Pickle (❀ •̀ᴗ•́ )🥒 — CS2 Stats

US76561198005092673[U:1:44826945]Steam profile ↗✓ No bans

932Tracked matches44%Win rate2024Tracked since

2,685Hours in CS36Hrs last 2 wks

CSDB Rating5.2 DevelopingHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim85

Positioning46

Utility35

0–100 skill scores via Leetify.

Recent form

STEADY33–54–13Last 10033%Win rateLWLWLTLWTW

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

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim8.5

Aggression4.9

Utility3.5

Positioning4.6

Opening Duels1.0

Sharp aimerLimited utility dependence

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 88% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower positioning profile; 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

Areas to improve

Positioning. Positioning trails aim by 39 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.

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

Aim8.5

Positioning4.6

Utility3.5

Mechanics5.7

Opening Duels1.0

Win Impact3.0

Composite 5.2/10 (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 rating0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg 0.00

Reaction time542ms−110ms

first ⅓ avg 652ms → last ⅓ avg 542ms

Headshot accuracy29.5%+2.2%

first ⅓ avg 27.3% → last ⅓ avg 29.5%

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

0.18Best rating — inferno 9–3

13–3Biggest win — dust2

4Longest win streak

6–6In matches decided by ≤2 rounds

1Overtime games

Map breakdown

trainBest map · 40% over 5cacheWeakest map · 9% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	50	19–31	38%	0.00
cache	D	11	1–10	9%	0.00
office	C	8	3–5	38%	0.00
mirage	D	8	1–7	13%	-0.01
inferno	D	7	2–5	29%	0.00
train	C	5	2–3	40%	-0.03
vertigo	—	4	2–2	50%	0.02
ancient	—	3	1–2	33%	-0.01
anubis	—	3	2–1	67%	0.00
overpass	—	1	0–1	0%	-0.08

Across the last 100 tracked matches.

Lifetime stats

81,320Lifetime kills

1.02K/D

3,307Matches

46.3%Match win rate · Top 50% of tracked players

49.0%Headshot % · Top 50% of tracked players

15.4%Shot accuracy · Top 50% of tracked players

7,853MVPs

1,451Hours (in match)

1,500Bombs planted

836Bombs defused

Most-used weapons

SSG 0829,220

Desert Eagle14,845

P2507,965

AK-477,012

M4A4 / M4A1-S5,281

P2000 / USP-S3,947

AWP3,250

Glock-182,635

P901,350

HE Grenade944

Lifetime map wins

22,109dust2

2,008nuke

1,897inferno

1,242office

541train

422vertigo

131italy

67cbble

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

Faceit stats

Combat

8Matches

38%Win rate

1.27Avg K/D

—ADR

38%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

1Longest win streak

Recent Faceit resultsWLWLL

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.

29.1%Headshot accuracy

33.0%Accuracy (enemy spotted)

32.2%Spray accuracy

75.5%Counter-strafing

6.7°Preaim

536msReaction time

34.4%T opening success

34.0%CT opening success

0.44Enemies flashed / flash

3.0%Flash assists

11.96HE damage / grenade

2.88Flashes / 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 0.4373 — below the 0.5 mark we flag
Grenade Lineups →
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 34.3916% — below the 40% mark we flag

