Cap'n Burntbeard — CS2 Stats

SE76561197965637201[U:1:5371473]Steam profile ↗✓ No bans

158Tracked matches50%Win rate2020Tracked since

CSDB Rating4.0 Developing

Ladder ranks via Leetify

Performance scores

Aim43

Positioning37

Utility50

0–100 skill scores via Leetify.

Recent form

STEADY43–52–5Last 10043%Win rateLLWWWLWWLW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating

Player DNA

Aim4.3

Aggression3.4

Utility5.0

Positioning3.7

Opening Duels0.0

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 76% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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 39% on T to 20% on CT — first contacts on the defending side are being lost.

Reaction time. 608ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Positioning3.7

Utility5.0

Mechanics4.0

Opening Duels1.1

Win Impact5.0

Composite 4.0/10 (Developing), 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-0.03−0.02

first ⅓ avg -0.01 → last ⅓ avg -0.03

Reaction time612ms−21ms

first ⅓ avg 633ms → last ⅓ avg 612ms

Headshot accuracy13.1%+0.6%

first ⅓ avg 12.5% → last ⅓ avg 13.1%

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

0.07Best rating — inferno 13–7

13–1Biggest win — nuke

6Longest win streak

L2Current streak

7–9In matches decided by ≤2 rounds

13Overtime games

Map breakdown

infernoBest map · 50% over 36trainWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	36	18–18	50%	-0.02
nuke	B	20	9–11	45%	-0.03
anubis	C	17	7–10	41%	-0.02
ancient	D	9	3–6	33%	-0.02
overpass	B	8	4–4	50%	-0.04
train	D	6	1–5	17%	-0.02
cache	—	2	1–1	50%	-0.01
dust2	—	2	0–2	0%	-0.04

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

13.2%Headshot accuracy

35.3%Accuracy (enemy spotted)

37.5%Spray accuracy

67.9%Counter-strafing

13.1°Preaim

608msReaction time

38.9%T opening success

19.9%CT opening success

0.53Enemies flashed / flash

1.0%Flash assists

9.06HE damage / grenade

7.17Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.1254° — above the 12° mark we flag
Aim Training →
Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.2146% — below the 15% mark we flag
Aim Training →

