p1ckle — CS2 Stats

76561199085917413[U:1:1125651685]Steam profile ↗✓ No bans

268Tracked matches54%Win rate2020Tracked since

CSDB Rating6.8 SolidAggressive Rifler

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim91

Positioning62

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY51–43–6Last 10051%Win rateLLLWWLWWLW

Last 10 vs previous 10: -10pp win rate · -0.02 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim9.1

Aggression8.9

Utility5.2

Positioning6.2

Opening Duels3.4

Clutch4.2

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 b1t 94% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: higher opening-fight frequency.

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

Strengths

Aim. Aim score of 91 — the mechanical foundation is a clear strength.

Areas to improve

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

Aim9.1

Positioning6.2

Utility5.2

Mechanics7.0

Opening Duels3.4

Win Impact6.2

Composite 6.8/10 (Solid), 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 rating0.04+0.02

first ⅓ avg 0.02 → last ⅓ avg 0.04

Reaction time522ms−56ms

first ⅓ avg 579ms → last ⅓ avg 522ms

Headshot accuracy20.0%+3.7%

first ⅓ avg 16.3% → last ⅓ avg 20.0%

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

0.21Best rating — inferno 9–0

13–0Biggest win — train

6Longest win streak

L3Current streak

3–6In matches decided by ≤2 rounds

3Overtime games

Map breakdown

vertigoBest map · 86% over 7dust2Weakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	18	10–8	56%	0.01
inferno	A	15	9–6	60%	0.06
cache	S	15	10–5	67%	0.05
ancient	D	12	4–8	33%	-0.00
overpass	B	8	4–4	50%	0.02
vertigo	S	7	6–1	86%	0.03
dust2	D	7	1–6	14%	-0.01
nuke	S	6	4–2	67%	0.04
train	C	5	2–3	40%	0.04
anubis	—	4	0–4	0%	-0.01
office	—	3	1–2	33%	0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

21Matches

52%Win rate

1.29Avg K/D

81.0ADR

39%Headshot %

Clutches & streaks

41%1v1 clutch win

14%1v2 clutch win

4Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	6	50%	1.51	16.5
Anubis	3	33%	0.93	16.3
Nuke	3	33%	1.40	19.3
Mirage	3	100%	1.82	15.7
Ancient	3	67%	1.24	12.7
Inferno	1	0%	0.94	17.0

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.

19.1%Headshot accuracy

41.4%Accuracy (enemy spotted)

46.8%Spray accuracy

81.6%Counter-strafing

8.1°Preaim

525msReaction time

41.9%T opening success

45.2%CT opening success

0.60Enemies flashed / flash

8.9%Flash assists

15.76HE damage / grenade

3.82Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.8231 — below the 4 mark we flag
Grenade Lineups →

