 Aug →
dust2	13–5	0.09	21%	7 Aug →
nuke	10–13	-0.00	37%	7 Aug →
cache	13–16	-0.06	33%	6 Aug →
inferno	7–13	-0.05	38%	6 Aug →
inferno	11–13	-0.00	27%	5 Aug →
inferno	8–13	0.01	32%	5 Aug →
dust2	4–13	-0.08	17%	4 Aug →
mirage	2–13	-0.05	20%	4 Aug →
ancient	3–13	-0.00	23%	4 Aug →
dust2	13–6	-0.03	12%	3 Aug →
cache	13–11	-0.04	9%	3 Aug →
inferno	9–13	-0.08	33%	2 Aug →
dust2	13–11	-0.03	21%	1 Aug →
dust2	13–6	-0.02	25%	1 Aug →
dust2	13–9	0.02	21%	1 Aug →
ancient	13–7	0.01	42%	1 Aug →
nuke	13–9	-0.02	22%	31 Jul →
dust2	13–4	0.12	33%	31 Jul →
nuke	13–8	-0.06	50%	30 Jul →
inferno	13–6	0.04	39%	29 Jul →
dust2	13–4	-0.02	56%	28 Jul →
inferno	13–4	0.12	37%	27 Jul →
nuke	1–4	-0.11	50%	27 Jul →
ancient	13–7	-0.06	33%	26 Jul →
nuke	13–2	-0.05	0%	26 Jul →
inferno	13–3	0.07	57%	24 Jul →
ancient	13–8	0.00	21%	23 Jul →
dust2	13–9	-0.02	33%	23 Jul →
nuke	9–13	-0.05	48%	22 Jul →
nuke	3–4	-0.09	100%	22 Jul →
inferno	13–10	0.06	21%	21 Jul →
ancient	13–8	-0.02	20%	20 Jul →
inferno	13–7	-0.01	47%	19 Jul →
dust2	13–0	0.05	25%	19 Jul →
inferno	13–9	-0.05	43%	18 Jul →
dust2	13–4	0.07	50%	18 Jul →
dust2	4–13	-0.02	29%	17 Jul →
nuke	11–13	-0.01	43%	17 Jul →
nuke	13–9	-0.03	20%	16 Jul →
ancient	11–13	-0.00	33%	15 Jul →
inferno	0–8	-0.09	33%	15 Jul →
inferno	11–13	-0.02	26%	14 Jul →
dust2	13–11	-0.04	45%	13 Jul →
inferno	13–3	-0.03	55%	12 Jul →
mirage	7–13	-0.03	19%	11 Jul →
inferno	13–2	0.09	40%	11 Jul →
ancient	1–13	-0.00	43%	10 Jul →
cache	13–9	-0.01	28%	8 Jul →
dust2	12–12	0.01	40%	8 Jul →
dust2	0–6	-0.03	50%	7 Jul →
dust2	3–13	-0.08	31%	6 Jul →
ancient	13–10	-0.02	43%	4 Jul →
ancient	9–13	-0.04	32%	3 Jul →
nuke	9–13	-0.07	67%	2 Jul →
dust2	9–13	-0.04	50%	2 Jul →
dust2	5–13	-0.08	50%	1 Jul →
cache	13–2	0.08	40%	1 Jul →
inferno	13–1	0.06	25%	30 Jun →
dust2	13–7	0.02	40%	30 Jun →
inferno	13–9	-0.05	24%	29 Jun →
inferno	13–7	-0.02	42%	28 Jun →
ancient	13–7	-0.02	38%	28 Jun →
dust2	4–13	-0.04	32%	26 Jun →
dust2	13–6	-0.01	24%	26 Jun →
inferno	9–13	-0.03	21%	25 Jun →
dust2	13–3	0.04	20%	25 Jun →
nuke	13–2	-0.00	32%	24 Jun →
dust2	10–13	-0.05	24%	24 Jun →
dust2	13–7	-0.03	30%	20 Jun →
ancient	13–5	0.12	29%	19 Jun →
dust2	5–13	-0.04	56%	18 Jun →
inferno	11–13	-0.07	25%	17 Jun →
nuke	16–13	-0.03	3%	17 Jun →
inferno	10–13	-0.09	75%	16 Jun →