Spend your practice time on Cache

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

9% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
dust2	10–13	-0.01	27%	26 Aug →
dust2	13–5	0.07	29%	26 Aug →
office	6–13	-0.02	32%	26 Aug →
office	13–8	0.00	26%	26 Aug →
overpass	1–13	-0.08	14%	26 Aug →
mirage	12–12	-0.06	21%	26 Aug →
dust2	5–13	-0.04	24%	25 Aug →
dust2	13–4	-0.00	22%	25 Aug →
dust2	12–12	0.01	61%	25 Aug →
dust2	13–6	0.04	21%	25 Aug →
dust2	12–12	-0.03	35%	25 Aug →
dust2	13–8	-0.06	24%	25 Aug →
dust2	13–9	-0.01	27%	25 Aug →
dust2	12–12	0.07	22%	25 Aug →
dust2	7–13	0.06	21%	24 Aug →
dust2	11–13	0.07	34%	24 Aug →
dust2	13–5	0.06	33%	24 Aug →
dust2	12–12	0.03	22%	24 Aug →
dust2	11–13	-0.02	31%	24 Aug →
dust2	8–13	0.04	37%	24 Aug →
dust2	11–13	-0.05	27%	24 Aug →
dust2	8–0	0.03	60%	24 Aug →
dust2	10–13	-0.04	33%	24 Aug →
cache	5–13	-0.01	16%	24 Aug →
ancient	8–13	0.04	29%	24 Aug →
ancient	13–11	0.01	27%	23 Aug →
dust2	13–16	-0.05	21%	23 Aug →
dust2	13–7	-0.00	38%	20 Aug →
office	4–13	-0.09	39%	20 Aug →
office	13–7	0.16	29%	20 Aug →
dust2	13–9	0.02	43%	20 Aug →
dust2	3–13	-0.04	19%	20 Aug →
dust2	11–13	-0.06	26%	19 Aug →
dust2	12–12	-0.00	33%	19 Aug →
dust2	8–13	0.05	37%	19 Aug →
dust2	9–13	0.01	46%	19 Aug →
dust2	13–8	0.03	34%	18 Aug →
dust2	13–10	-0.05	26%	18 Aug →
dust2	13–11	-0.02	18%	18 Aug →
inferno	9–3	0.18	21%	18 Aug →
dust2	8–13	0.01	35%	18 Aug →
dust2	9–13	0.01	31%	18 Aug →
dust2	10–13	0.05	30%	17 Aug →
dust2	3–13	-0.00	42%	17 Aug →
dust2	13–10	-0.01	53%	17 Aug →
office	12–12	0.11	42%	16 Aug →
office	1–7	-0.05	33%	16 Aug →
vertigo	13–6	0.03	36%	16 Aug →
mirage	9–13	-0.00	36%	16 Aug →
train	13–4	-0.03	28%	16 Aug →
inferno	11–13	0.03	20%	16 Aug →
dust2	13–10	0.03	36%	14 Aug →
dust2	12–12	-0.00	36%	14 Aug →
dust2	10–13	-0.05	31%	14 Aug →
dust2	13–9	-0.02	23%	14 Aug →
mirage	4–13	-0.01	24%	14 Aug →
cache	3–13	0.03	22%	14 Aug →
dust2	13–11	0.02	23%	14 Aug →
cache	12–12	0.03	18%	14 Aug →
anubis	13–4	0.04	12%	14 Aug →
train	12–12	-0.04	9%	14 Aug →
cache	13–8	0.04	16%	14 Aug →
mirage	3–13	-0.02	15%	13 Aug →
cache	8–13	0.02	39%	13 Aug →
inferno	5–13	-0.00	24%	13 Aug →
dust2	13–11	-0.06	16%	13 Aug →
mirage	5–0	0.07	17%	13 Aug →
ancient	8–13	-0.09	20%	13 Aug →
train	10–13	-0.08	26%	12 Aug →
dust2	6–13	0.00	33%	10 Aug →
dust2	8–13	0.03	34%	10 Aug →
dust2	12–12	-0.02	35%	10 Aug →
dust2	13–3	0.05	39%	10 Aug →
office	13–9	-0.03	24%	10 Aug →
train	13–10	-0.01	40%	10 Aug →
anubis	3–13	-0.02	37%	10 Aug →
vertigo	11–13	0.03	28%	10 Aug →
mirage	12–12	0.01	38%	10 Aug →
inferno	6–13	-0.04	32%	10 Aug →
dust2	11–1	0.03	21%	10 Aug →
vertigo	13–11	0.06	28%	6 Aug →
vertigo	4–13	-0.03	14%	31 Jul →
office	6–13	-0.06	26%	26 Jul →
cache	8–13	0.04	21%	26 Jul →
mirage	12–12	-0.03	21%	26 Jul →
dust2	3–13	-0.00	26%	26 Jul →
cache	1–13	-0.09	29%	3 Jun →
cache	6–13	0.02	18%	3 Jun →
dust2	9–13	-0.03	27%	3 Jun →
train	3–13	-0.01	19%	3 Jun →
inferno	6–13	-0.04	50%	3 Jun →
cache	9–13	0.03	28%	3 Jun →
anubis	13–9	-0.01	26%	3 Jun →
dust2	6–13	-0.06	23%	20 May →
cache	4–13	-0.03	18%	20 May →
inferno	13–11	-0.05	20%	18 May →
inferno	7–13	-0.05	28%	16 May →
mirage	9–13	-0.06	17%	16 May →
cache	7–13	-0.04	13%	16 May →
dust2	9–13	-0.00	42%	16 May →