cub — CS2 Stats

76561198316767215[U:1:356501487]Steam profile ↗✓ No bans

307Tracked matches33%Win rate2020Tracked since

CSDB Rating2.7 Learning

Ladder ranks via Leetify

Performance scores

Aim18

Positioning52

Utility16

0–100 skill scores via Leetify.

Recent form

COLD32–60–8Last 10032%Win rateLLLTWLLLWL

Last 10 vs previous 10: -20pp win rate · -0.03 avg rating

Player DNA

Aim1.8

Aggression6.2

Utility1.6

Positioning5.2

Opening Duels1.9

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 b1t 73% playstyle similarity

Most alike: opening-fight frequency, 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

Reaction time. 716ms 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

Aim1.8

Positioning5.2

Utility1.6

Mechanics4.6

Opening Duels1.9

Win Impact0.0

Composite 2.7/10 (Learning), 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+0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time710ms+2ms

first ⅓ avg 708ms → last ⅓ avg 710ms

Headshot accuracy12.4%−2.4%

first ⅓ avg 14.8% → last ⅓ avg 12.4%

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

0.11Best rating — overpass 11–2

13–2Biggest win — cache

4Longest win streak

L3Current streak

4–5In matches decided by ≤2 rounds

Map breakdown

overpassBest map · 56% over 9trainWeakest map · 17% over 12

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	15	6–9	40%	-0.02
train	D	12	2–10	17%	-0.02
cache	D	11	2–9	18%	-0.02
anubis	D	11	2–9	18%	-0.02
overpass	A	9	5–4	56%	-0.01
dust2	C	9	4–5	44%	-0.03
ancient	D	7	2–5	29%	-0.03
inferno	D	7	2–5	29%	-0.02
nuke	C	5	2–3	40%	-0.05
office	C	5	2–3	40%	-0.05
vertigo	D	5	1–4	20%	-0.05
grail	—	3	1–2	33%	0.02
italy	—	1	1–0	100%	-0.02

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.

12.3%Headshot accuracy

25.4%Accuracy (enemy spotted)

