MoronPunk_Paid_Actor — CS2 Stats

76561198079031957[U:1:118766229]

1,738Tracked matches55%Win rate2020Tracked since

CSDB Rating6.2 SolidHybrid Rifler

Premier CS Rating17,385Purple band · top ~18.9% of ranked players (population est.)

CSDB Leaderboard#20649 of 39415 tracked

FaceitLevel 3 · 770 ELOTop 90.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim63

Positioning64

Utility57

0–100 skill scores via Leetify.

Recent form

STEADY53–41–6Last 10053%Win rateLLLLWWWWWL

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

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

Aim6.3

Aggression9.4

Utility5.7

Positioning6.4

Opening Duels4.9

Clutch3.4

Strong CT-side opener

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 sh1ro 90% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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

T-side openings. Opening success drops from 58% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 582ms 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

Aim6.3

Positioning6.4

Utility5.7

Mechanics6.5

Opening Duels4.9

Win Impact6.7

Composite 6.2/10 (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 rating-0.00−0.00

first ⅓ avg 0.00 → last ⅓ avg -0.00

Reaction time591ms−66ms

first ⅓ avg 657ms → last ⅓ avg 591ms

Headshot accuracy12.5%−0.7%

first ⅓ avg 13.1% → last ⅓ avg 12.5%

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

0.10Best rating — inferno 13–6

13–0Biggest win — anubis

5Longest win streak

L4Current streak

3–9In matches decided by ≤2 rounds

11Overtime games

Map breakdown

infernoBest map · 65% over 26dust2Weakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	26	17–9	65%	0.00
ancient	B	25	12–13	48%	-0.01
nuke	B	22	11–11	50%	-0.01
cache	B	8	4–4	50%	-0.01
dust2	C	8	3–5	38%	0.01
anubis	C	7	3–4	43%	-0.00
mirage	—	2	1–1	50%	0.04
train	—	1	1–0	100%	0.02
vertigo	—	1	1–0	100%	-0.07

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

230Matches

47%Win rate

0.96Avg K/D

79.1ADR

35%Headshot %

Clutches & streaks

37%1v1 clutch win

19%1v2 clutch win

6Longest win streak

Recent Faceit resultsWLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	56	43%	0.85	13.7
Inferno	53	49%	1.01	15.6
Anubis	31	48%	0.92	14.5
Ancient	31	39%	0.98	16.1
Nuke	29	52%	1.01	16.3
Vertigo	9	33%	1.08	16.4
Dust2	8	75%	0.87	13.8
Train	7	71%	1.33	18.4

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.

12.4%Headshot accuracy

36.7%Accuracy (enemy spotted)

36.3%Spray accuracy

79.2%Counter-strafing

10.7°Preaim

582msReaction time

41.3%T opening success

58.3%CT opening success

0.63Enemies flashed / flash

7.1%Flash assists

10.25HE damage / grenade

5.89Flashes / 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.

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 12.3766% — below the 15% mark we flag
Aim Training →

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.

38% win rate across 8 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
nuke	11–13	-0.00	5%	29 Aug →
nuke	6–13	-0.06	13%	29 Aug →
anubis	9–13	-0.03	16%	29 Aug →
nuke	4–13	0.05	8%	29 Aug →
inferno	13–9	0.04	9%	29 Aug →
ancient	13–2	-0.08	12%	29 Aug →
ancient	13–9	0.03	8%	28 Aug →
inferno	13–7	-0.06	27%	28 Aug →
inferno	13–4	0.00	13%	28 Aug →
ancient	4–13	-0.05	5%	27 Aug →
cache	13–9	-0.02	10%	27 Aug →
inferno	13–4	0.01	10%	27 Aug →
nuke	13–10	-0.02	11%	26 Aug →
ancient	14–16	0.00	7%	26 Aug →
ancient	13–7	-0.01	20%	26 Aug →
anubis	13–0	0.08	12%	25 Aug →
nuke	2–13	0.01	8%	25 Aug →
ancient	14–16	0.02	22%	25 Aug →
ancient	11–13	-0.00	4%	20 Aug →
nuke	15–15	-0.03	13%	20 Aug →
inferno	13–4	-0.00	16%	20 Aug →
ancient	13–8	0.01	11%	19 Aug →
cache	16–12	-0.02	16%	18 Aug →
anubis	10–13	-0.02	21%	18 Aug →
ancient	6–13	-0.05	6%	18 Aug →
anubis	13–5	0.01	20%	18 Aug →
inferno	9–13	-0.02	19%	16 Aug →
dust2	13–10	-0.03	11%	14 Aug →
nuke	14–16	0.08	7%	14 Aug →
inferno	13–10	0.05	11%	14 Aug →
nuke	13–6	0.01	11%	13 Aug →
nuke	13–10	0.00	15%	13 Aug →
ancient	8–13	-0.02	16%	13 Aug →
inferno	16–13	-0.00	8%	13 Aug →
inferno	3–13	-0.08	0%	12 Aug →
ancient	13–9	0.03	8%	12 Aug →
dust2	10–13	0.02	25%	12 Aug →
nuke	7–13	-0.01	5%	12 Aug →
inferno	13–3	0.08	10%	12 Aug →
train	13–5	0.02	7%	11 Aug →
inferno	13–4	0.09	5%	11 Aug →
inferno	12–12	-0.04	21%	11 Aug →
inferno	9–13	-0.01	15%	11 Aug →
inferno	6–13	-0.09	14%	11 Aug →
ancient	7–0	-0.01	13%	11 Aug →
nuke	16–12	-0.03	16%	11 Aug →
ancient	13–10	-0.02	9%	9 Aug →
ancient	4–13	-0.07	6%	9 Aug →
anubis	6–13	-0.05	2%	9 Aug →
nuke	13–5	0.03	9%	9 Aug →
dust2	13–11	-0.03	7%	9 Aug →
nuke	10–13	0.01	11%	9 Aug →
ancient	9–13	-0.05	7%	7 Aug →
nuke	16–14	0.02	8%	7 Aug →
ancient	5–13	-0.01	4%	7 Aug →
inferno	13–6	-0.00	13%	7 Aug →
ancient	13–8	0.06	14%	7 Aug →
cache	5–13	-0.08	7%	6 Aug →
nuke	13–4	-0.05	8%	6 Aug →
vertigo	13–10	-0.07	11%	6 Aug →
inferno	13–6	0.10	14%	6 Aug →
dust2	7–13	0.02	8%	6 Aug →
inferno	13–4	-0.02	8%	6 Aug →
inferno	9–13	-0.01	19%	6 Aug →
mirage	13–2	0.09	8%	6 Aug →
inferno	13–16	-0.01	18%	5 Aug →
nuke	13–7	0.01	2%	4 Aug →
inferno	6–13	-0.03	15%	4 Aug →
inferno	13–6	0.05	12%	4 Aug →
ancient	13–9	0.04	9%	4 Aug →
cache	13–2	0.01	18%	3 Aug →
nuke	13–10	0.01	17%	1 Aug →
inferno	13–6	0.02	3%	1 Aug →
cache	14–16	-0.03	11%	31 Jul →
inferno	13–8	0.04	20%	30 Jul →
ancient	11–13	0.02	9%	30 Jul →
cache	10–13	0.03	16%	29 Jul →
nuke	13–11	-0.05	5%	29 Jul →
inferno	13–10	0.07	18%	29 Jul →
mirage	6–13	-0.01	7%	29 Jul →
dust2	13–8	0.09	26%	29 Jul →
nuke	1–13	-0.03	10%	29 Jul →
nuke	12–12	-0.02	11%	28 Jul →
cache	13–5	0.06	29%	28 Jul →
nuke	13–5	-0.04	19%	27 Jul →
anubis	13–10	-0.00	8%	27 Jul →
dust2	11–13	0.03	8%	27 Jul →
inferno	13–7	-0.04	7%	24 Jul →
inferno	1–13	-0.05	7%	24 Jul →
ancient	11–13	-0.03	13%	24 Jul →
ancient	13–9	0.03	13%	23 Jul →
anubis	12–12	-0.02	14%	23 Jul →
dust2	2–13	-0.04	11%	23 Jul →
nuke	15–15	-0.02	17%	23 Jul →
ancient	13–3	0.03	19%	23 Jul →
cache	10–13	-0.04	14%	23 Jul →
ancient	13–6	0.00	9%	22 Jul →
ancient	10–13	-0.05	11%	22 Jul →
ancient	5–13	-0.02	12%	21 Jul →
dust2	12–12	0.02	18%	21 Jul →