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bug — CS2 Stats

76561199089849599[U:1:1129583871]

378Tracked matches55%Win rate2020Tracked since
CSDB Rating5.9 SolidHybrid Rifler
Premier CS Rating11,754Blue band · top ~45.6% of ranked players (population est.)
CSDB Leaderboard#23435 of 33493 tracked
WingmanGold Nova III
Ladder ranks via Leetify

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CSDB.GGbugPREMIER11,754 · Blue bandcsdb.gg/stats

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Performance scores

Aim64
Positioning63
Utility64

0–100 skill scores via Leetify.

Recent form

STEADY43–50–7Last 10043%Win rateWLWTLWLLWL

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.

Aim6.4
Aggression7.7
Utility6.4
Positioning6.3
Opening Duels3.5

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

b1t

Plays most like b1t 93% playstyle similarity

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

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

Reaction time. 596ms 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

Aim6.4
Positioning6.3
Utility6.4
Mechanics6.7
Opening Duels3.5
Win Impact6.7

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03−0.00
first ⅓ avg 0.03 → last ⅓ avg 0.03
Reaction time592ms−25ms
first ⅓ avg 617ms → last ⅓ avg 592ms
Headshot accuracy9.0%−0.2%
first ⅓ avg 9.2% → last ⅓ avg 9.0%

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

0.36Best rating — inferno 9–2
13–0Biggest win — anubis
5Longest win streak
2–4In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 67% over 9anubisWeakest map · 25% over 16
MapGradePlayedRecordWin rateAvg rating
anubisD164–1225%0.00
dust2B158–753%0.00
infernoB147–750%0.03
mirageC114–736%0.00
ancientC94–544%0.04
cacheS96–367%0.04
vertigoD72–529%0.01
trainS64–267%0.06
nukeC52–340%0.02
officeC52–340%0.04
overpass—30–30%0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (25% over 16). 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.

9.8%Headshot accuracy
38.4%Accuracy (enemy spotted)
43.4%Spray accuracy
80.1%Counter-strafing
11.6°Preaim
596msReaction time
43.9%T opening success
44.2%CT opening success
0.62Enemies flashed / flash
6.4%Flash assists
13.70HE damage / grenade
10.97Flashes / 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. 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 9.8272% — below the 15% mark we flag

    Aim Training →
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.

25% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
train13–100.109%10 Aug →
vertigo1–13-0.050%2 Aug →
vertigo13–70.2014%2 Aug →
anubis12–120.0514%28 Jul →
overpass6–13-0.027%27 Jul →
dust213–80.0413%27 Jul →
dust26–13-0.047%26 Jul →
inferno6–9-0.054%26 Jul →
dust213–10-0.0211%26 Jul →
dust23–8-0.020%25 Jul →
anubis13–00.075%25 Jul →
anubis8–13-0.064%24 Jul →
anubis8–13-0.0110%23 Jul →
dust26–130.067%18 Jul →
ancient8–130.0517%18 Jul →
mirage13–20.079%18 Jul →
inferno13–7-0.019%18 Jul →
cache13–100.1212%18 Jul →
ancient9–130.0511%18 Jul →
mirage7–13-0.0012%18 Jul →
inferno9–70.045%17 Jul →
cache13–100.048%16 Jul →
overpass9–130.088%14 Jul →
cache13–7-0.0412%12 Jul →
dust213–9-0.0316%12 Jul →
ancient13–70.108%12 Jul →
cache13–30.0814%12 Jul →
dust213–10-0.025%12 Jul →
inferno8–130.0512%12 Jul →
anubis13–10-0.033%12 Jul →
ancient13–40.0413%11 Jul →
nuke8–130.0313%11 Jul →
mirage13–40.036%11 Jul →
mirage14–160.029%11 Jul →
cache13–50.0712%11 Jul →
inferno3–9-0.116%11 Jul →
mirage16–14-0.048%11 Jul →
dust28–13-0.018%11 Jul →
dust25–13-0.028%11 Jul →
cache15–150.028%11 Jul →
dust212–160.0111%11 Jul →
inferno6–9-0.069%10 Jul →
inferno5–13-0.074%10 Jul →
anubis7–130.045%10 Jul →
vertigo3–11-0.096%10 Jul →
ancient13–60.047%10 Jul →
office13–30.0811%9 Jul →
office5–13-0.019%8 Jul →
mirage13–90.036%3 Jul →
cache5–13-0.0713%2 Jul →
cache13–50.0814%2 Jul →
nuke11–130.038%2 Jul →
mirage10–130.107%30 Jun →
anubis13–40.0310%28 Jun →
dust213–00.0810%28 Jun →
mirage1–9-0.110%28 Jun →
overpass7–13-0.029%28 Jun →
dust27–130.015%27 Jun →
nuke10–130.007%27 Jun →
anubis2–13-0.095%27 Jun →
mirage6–13-0.0114%27 Jun →
ancient3–13-0.0012%27 Jun →
ancient11–13-0.026%27 Jun →
inferno5–130.009%27 Jun →
nuke13–60.025%27 Jun →
dust213–40.038%27 Jun →
inferno9–10.206%27 Jun →
train13–80.0511%19 Jun →
train4–13-0.025%19 Jun →
train8–30.129%18 Jun →
inferno9–20.3620%14 Jun →
mirage9–13-0.0114%14 Jun →
dust213–9-0.018%14 Jun →
inferno13–30.026%14 Jun →
inferno9–50.065%13 Jun →
anubis12–120.017%13 Jun →
office13–20.054%12 Jun →
anubis13–80.079%9 Jun →
office8–13-0.0314%9 Jun →
office10–130.119%8 Jun →
ancient10–40.0816%8 Jun →
cache12–120.1013%7 Jun →
inferno13–30.0611%7 Jun →
ancient9–13-0.018%7 Jun →
nuke13–100.029%7 Jun →
mirage7–13-0.0911%6 Jun →
vertigo10–13-0.067%4 Jun →
vertigo0–13-0.039%4 Jun →
vertigo13–40.0613%3 Jun →
inferno12–12-0.015%3 Jun →
dust210–30.004%2 Jun →
train6–13-0.0118%1 Jun →
vertigo9–130.035%1 Jun →
anubis6–13-0.0012%30 May →
anubis12–120.039%30 May →
anubis11–130.057%30 May →
anubis6–13-0.056%29 May →
anubis12–12-0.075%27 May →
anubis7–130.039%27 May →
train13–100.095%23 May →

Match data via Leetify.

Recent teammates

Milestones

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

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