32.6%Spray accuracy

70.6%Counter-strafing

13.1°Preaim

716msReaction time

33.4%T opening success

42.0%CT opening success

0.40Enemies flashed / flash

0.9%Flash assists

3.40HE damage / grenade

2.61Flashes / 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 13.0907° — 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 12.2613% — below the 15% mark we flag
Aim Training →
Best CS2 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 716.4286ms — above the 700ms 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 12 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
cache	3–13	-0.05	10%	28 Aug →
ancient	11–13	-0.00	12%	21 Aug →
mirage	10–13	-0.06	11%	20 Aug →
nuke	12–12	-0.13	10%	20 Aug →
train	13–11	-0.03	14%	14 Aug →
train	5–13	0.06	12%	14 Aug →
train	10–13	-0.03	8%	12 Aug →
mirage	10–13	-0.02	10%	5 Aug →
anubis	13–11	-0.05	9%	22 Jul →
anubis	2–13	-0.05	23%	22 Jul →
overpass	13–5	-0.06	21%	12 Jul →
cache	13–2	-0.04	4%	11 Jul →
cache	4–13	-0.01	5%	1 Jul →
cache	7–13	-0.05	15%	1 Jul →
cache	9–13	-0.02	17%	1 Jul →
mirage	11–13	-0.05	15%	24 Jun →
train	12–12	0.01	9%	23 Jun →
cache	13–9	0.08	17%	14 Jun →
anubis	3–13	-0.06	4%	21 May →
overpass	11–2	0.11	18%	20 May →
nuke	13–9	-0.05	7%	20 May →
office	3–13	-0.05	7%	13 May →
office	8–13	-0.07	18%	13 May →
cache	4–13	0.01	15%	6 May →
cache	10–13	-0.01	11%	6 May →
cache	8–13	-0.06	13%	6 May →
cache	11–13	-0.05	13%	29 Apr →
ancient	13–7	0.01	11%	29 Apr →
cache	12–12	-0.03	16%	29 Apr →
dust2	13–11	0.00	14%	26 Apr →
train	7–13	-0.06	4%	22 Apr →
inferno	12–12	-0.03	21%	16 Apr →
ancient	6–13	-0.01	17%	15 Apr →
dust2	13–7	0.01	13%	13 Apr →
vertigo	13–3	-0.03	2%	8 Apr →
vertigo	10–13	-0.02	10%	8 Apr →
vertigo	0–7	-0.09	0%	8 Apr →
mirage	13–6	-0.06	17%	26 Mar →
ancient	7–13	-0.03	18%	4 Mar →
inferno	3–10	0.00	21%	4 Mar →
overpass	6–13	-0.06	16%	27 Feb →
nuke	6–13	-0.10	20%	27 Feb →
inferno	12–12	-0.08	6%	27 Feb →
dust2	7–13	-0.13	10%	27 Feb →
mirage	13–7	0.05	15%	20 Feb →
inferno	13–7	0.01	15%	17 Feb →
anubis	10–13	0.03	10%	4 Feb →
anubis	9–13	-0.02	16%	4 Feb →
mirage	13–4	0.05	13%	29 Jan →
nuke	6–13	0.03	21%	28 Jan →
office	13–10	0.02	17%	21 Jan →
ancient	6–13	-0.12	12%	17 Jan →
overpass	13–6	0.01	13%	17 Jan →
mirage	7–13	-0.02	17%	7 Jan →
overpass	9–5	-0.02	10%	7 Jan →
mirage	6–13	0.08	22%	7 Jan →
train	13–6	0.05	16%	1 Jan →
dust2	9–13	-0.03	26%	11 Dec →
train	10–13	0.03	17%	11 Dec →
mirage	4–13	0.00	8%	11 Dec →
nuke	13–9	0.03	27%	11 Dec →
anubis	12–12	-0.10	12%	10 Dec →
mirage	13–4	-0.03	9%	3 Dec →
dust2	13–10	0.00	12%	3 Dec →
inferno	13–8	-0.01	16%	19 Nov →
overpass	13–9	-0.04	36%	19 Nov →
overpass	6–13	0.04	26%	12 Nov →
train	1–13	-0.12	17%	7 Nov →
train	8–13	-0.11	9%	7 Nov →
ancient	13–11	-0.04	26%	5 Nov →
mirage	10–13	-0.12	20%	29 Oct →
mirage	13–7	0.00	18%	29 Oct →
dust2	2–13	-0.07	8%	26 Oct →
inferno	9–13	0.02	25%	26 Oct →
vertigo	11–13	-0.01	17%	22 Oct →
vertigo	12–12	-0.09	10%	22 Oct →
anubis	13–6	-0.01	12%	15 Oct →
anubis	2–13	-0.02	12%	15 Oct →
inferno	0–13	-0.04	8%	8 Oct →
mirage	1–13	-0.04	10%	8 Oct →
train	9–13	0.03	12%	8 Oct →
dust2	13–5	-0.03	11%	8 Oct →
office	2–13	-0.10	14%	1 Oct →
office	13–9	-0.06	15%	1 Oct →
overpass	8–13	0.01	23%	24 Sept →
overpass	0–10	-0.07	25%	24 Sept →
italy	13–10	-0.02	17%	17 Sept →
train	1–13	-0.06	11%	17 Sept →
dust2	12–12	0.07	15%	17 Sept →
ancient	9–13	-0.02	11%	17 Sept →
train	5–13	-0.05	12%	10 Sept →
mirage	10–13	-0.06	4%	8 Sept →
mirage	13–8	-0.02	10%	3 Sept →
anubis	6–13	0.07	17%	3 Sept →
dust2	6–13	-0.06	17%	3 Sept →
grail	13–7	0.10	20%	27 Aug →
grail	4–13	-0.04	12%	27 Aug →
grail	2–13	-0.01	17%	27 Aug →
anubis	11–13	0.05	15%	21 Aug →
anubis	8–13	-0.02	21%	20 Aug →