Paco غوريلا تدخن

Paco غوريلا تدخن — CS2 Stats

AF76561198109539988[U:1:149274260]Steam profile ↗✓ No bans

1,617Tracked matches48%Win rate2020Tracked since
CSDB Rating6.0 SolidEntry Fragger
FaceitLevel 5 · 1,090 ELOTop 67.6% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

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CSDB.GGPaco غوريلا تدخنFACEITLevel 5 · 1,090 ELOSTANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim84
Positioning67
Utility49

0–100 skill scores via Leetify.

Recent form

COLD50455Last 10050%Win rateLWLLWLLLLL

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

Player DNA

Primary style: Entry FraggerHigh opening-fight frequency with above-par success in them.

Aim8.4
Aggression10.0
Utility4.9
Positioning6.7
Opening Duels6.9
Clutch4.2

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

s1mple

Plays most like s1mple 92% playstyle similarity

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

Where you differ: 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

Strengths

CT openings. 69% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 69% on CT to 46% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.4
Positioning6.7
Utility4.9
Mechanics6.3
Opening Duels6.9
Win Impact4.4

Composite 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.02
first ⅓ avg 0.01 → last ⅓ avg 0.03
Reaction time512ms−73ms
first ⅓ avg 585ms → last ⅓ avg 512ms
Headshot accuracy15.9%+2.1%
first ⅓ avg 13.8% → last ⅓ avg 15.9%

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

0.19Best rating — mirage 13–6
130Biggest win — dust2
6Longest win streak
62In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 63% over 8infernoWeakest map · 18% over 11
MapGradePlayedRecordWin rateAvg rating
dust2B41221954%0.04
cacheC125742%0.00
infernoD112918%-0.04
mirageA106460%0.03
nukeA85363%0.04
ancient43175%0.03
anubis330100%0.04
shelter31233%0.06
train21150%0.06
fachwerk1010%0.07
italy1010%0.02
office1010%0.00
overpass1010%-0.02
boulder110100%0.07
debris110100%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

75Matches
48%Win rate
1.31Avg K/D
96.5ADR
43%Headshot %

Clutches & streaks

41%1v1 clutch win
38%1v2 clutch win
6Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Dust23060%1.3920.1
Mirage2348%1.3618.4
Ancient1233%1.2119.1
Inferno633%1.2317.7
Train20%0.8914.0
Nuke250%0.8814.0

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.

15.5%Headshot accuracy
41.1%Accuracy (enemy spotted)
44.1%Spray accuracy
78.4%Counter-strafing
9.9°Preaim
507msReaction time
46.0%T opening success
69.1%CT opening success
0.47Enemies flashed / flash
6.4%Flash assists
9.59HE damage / grenade
7.76Flashes / 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.

  1. 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 0.4709 — below the 0.5 mark we flag

    Grenade Lineups
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.

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke6–9-0.0612%23 Aug
anubis13–110.0311%23 Aug
inferno6–90.0012%23 Aug
inferno3–9-0.1617%23 Aug
nuke9–40.0324%23 Aug
dust211–13-0.0527%23 Aug
dust23–130.0219%22 Aug
shelter4–130.1323%22 Aug
fachwerk6–130.0717%22 Aug
dust26–13-0.0510%22 Aug
dust213–40.087%22 Aug
dust29–130.1015%21 Aug
dust213–10.1515%21 Aug
dust27–30.039%21 Aug
inferno8–80.1512%21 Aug
inferno0–9-0.2215%21 Aug
italy9–130.0216%15 Aug
office10–130.0010%15 Aug
overpass0–13-0.0220%15 Aug
dust212–120.0820%14 Aug
dust25–130.1313%14 Aug
dust27–130.0618%13 Aug
dust213–80.1023%13 Aug
boulder13–80.075%13 Aug
dust26–130.0622%12 Aug
dust24–20.0140%12 Aug
train13–30.0714%12 Aug
shelter13–40.037%12 Aug
dust213–110.0313%8 Aug
inferno9–50.119%7 Aug
debris9–7-0.0114%7 Aug
inferno6–90.0219%7 Aug
dust213–90.0518%2 Aug
dust213–60.0114%2 Aug
cache8–13-0.0411%2 Aug
nuke2–130.0210%31 Jul
dust213–100.0511%31 Jul
dust213–90.1621%31 Jul
dust210–130.0319%31 Jul
dust213–100.0216%29 Jul
inferno13–80.0715%29 Jul
dust213–9-0.0015%29 Jul
dust213–20.058%29 Jul
anubis13–100.0314%22 Jul
anubis13–60.079%22 Jul
dust211–130.0414%21 Jul
dust26–130.0423%21 Jul
dust26–13-0.0319%19 Jul
cache5–13-0.0514%19 Jul
dust213–00.0319%19 Jul
dust26–130.0424%11 Jul
mirage13–110.0917%10 Jul
dust213–60.0324%10 Jul
train9–130.0522%10 Jul
cache8–130.0211%10 Jul
dust212–120.0622%10 Jul
shelter12–120.0120%10 Jul
dust29–130.0610%6 Jul
mirage7–130.0014%5 Jul
mirage15–150.0411%5 Jul
cache13–8-0.0324%3 Jul
cache13–90.0821%3 Jul
dust29–13-0.047%30 Jun
dust28–10.0620%29 Jun
cache2–13-0.0817%10 May
cache13–50.0923%10 May
ancient10–13-0.0320%10 May
nuke2–13-0.0313%9 May
dust212–16-0.0117%9 May
inferno3–9-0.0414%9 May
inferno1–9-0.170%9 May
inferno2–9-0.1329%7 May
dust213–110.0216%2 May
mirage13–6-0.0314%2 May
mirage13–60.1914%2 May
mirage4–130.007%2 May
cache4–13-0.1013%2 May
mirage13–9-0.029%30 Apr
dust29–20.0816%30 Apr
cache6–130.119%30 Apr
cache13–80.0913%29 Apr
cache0–13-0.0819%29 Apr
cache13–70.0411%29 Apr
ancient13–80.0518%27 Apr
dust25–13-0.107%27 Apr
dust26–130.0215%26 Apr
mirage13–00.0521%26 Apr
dust213–10-0.0115%26 Apr
inferno3–9-0.103%24 Apr
nuke9–40.1411%24 Apr
nuke9–20.0814%24 Apr
dust213–80.0216%24 Apr
ancient13–5-0.0214%24 Apr
nuke13–40.039%24 Apr
mirage10–13-0.0114%24 Apr
dust213–90.0215%23 Apr
ancient13–50.1324%23 Apr
mirage13–9-0.0116%22 Apr
nuke13–70.0922%22 Apr
dust213–80.047%22 Apr

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →