BJ Deefstorm — CS2 Stats

HM76561198297450626[U:1:337184898]Steam profile ↗

1,097Tracked matches57%Win rate2020Tracked since

4,446Hours in CS17Hrs last 2 wks

CSDB Rating4.2 Developing

FaceitLevel 4 · 1,049 ELOTop 81.0% of ranked FACEIT players

WingmanGold Nova III

Ladder ranks via Leetify

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Performance scores

Aim43

Positioning57

Utility48

0–100 skill scores via Leetify.

Recent form

COLD48–45–7Last 10048%Win rateLTWLLLTWWL

Last 10 vs previous 10: -50pp win rate · -0.01 avg rating

Player DNA

Aim4.3

Aggression6.0

Utility4.8

Positioning5.7

Opening Duels1.3

Clutch2.4

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 82% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

CT openings. Opening success drops from 44% on T to 26% on CT — first contacts on the defending side are being lost.

Reaction time. 616ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.3

Positioning5.7

Utility4.8

Mechanics4.1

Opening Duels1.8

Win Impact7.4

Composite 4.2/10 (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 rating0.01+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.01

Reaction time610ms−14ms

first ⅓ avg 625ms → last ⅓ avg 610ms

Headshot accuracy17.3%−3.9%

first ⅓ avg 21.3% → last ⅓ avg 17.3%

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 — vertigo 9–7

13–2Biggest win — dust2

9Longest win streak

6–4In matches decided by ≤2 rounds

2Overtime games

Map breakdown

officeBest map · 60% over 5infernoWeakest map · 20% over 10

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	19	10–9	53%	0.01
dust2	B	17	8–9	47%	-0.01
vertigo	A	16	9–7	56%	0.03
nuke	A	11	6–5	55%	-0.02
inferno	D	10	2–8	20%	-0.02
ancient	C	8	3–5	38%	0.00
anubis	D	5	1–4	20%	-0.02
office	A	5	3–2	60%	0.02
mirage	—	4	2–2	50%	-0.00
train	—	4	3–1	75%	-0.04
overpass	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

75,965Lifetime kills

1.08K/D · Top 50% of tracked players

3,833Matches

34.2%Match win rate

36.2%Headshot %

12.3%Shot accuracy · Top 50% of tracked players

6,475MVPs

1,271Hours (in match)

2,883Bombs planted

724Bombs defused

Most-used weapons

AK-4719,721

M4A4 / M4A1-S10,782

AWP10,646

Desert Eagle3,996

P2000 / USP-S3,892

Glock-182,520

Tec-92,125

MAC-101,716

Knife1,521

P2501,401

Lifetime map wins

6,779dust2

2,887nuke

2,152inferno

1,726vertigo

1,425office

1,165train

140cbble

81ar_shoots

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

128Matches

52%Win rate

1.05Avg K/D

81.0ADR

34%Headshot %

Clutches & streaks

32%1v1 clutch win

35%1v2 clutch win

5Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	31	55%	1.03	15.9
Mirage	14	43%	1.09	15.9
Ancient	12	42%	1.06	16.5
Inferno	6	50%	0.84	9.8
Train	5	80%	0.77	12.8
Nuke	5	80%	1.32	14.6
Anubis	3	67%	1.63	16.0
Overpass	1	0%	0.70	14.0

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.

17.7%Headshot accuracy

30.8%Accuracy (enemy spotted)

30.3%Spray accuracy

68.6%Counter-strafing

11.0°Preaim

616msReaction time

44.3%T opening success

26.4%CT opening success

0.35Enemies flashed / flash

3.7%Flash assists

8.82HE damage / grenade

8.29Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3544 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 26.3623% — 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.