Spend your practice time on Dust 2

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	8–13	0.00	18%	26 Jul →
ancient	7–13	-0.02	8%	17 Jul →
inferno	8–13	0.09	20%	17 Jul →
ancient	13–9	0.02	6%	16 Jul →
inferno	13–5	0.08	38%	14 Jul →
anubis	10–13	-0.02	17%	11 Jul →
cache	13–9	0.00	12%	11 Jul →
ancient	13–7	0.06	24%	11 Jul →
office	6–13	-0.02	8%	9 Jul →
office	13–6	0.15	31%	9 Jul →
cache	12–12	0.13	21%	8 Jul →
vertigo	0–13	-0.05	25%	7 Jul →
cache	13–9	0.05	13%	7 Jul →
inferno	13–10	0.00	3%	7 Jul →
dust2	3–13	0.02	32%	7 Jul →
ancient	12–12	0.04	15%	7 Jul →
train	13–0	0.14	15%	6 Jul →
vertigo	13–11	0.08	14%	6 Jul →
cache	13–8	0.03	8%	6 Jul →
cache	13–7	0.08	13%	5 Jul →
train	9–13	0.06	26%	4 Jul →
mirage	7–13	-0.10	31%	4 Jul →
office	6–13	-0.00	42%	3 Jul →
inferno	9–3	0.14	13%	3 Jul →
dust2	5–13	-0.04	21%	2 Jul →
ancient	4–13	-0.05	16%	2 Jul →
vertigo	13–6	0.09	12%	29 Jun →
vertigo	4–1	-0.05	33%	29 Jun →
mirage	13–1	0.06	47%	29 Jun →
cache	13–5	0.02	12%	29 Jun →
nuke	9–5	0.11	29%	29 Jun →
inferno	9–1	0.19	12%	29 Jun →
ancient	1–13	-0.07	25%	28 Jun →
cache	12–12	-0.03	16%	28 Jun →
mirage	13–10	0.04	41%	22 Jun →
inferno	13–9	0.02	20%	22 Jun →
mirage	2–13	-0.05	16%	22 Jun →
ancient	8–13	-0.01	16%	19 Jun →
inferno	10–13	-0.03	7%	10 Jun →
mirage	9–13	0.01	22%	10 Jun →
mirage	13–5	0.04	21%	10 Jun →
mirage	5–13	0.06	10%	8 Jun →
inferno	3–13	0.02	35%	8 Jun →
overpass	13–10	0.01	8%	5 Jun →
cache	13–11	0.10	25%	5 Jun →
anubis	6–13	-0.06	21%	29 May →
cache	7–13	0.08	24%	28 May →
inferno	16–13	-0.01	13%	28 May →
anubis	5–13	0.05	25%	28 May →
overpass	15–15	0.08	17%	27 May →
anubis	7–13	-0.02	18%	27 May →
cache	13–8	-0.02	14%	24 May →
vertigo	13–9	0.03	11%	24 May →
mirage	11–13	-0.00	10%	23 May →
inferno	11–13	0.00	13%	23 May →
train	10–13	0.01	43%	23 May →
cache	13–7	0.11	20%	23 May →
overpass	4–13	-0.02	6%	23 May →
cache	11–13	0.02	30%	22 May →
cache	13–7	0.11	38%	22 May →
mirage	13–7	-0.03	18%	22 May →
ancient	13–3	0.15	17%	22 May →
ancient	13–4	0.01	9%	22 May →
vertigo	13–9	0.02	20%	21 May →
cache	12–12	-0.00	10%	21 May →
mirage	13–9	-0.01	10%	21 May →
overpass	13–8	0.01	24%	21 May →
ancient	5–13	-0.10	14%	18 May →
overpass	10–13	0.01	16%	18 May →
cache	13–2	0.07	9%	18 May →
dust2	14–16	0.04	17%	7 Aug →
nuke	10–13	0.02	33%	7 Aug →
ancient	3–13	-0.03	4%	3 Aug →
vertigo	9–6	0.07	21%	2 Aug →
nuke	9–4	0.08	13%	2 Aug →
mirage	5–13	-0.08	0%	1 Aug →
dust2	13–10	-0.04	7%	31 Jul →
overpass	10–13	-0.04	15%	27 Jul →
dust2	6–13	-0.06	24%	27 Jul →
train	9–13	-0.07	14%	26 Jul →
inferno	9–0	0.21	21%	26 Jul →
nuke	13–2	0.03	8%	24 Jul →
ancient	11–13	-0.06	11%	23 Jul →
overpass	13–1	0.12	15%	22 Jul →
dust2	11–13	-0.03	28%	21 Jul →
mirage	6–13	0.06	15%	20 Jul →
inferno	13–5	0.07	24%	20 Jul →
dust2	12–12	0.06	17%	20 Jul →
mirage	13–11	0.08	10%	20 Jul →
mirage	13–10	-0.02	6%	17 Jul →
overpass	13–8	-0.03	10%	17 Jul →
nuke	13–9	0.01	35%	17 Jul →
mirage	13–6	-0.05	15%	17 Jul →
inferno	5–13	0.03	19%	17 Jul →
mirage	13–8	0.13	30%	17 Jul →
mirage	13–6	0.00	16%	13 Jul →
nuke	4–13	-0.01	23%	13 Jul →
mirage	8–13	0.01	23%	13 Jul →
inferno	9–6	0.01	11%	10 Jul →
train	13–7	0.08	14%	30 Jun →