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𝐆𝐋𝐀𝐃𝐘𝐒 ᛅ — CS2 Stats

76561199488286215[U:1:1528020487]✓ No bans

678Tracked matches55%Win rate2023Tracked since
CSDB Rating6.2 SolidAggressive Rifler
Ladder ranks via Leetify

Performance scores

Aim72
Positioning56
Utility49

0–100 skill scores via Leetify.

Recent form

STEADY57–40–3Last 10057%Win rateTLLWWLLWWW

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

Player DNA

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

Aim7.2
Aggression8.7
Utility4.9
Positioning5.6
Opening Duels3.8

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

ropz

Plays most like ropz 89% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: higher opening-fight frequency; 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

Reaction time. 614ms 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

Aim7.2
Positioning5.6
Utility4.9
Mechanics7.5
Opening Duels3.8
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 rating0.00+0.01
first ⅓ avg -0.01 → last ⅓ avg 0.00
Reaction time616ms+1ms
first ⅓ avg 615ms → last ⅓ avg 616ms
Headshot accuracy20.4%−1.6%
first ⅓ avg 22.0% → last ⅓ avg 20.4%

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

0.13Best rating — anubis 13–4
13–0Biggest win — inferno
6Longest win streak
8–5In matches decided by ≤2 rounds
7Overtime games

Map breakdown

ancientBest map · 67% over 9anubisWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
infernoA2616–1062%0.00
dust2A2515–1060%0.00
mirageA1810–856%-0.00
ancientS96–367%-0.01
anubisC83–538%-0.00
overpassA74–357%-0.02
nuke—32–167%-0.03
train—20–20%-0.04
cache—21–150%-0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Anubis 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.

20.4%Headshot accuracy
33.9%Accuracy (enemy spotted)
36.8%Spray accuracy
83.8%Counter-strafing
9.7°Preaim
614msReaction time
42.5%T opening success
47.8%CT opening success
0.47Enemies flashed / flash
2.1%Flash assists
11.16HE damage / grenade
6.11Flashes / 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 0.4746 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Anubis

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.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno15–150.0120%4 Aug →
inferno5–13-0.0519%4 Aug →
anubis4–13-0.0216%4 Aug →
anubis13–40.1319%4 Aug →
dust213–6-0.0121%4 Aug →
dust24–13-0.0612%4 Aug →
dust25–12-0.0716%2 Aug →
dust213–10-0.0718%6 Jul →
mirage13–60.1323%5 Jul →
dust213–70.0220%5 Jul →
anubis13–5-0.0218%27 Jun →
inferno13–1-0.0015%27 Jun →
dust211–130.0337%27 Jun →
nuke16–13-0.0719%27 Jun →
train5–13-0.0628%23 Jun →
inferno5–13-0.0525%9 Jun →
dust213–100.0430%27 May →
inferno13–30.1225%25 May →
ancient13–70.0713%25 May →
dust213–60.1031%22 May →
dust214–16-0.0423%17 May →
nuke13–110.0018%17 May →
ancient3–13-0.0523%17 May →
anubis11–130.0210%12 May →
nuke5–13-0.0214%12 May →
ancient1–13-0.1310%12 May →
dust213–70.0215%8 May →
inferno13–00.1230%8 May →
cache13–90.0016%8 May →
cache5–13-0.0126%6 May →
inferno13–11-0.0614%6 May →
dust210–13-0.0030%6 May →
dust210–130.0122%6 May →
inferno13–20.0627%22 Apr →
dust213–20.0431%22 Apr →
inferno7–13-0.0912%21 Apr →
dust29–13-0.0621%17 Apr →
anubis8–13-0.0317%17 Apr →
inferno13–7-0.0218%15 Apr →
ancient13–7-0.0418%12 Apr →
mirage13–50.0712%12 Apr →
dust213–8-0.0416%12 Apr →
mirage6–13-0.0711%9 Apr →
ancient13–110.0831%5 Apr →
ancient13–10-0.0518%1 Apr →
anubis4–13-0.0124%1 Apr →
dust210–13-0.0324%30 Mar →
mirage3–13-0.0324%25 Mar →
inferno7–13-0.0126%25 Mar →
inferno13–50.0923%24 Mar →
inferno15–150.0626%24 Mar →
ancient13–60.0311%24 Mar →
dust28–13-0.0217%19 Mar →
inferno13–7-0.0138%19 Mar →
overpass13–8-0.0315%19 Mar →
inferno13–6-0.0143%13 Mar →
inferno10–13-0.0134%13 Mar →
mirage8–13-0.0218%13 Mar →
dust213–80.0023%13 Mar →
inferno13–10-0.0711%4 Mar →
inferno13–110.0523%4 Mar →
dust213–110.0618%2 Mar →
anubis13–6-0.0017%2 Mar →
mirage13–7-0.0122%2 Mar →
inferno8–13-0.0224%1 Mar →
overpass13–70.0320%1 Mar →
ancient15–15-0.0015%1 Mar →
mirage13–11-0.0515%22 Feb →
inferno9–13-0.0311%21 Feb →
overpass11–13-0.0821%21 Feb →
inferno9–13-0.0129%21 Feb →
inferno13–10-0.0223%15 Feb →
mirage13–30.0816%12 Feb →
dust213–70.0016%12 Feb →
mirage9–130.0126%7 Feb →
mirage13–60.0232%7 Feb →
inferno13–2-0.0514%5 Feb →
mirage10–13-0.0220%1 Feb →
overpass6–13-0.0424%1 Feb →
dust213–90.0420%29 Jan →
mirage5–13-0.0714%29 Jan →
mirage13–80.0121%29 Jan →
mirage10–13-0.0532%26 Jan →
mirage13–70.0219%25 Jan →
mirage7–13-0.0829%25 Jan →
ancient13–90.0022%25 Jan →
inferno16–120.0432%25 Jan →
overpass13–4-0.0134%25 Jan →
anubis11–13-0.0923%22 Jan →
dust213–30.0814%14 Jan →
overpass4–13-0.0229%14 Jan →
overpass13–10-0.0127%11 Jan →
train10–13-0.0224%9 Jan →
mirage13–11-0.0033%8 Jan →
inferno13–4-0.0311%6 Jan →
dust213–90.0420%6 Jan →
inferno13–20.0222%6 Jan →
dust24–13-0.0314%4 Jan →
mirage13–80.0217%4 Jan →
dust216–140.0120%4 Jan →

Match data via Leetify.

Recent teammates

Milestones

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

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