PEEKASSO — CS2 Stats

76561198117820619[U:1:157554891]

1,439Tracked matches62%Win rate2020Tracked since

CSDB Rating3.5 Learning

FaceitLevel 6Top 54.0% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim35

Positioning59

Utility8

0–100 skill scores via Leetify.

Recent form

STEADY45–51–4Last 10045%Win rateWLLWLLWWLW

Last 10 vs previous 10: -20pp win rate · -0.04 avg rating

Player DNA

Aim3.5

Aggression7.5

Utility0.8

Positioning5.9

Opening Duels2.3

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 74% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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. 577ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 0% 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

Aim3.5

Positioning5.9

Utility0.8

Mechanics0.0

Opening Duels2.3

Win Impact9.0

Composite 3.5/10 (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 rating0.03−0.02

first ⅓ avg 0.05 → last ⅓ avg 0.03

Reaction time583ms−20ms

first ⅓ avg 603ms → last ⅓ avg 583ms

Headshot accuracy12.0%−0.2%

first ⅓ avg 12.3% → last ⅓ avg 12.0%

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

0.16Best rating — inferno 13–9

13–1Biggest win — italy

4Longest win streak

7–9In matches decided by ≤2 rounds

9Overtime games

Map breakdown

cacheBest map · 71% over 7infernoWeakest map · 33% over 18

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	24	9–15	38%	0.04
inferno	D	18	6–12	33%	0.05
ancient	D	12	4–8	33%	0.03
anubis	C	9	4–5	44%	0.04
cache	S	7	5–2	71%	0.02
mirage	A	7	4–3	57%	0.03
nuke	A	5	3–2	60%	0.07
overpass	A	5	3–2	60%	0.03
office	—	4	3–1	75%	0.04
italy	—	4	2–2	50%	0.05
alpine	—	2	0–2	0%	-0.01
train	—	2	1–1	50%	-0.03
warden	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

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

12.0%Headshot accuracy

26.5%Accuracy (enemy spotted)

0.0%Spray accuracy

0.0%Counter-strafing

9.5°Preaim

577msReaction time

42.4%T opening success

36.1%CT opening success

0.14Enemies flashed / flash

7.4%Flash assists

5.67HE damage / grenade

0.43Flashes / 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.

Movement Guide
Under half your shots are taken fully stopped, so the bullets are going where the spread sends them rather than where you aim.
Counter-strafing 0% — below the 45% mark we flag
Practice Config →
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 11.9985% — below the 15% mark we flag
Aim Training →
Advanced Mechanics
Sustained sprays are missing more than they land, which is a recoil-control pattern you can drill directly.
Spray accuracy 0% — below the 20% mark we flag
Practice Config →

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.

