monkey — CS2 Stats

76561199826160348[U:1:1865894620]

70Tracked matches83%Win rate2025Tracked since
CSDB Rating7.0 StrongAggressive Rifler
Ladder ranks via Leetify

Performance scores

Aim82
Positioning62
Utility36

0–100 skill scores via Leetify.

Recent form

HOT46231Last 7066%Win rateWWWLWWWWWW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim8.2
Aggression10.0
Utility3.6
Positioning6.2
Opening Duels5.4

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

device

Plays most like device 88% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: lower aim 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

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 59% on CT to 44% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 663ms 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

Aim8.2
Positioning6.2
Utility3.6
Mechanics8.4
Opening Duels5.4
Win Impact10.0

Composite 7.0/10 (Strong), 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 rating0.06−0.01
first ⅓ avg 0.07 → last ⅓ avg 0.06
Reaction time666ms+7ms
first ⅓ avg 659ms → last ⅓ avg 666ms
Headshot accuracy26.0%+4.3%
first ⅓ avg 21.6% → last ⅓ avg 26.0%

Rolling 5-match average across the last 70 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.33Best rating — inferno 13–3
130Biggest win — dust2
9Longest win streak
W3Current streak

Map breakdown

infernoBest map · 85% over 13nukeWeakest map · 50% over 8
MapGradePlayedRecordWin rateAvg rating
dust2S2013765%0.04
mirageA159660%0.04
infernoS1311285%0.11
nukeB84450%0.08
ancientB63350%-0.00
overpass330100%0.07
anubis21150%0.03
train220100%0.13
vertigo1010%0.04

Across the last 70 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (50% over 8). Start with the 6 essential Nuke 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.

23.2%Headshot accuracy
37.8%Accuracy (enemy spotted)
38.7%Spray accuracy
87.7%Counter-strafing
8.6°Preaim
663msReaction time
44.0%T opening success
59.0%CT opening success
0.56Enemies flashed / flash
6.5%Flash assists
9.53HE damage / grenade
8.03Flashes / match

Recent matches

MapScoreRatingHS%Date
inferno13–80.0120%9 Apr
dust213–60.0725%9 Apr
inferno13–90.2517%9 Apr
nuke3–130.0926%6 Apr
ancient13–10-0.0725%6 Apr
anubis13–30.0053%6 Apr
ancient7–20.0730%6 Apr
mirage8–10.1250%6 Apr
dust213–5-0.018%6 Apr
inferno13–20.0440%6 Apr
nuke6–130.1128%6 Apr
mirage6–00.0525%6 Apr
ancient8–130.0217%5 Apr
overpass13–10.0527%27 Jul
mirage13–50.0018%27 Jul
mirage1–13-0.0328%26 Jul
nuke13–70.0734%22 Jul
overpass13–40.0816%22 Jul
dust213–80.0215%22 Apr
dust213–00.0115%16 Apr
mirage13–40.0824%16 Apr
train13–70.0927%16 Apr
inferno13–00.2230%16 Apr
dust213–1-0.0229%16 Apr
dust213–60.0612%12 Apr
inferno2–130.0516%12 Apr
dust211–40.0113%12 Apr
ancient13–50.0517%7 Apr
dust212–120.1923%7 Apr
inferno13–20.0815%7 Apr
overpass13–30.0912%7 Apr
dust213–110.0221%7 Apr
dust28–130.0823%7 Apr
dust24–13-0.0419%27 Mar
mirage3–13-0.0315%27 Mar
nuke13–50.0815%26 Mar
mirage2–130.027%26 Mar
mirage1–13-0.0975%25 Mar
mirage13–10-0.0410%25 Mar
ancient4–13-0.0410%25 Mar
mirage5–13-0.0228%25 Mar
inferno13–30.094%25 Mar
anubis9–130.0516%24 Mar
inferno13–30.0923%24 Mar
mirage13–110.0420%24 Mar
inferno13–30.0931%24 Mar
nuke13–40.1723%24 Mar
vertigo11–130.0416%24 Mar
mirage13–80.2024%24 Mar
nuke4–13-0.0432%24 Mar
train13–70.1723%24 Mar
nuke13–80.0420%24 Mar
dust210–13-0.1520%3 Mar
dust213–30.0728%3 Mar
inferno0–13-0.130%2 Mar
nuke10–130.0924%2 Mar
dust27–13-0.0413%2 Mar
dust213–50.0423%2 Mar
dust213–2-0.069%1 Mar
ancient4–13-0.037%16 Feb
inferno13–60.0023%16 Feb
dust26–13-0.0040%14 Feb
mirage1–13-0.0330%14 Feb
mirage13–10.1525%14 Feb
dust28–10.1721%14 Feb
inferno13–30.3322%14 Feb
mirage13–50.2028%14 Feb
dust211–20.0822%14 Feb
dust23–130.2118%14 Feb
inferno13–50.3129%14 Feb

Match data via Leetify.

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