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–16	-0.03	12%	27 Aug →
nuke	5–13	-0.12	0%	16 Aug →
inferno	13–10	-0.02	15%	16 Aug →
nuke	13–5	0.04	5%	31 Jul →
cache	16–12	0.02	14%	31 Jul →
anubis	10–13	-0.03	12%	26 Jul →
inferno	13–11	-0.06	8%	26 Jul →
inferno	13–8	-0.03	8%	24 Jul →
dust2	10–13	-0.05	5%	4 Jul →
ancient	16–13	-0.05	20%	4 Jul →
anubis	7–13	-0.01	25%	29 Jun →
inferno	9–13	-0.08	18%	29 Jun →
inferno	7–13	-0.07	25%	24 Jun →
overpass	13–10	-0.02	5%	22 Jun →
nuke	13–3	-0.06	14%	22 Jun →
anubis	9–13	-0.04	18%	21 Jun →
anubis	13–7	-0.02	13%	20 Jun →
nuke	13–5	-0.07	16%	20 Jun →
inferno	9–13	-0.03	4%	17 Jun →
anubis	11–13	-0.03	19%	17 Jun →
inferno	13–9	0.02	32%	17 Jun →
nuke	5–13	-0.09	17%	16 Jun →
inferno	8–13	-0.04	9%	16 Jun →
inferno	13–4	-0.04	17%	15 Jun →
anubis	10–13	-0.07	5%	15 Jun →
inferno	13–11	0.03	15%	15 Jun →
inferno	13–9	-0.03	10%	9 Jun →
nuke	11–13	-0.03	5%	9 Jun →
inferno	13–3	-0.01	19%	7 Jun →
anubis	7–13	-0.03	17%	7 Jun →
inferno	15–15	-0.01	13%	7 Jun →
overpass	7–13	-0.04	17%	23 May →
anubis	7–13	-0.05	6%	23 May →
inferno	11–13	-0.02	17%	21 May →
inferno	13–6	0.06	15%	16 May →
inferno	7–13	-0.07	7%	15 May →
overpass	10–13	-0.05	21%	15 May →
nuke	5–13	-0.03	16%	14 May →
inferno	8–13	-0.10	21%	14 May →
nuke	13–1	0.05	13%	11 Apr →
nuke	13–10	-0.04	9%	11 Apr →
anubis	13–11	-0.03	25%	6 Apr →
nuke	11–13	-0.02	17%	5 Apr →
inferno	16–12	-0.03	11%	5 Apr →
nuke	11–13	-0.00	15%	2 Apr →
inferno	8–13	-0.05	16%	2 Apr →
inferno	13–4	-0.07	38%	24 Aug →
train	16–13	0.06	16%	22 Aug →
inferno	14–16	0.00	22%	9 Aug →
ancient	7–13	0.01	15%	4 Aug →
overpass	13–10	-0.01	17%	23 Jul →
nuke	13–6	0.04	11%	23 Jul →
inferno	4–13	-0.06	14%	22 Jul →
train	4–13	0.01	13%	22 Jul →
train	11–13	-0.04	22%	21 Jul →
overpass	13–7	-0.05	22%	21 Jul →
overpass	13–11	-0.04	10%	20 Jul →
nuke	2–13	-0.09	13%	17 Jul →
anubis	7–13	-0.07	8%	4 Jul →
overpass	9–13	-0.04	21%	4 Jul →
overpass	10–13	-0.05	6%	3 Jul →
inferno	13–7	-0.07	6%	30 May →
ancient	6–13	-0.02	11%	26 Mar →
ancient	8–13	-0.00	14%	23 Mar →
inferno	16–14	0.01	15%	22 Mar →
nuke	10–13	-0.03	5%	22 Mar →
train	9–13	-0.05	11%	16 Mar →
nuke	8–13	-0.03	9%	16 Mar →
nuke	13–8	-0.01	26%	12 Mar →
anubis	13–8	0.01	9%	12 Mar →
ancient	10–13	-0.06	8%	11 Mar →
inferno	11–13	-0.05	9%	7 Mar →
inferno	13–6	-0.03	6%	4 Mar →
ancient	13–10	-0.01	4%	24 Feb →
inferno	16–12	0.01	9%	24 Feb →
anubis	13–8	-0.02	8%	23 Feb →
inferno	15–15	0.03	13%	23 Feb →
dust2	15–15	-0.04	17%	21 Feb →
nuke	13–10	-0.03	16%	21 Feb →
anubis	9–13	-0.01	12%	19 Feb →
train	9–13	-0.09	8%	19 Feb →
ancient	10–13	-0.02	9%	19 Feb →
anubis	13–1	0.06	12%	17 Feb →
inferno	11–13	-0.03	17%	17 Feb →
ancient	10–13	-0.00	21%	16 Feb →
nuke	3–13	-0.02	12%	16 Feb →
inferno	9–13	-0.09	11%	14 Feb →
nuke	9–13	-0.07	13%	14 Feb →
inferno	8–13	-0.02	32%	14 Feb →
inferno	15–15	-0.01	18%	14 Feb →
inferno	13–10	-0.02	15%	13 Feb →
anubis	4–13	0.01	14%	13 Feb →
inferno	13–7	0.07	11%	13 Feb →
inferno	13–7	0.04	15%	11 Feb →
anubis	13–9	-0.04	8%	11 Feb →
nuke	13–11	0.00	15%	10 Feb →
anubis	13–11	-0.00	9%	10 Feb →
ancient	13–8	-0.00	1%	9 Feb →
train	15–15	-0.03	12%	9 Feb →
inferno	7–13	0.02	14%	9 Feb →