33% win rate across 18 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
ancient	13–9	0.02	8%	22 Aug →
inferno	6–13	-0.05	17%	28 Jun →
alpine	4–13	-0.03	12%	28 Jun →
cache	13–7	0.02	11%	28 Jun →
office	3–13	-0.05	10%	28 Jun →
inferno	9–13	0.02	9%	24 Jun →
nuke	16–12	0.06	10%	24 Jun →
train	13–3	-0.00	2%	18 Jun →
alpine	9–13	0.02	12%	18 Jun →
office	8–0	0.05	14%	18 Jun →
cache	13–7	0.06	8%	17 Jun →
office	13–9	0.08	10%	17 Jun →
inferno	8–13	-0.02	8%	17 Jun →
italy	6–13	0.05	7%	5 Jun →
cache	13–10	0.02	9%	5 Jun →
office	13–10	0.07	21%	3 Jun →
warden	13–4	0.04	26%	3 Jun →
italy	10–13	0.04	14%	3 Jun →
cache	13–6	0.02	14%	3 Jun →
italy	13–1	0.09	11%	24 May →
cache	12–12	-0.04	19%	24 May →
cache	13–10	0.06	14%	4 May →
cache	8–13	-0.04	8%	29 Apr →
dust2	13–7	0.16	13%	14 Apr →
inferno	8–13	0.10	13%	14 Apr →
ancient	13–9	0.09	14%	10 Apr →
dust2	13–6	0.11	11%	10 Apr →
dust2	13–4	0.16	8%	8 Apr →
italy	13–8	0.03	22%	8 Apr →
train	6–13	-0.06	3%	8 Apr →
inferno	4–13	0.02	9%	29 Mar →
inferno	5–13	0.00	16%	23 Mar →
mirage	2–13	0.02	13%	23 Mar →
anubis	13–11	0.04	9%	23 Mar →
anubis	5–13	-0.01	14%	23 Mar →
inferno	11–13	-0.02	11%	22 Mar →
dust2	13–7	0.03	12%	22 Mar →
inferno	13–10	0.10	11%	22 Mar →
overpass	13–8	0.03	14%	22 Mar →
inferno	3–13	0.03	13%	22 Mar →
dust2	7–13	-0.03	13%	21 Mar →
overpass	8–13	0.04	4%	21 Mar →
mirage	13–8	0.02	6%	21 Mar →
ancient	8–13	-0.00	10%	21 Mar →
mirage	3–13	-0.06	10%	19 Mar →
mirage	13–5	0.04	17%	19 Mar →
dust2	14–16	0.09	10%	19 Mar →
dust2	6–13	0.01	15%	19 Mar →
dust2	10–13	-0.03	7%	18 Mar →
dust2	4–13	-0.01	11%	18 Mar →
overpass	13–8	0.09	4%	18 Mar →
nuke	13–4	0.12	12%	18 Mar →
inferno	13–6	0.09	11%	18 Mar →
dust2	12–16	0.01	13%	16 Mar →
ancient	6–13	-0.00	19%	16 Mar →
overpass	13–10	-0.05	7%	15 Mar →
dust2	9–13	-0.00	8%	15 Mar →
mirage	4–13	0.05	12%	12 Mar →
dust2	5–13	-0.05	6%	12 Mar →
inferno	11–13	0.03	12%	9 Mar →
dust2	11–13	0.02	8%	9 Mar →
dust2	13–8	0.07	13%	9 Mar →
dust2	11–13	0.01	14%	8 Mar →
dust2	16–14	0.10	15%	8 Mar →
mirage	16–14	0.05	10%	8 Mar →
dust2	5–13	0.04	11%	8 Mar →
anubis	7–13	0.09	9%	8 Mar →
inferno	3–13	-0.02	20%	6 Mar →
anubis	13–9	0.07	5%	6 Mar →
ancient	7–13	-0.00	7%	6 Mar →
mirage	13–5	0.13	5%	6 Mar →
nuke	11–13	-0.00	3%	6 Mar →
inferno	7–13	0.05	10%	6 Mar →
ancient	9–13	-0.02	10%	6 Mar →
anubis	13–9	0.04	8%	5 Mar →
inferno	10–13	0.09	8%	5 Mar →
nuke	13–11	0.14	17%	5 Mar →
dust2	5–13	0.02	23%	4 Mar →
inferno	13–11	0.14	10%	4 Mar →
dust2	11–13	0.09	12%	4 Mar →
dust2	13–11	0.02	16%	4 Mar →
anubis	13–7	0.06	14%	3 Mar →
ancient	15–15	0.08	7%	3 Mar →
ancient	10–13	0.08	6%	3 Mar →
dust2	15–15	0.04	7%	2 Mar →
ancient	9–2	0.09	15%	2 Mar →
inferno	13–9	0.16	15%	2 Mar →
ancient	15–15	0.00	16%	1 Mar →
anubis	13–16	-0.01	14%	1 Mar →
inferno	13–6	0.07	30%	1 Mar →
dust2	10–13	0.01	14%	1 Mar →
nuke	11–13	0.02	12%	28 Feb →
dust2	13–11	0.07	6%	28 Feb →
anubis	11–13	0.06	8%	28 Feb →
overpass	6–13	0.04	11%	28 Feb →
ancient	7–13	-0.06	12%	28 Feb →
dust2	13–8	0.13	22%	28 Feb →
anubis	9–13	0.03	13%	28 Feb →
inferno	13–5	0.08	16%	27 Feb →
ancient	13–6	0.07	11%	27 Feb →