20% win rate across 10 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	8–13	-0.01	16%	28 Aug →
vertigo	12–12	0.06	17%	27 Aug →
cache	13–5	0.12	27%	26 Aug →
anubis	4–13	-0.03	23%	20 Aug →
ancient	10–13	0.06	16%	19 Aug →
ancient	5–13	-0.03	25%	19 Aug →
vertigo	12–12	0.05	16%	14 Aug →
ancient	16–14	0.02	15%	4 Aug →
nuke	13–3	-0.02	25%	4 Aug →
anubis	6–13	-0.09	15%	4 Aug →
anubis	5–13	-0.08	15%	30 Jul →
cache	13–6	0.06	21%	29 Jul →
ancient	6–13	0.04	10%	29 Jul →
dust2	13–2	-0.02	22%	29 Jul →
dust2	13–9	0.04	16%	28 Jul →
nuke	13–9	-0.00	8%	25 Jun →
inferno	13–7	-0.01	16%	25 Jun →
nuke	16–12	-0.01	18%	25 Jun →
anubis	13–8	0.14	14%	24 Jun →
cache	13–7	0.07	26%	24 Jun →
cache	13–8	0.01	25%	23 Jun →
dust2	13–6	-0.01	15%	23 Jun →
mirage	11–13	0.02	12%	21 Jun →
nuke	10–13	-0.01	20%	21 Jun →
dust2	11–13	-0.04	20%	21 Jun →
vertigo	8–13	-0.00	15%	21 Jun →
dust2	13–6	0.04	26%	21 Jun →
dust2	6–13	-0.03	13%	20 Jun →
cache	13–6	0.02	16%	20 Jun →
nuke	13–10	0.02	16%	19 Jun →
dust2	13–11	-0.03	7%	19 Jun →
inferno	8–13	-0.01	8%	19 Jun →
ancient	13–10	0.02	18%	19 Jun →
nuke	13–5	0.02	13%	19 Jun →
nuke	2–9	-0.13	25%	18 Jun →
inferno	6–13	0.01	19%	18 Jun →
inferno	4–13	-0.03	8%	18 Jun →
train	13–11	-0.02	28%	18 Jun →
dust2	5–13	0.02	24%	18 Jun →
mirage	13–7	-0.02	26%	18 Jun →
cache	13–7	0.04	10%	18 Jun →
cache	10–13	0.04	17%	18 Jun →
vertigo	13–5	0.02	11%	16 Jun →
cache	8–13	0.01	20%	12 Jun →
vertigo	13–4	0.06	20%	12 Jun →
train	5–2	-0.06	30%	12 Jun →
inferno	5–13	-0.05	21%	12 Jun →
ancient	4–13	-0.03	14%	12 Jun →
vertigo	6–13	-0.07	14%	12 Jun →
dust2	10–13	0.01	26%	11 Jun →
cache	0–13	-0.04	12%	10 Jun →
dust2	13–6	-0.03	23%	9 Jun →
office	13–9	0.01	18%	9 Jun →
inferno	10–13	-0.03	12%	5 Jun →
mirage	13–7	0.02	18%	5 Jun →
overpass	13–5	0.03	11%	5 Jun →
nuke	1–13	-0.04	13%	5 Jun →
inferno	5–13	0.01	27%	4 Jun →
inferno	13–8	-0.04	10%	4 Jun →
cache	13–9	-0.01	7%	4 Jun →
dust2	7–13	0.02	15%	4 Jun →
nuke	9–4	-0.04	21%	3 Jun →
vertigo	13–7	0.04	12%	3 Jun →
vertigo	13–7	0.00	9%	3 Jun →
anubis	2–13	-0.02	35%	2 Jun →
ancient	3–13	-0.07	21%	31 May →
inferno	11–13	-0.03	11%	31 May →
nuke	7–13	-0.01	21%	31 May →
cache	10–13	-0.02	14%	31 May →
cache	13–8	0.05	25%	10 May →
cache	13–2	-0.06	14%	10 May →
vertigo	9–7	0.14	28%	5 May →
cache	11–13	-0.01	21%	4 May →
mirage	3–13	-0.04	23%	3 May →
office	5–13	0.00	23%	3 May →
dust2	4–13	-0.05	24%	2 May →
vertigo	13–8	0.08	11%	2 May →
office	13–7	0.04	18%	2 May →
cache	10–13	0.00	32%	2 May →
cache	8–13	-0.04	50%	2 May →
cache	13–6	-0.00	31%	1 May →
cache	6–13	0.02	17%	30 Apr →
cache	12–12	-0.01	31%	29 Apr →
office	8–13	-0.04	18%	26 Apr →
train	12–12	0.00	20%	23 Apr →
nuke	12–12	-0.05	21%	23 Apr →
vertigo	13–7	-0.02	6%	22 Apr →
vertigo	6–13	-0.01	17%	22 Apr →
dust2	1–13	-0.09	4%	22 Apr →
train	13–4	-0.10	13%	22 Apr →
dust2	13–11	-0.06	21%	19 Apr →
ancient	13–7	0.01	19%	19 Apr →
vertigo	13–5	0.06	33%	19 Apr →
dust2	13–8	0.07	22%	19 Apr →
dust2	12–12	-0.01	13%	15 Apr →
vertigo	12–12	0.02	22%	15 Apr →
office	13–11	0.10	27%	15 Apr →
vertigo	13–10	-0.03	10%	14 Apr →
dust2	6–13	-0.02	29%	14 Apr →
vertigo	4–13	0.00	24%	14 Apr →