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Gucci Bane

Gucci Bane — CS2 Stats

US76561198057531919[U:1:97266191]Steam profile ↗

785Tracked matches46%Win rate2023Tracked since
CSDB Rating3.6 Learning
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGGucci BaneFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim42
Positioning36
Utility40

0–100 skill scores via Leetify.

Recent form

COLD44–46–10Last 10044%Win rateLWLLWLTLTW

Last 10 vs previous 10: -20pp win rate · +0.01 avg rating

Player DNA

Aim4.2
Aggression3.8
Utility4.0
Positioning3.6
Opening Duels0.0

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

NiKo

Plays most like NiKo 71% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower opening-duel success; 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. 612ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.2
Positioning3.6
Utility4.0
Mechanics4.0
Opening Duels0.5
Win Impact3.8

Composite 3.6/10 (Learning), 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-0.03−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time610ms−54ms
first ⅓ avg 664ms → last ⅓ avg 610ms
Headshot accuracy17.5%+2.3%
first ⅓ avg 15.2% → last ⅓ avg 17.5%

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

0.06Best rating — dust2 13–4
13–2Biggest win — mirage
4Longest win streak
3–4In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 67% over 6dust2Weakest map · 27% over 22
MapGradePlayedRecordWin rateAvg rating
dust2D226–1627%-0.03
anubisA138–562%-0.02
infernoC135–838%-0.03
ancientA116–555%-0.01
vertigoC114–736%-0.02
cacheC83–538%-0.04
trainA74–357%-0.03
mirageS64–267%-0.03
nukeD62–433%-0.02
overpass—32–167%-0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (27% over 22). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6Matches
33%Win rate
0.84Avg K/D
—ADR
40%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
1Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Vertigo10%1.0813.0
Anubis1100%1.009.0
Inferno10%1.0814.0
Mirage10%1.0013.0
Dust21100%0.6710.0

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.

17.5%Headshot accuracy
28.3%Accuracy (enemy spotted)
23.8%Spray accuracy
68.1%Counter-strafing
8.4°Preaim
612msReaction time
33.6%T opening success
24.7%CT opening success
0.57Enemies flashed / flash
6.0%Flash assists
3.67HE damage / grenade
6.63Flashes / 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. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 33.6442% — below the 40% mark we flag

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.

27% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis9–13-0.0315%28 Aug →
mirage13–20.0226%28 Aug →
dust22–13-0.0519%27 Aug →
dust21–4-0.0025%27 Aug →
mirage13–4-0.0523%26 Jul →
ancient8–13-0.0619%26 Jul →
nuke12–12-0.0115%26 Jul →
dust27–13-0.0116%22 Jul →
mirage12–12-0.029%22 Jul →
anubis13–3-0.0616%18 Jul →
inferno13–7-0.1014%18 Jul →
vertigo13–2-0.0519%18 Jul →
cache13–3-0.0312%4 Jul →
inferno10–13-0.0412%18 Jun →
cache7–13-0.0818%14 Jun →
vertigo11–130.0015%10 Jun →
anubis7–13-0.0612%27 May →
inferno13–40.0526%25 May →
dust23–13-0.0823%25 May →
mirage13–4-0.0325%16 May →
ancient7–13-0.0613%16 May →
nuke8–13-0.038%16 May →
ancient13–5-0.0518%12 May →
cache13–8-0.0024%12 May →
cache13–60.0023%12 May →
anubis9–130.0020%9 May →
dust28–130.0428%9 May →
anubis13–4-0.0127%9 May →
ancient13–3-0.059%9 May →
inferno3–13-0.1413%9 May →
nuke4–13-0.0413%8 May →
dust213–8-0.0715%8 May →
inferno8–13-0.059%6 May →
cache6–13-0.0223%6 May →
dust213–90.0312%6 May →
ancient13–40.037%1 May →
cache7–13-0.1213%1 May →
cache12–12-0.0516%29 Apr →
cache3–13-0.0323%29 Apr →
vertigo10–13-0.0413%27 Apr →
inferno4–13-0.0319%27 Apr →
vertigo13–11-0.046%27 Apr →
inferno11–13-0.0224%26 Apr →
train7–13-0.0519%26 Apr →
nuke13–3-0.0525%26 Apr →
ancient13–50.048%26 Apr →
anubis13–100.0422%23 Apr →
vertigo10–130.0119%21 Apr →
dust213–9-0.0017%21 Apr →
inferno12–12-0.0718%17 Apr →
vertigo12–4-0.014%11 Apr →
ancient7–130.0329%11 Apr →
inferno13–8-0.0213%11 Apr →
anubis7–130.0110%11 Apr →
ancient3–13-0.0415%10 Apr →
dust21–13-0.0422%10 Apr →
nuke13–50.0520%4 Apr →
dust26–13-0.0616%4 Apr →
dust28–13-0.0518%13 Mar →
inferno12–12-0.0324%1 Nov →
dust212–12-0.099%1 Nov →
dust212–12-0.065%30 Oct →
vertigo12–12-0.0015%23 Oct →
vertigo13–70.0516%22 Oct →
anubis13–10-0.0224%22 Oct →
anubis13–7-0.1212%21 Oct →
anubis5–13-0.0612%19 Oct →
dust25–13-0.143%11 Oct →
anubis13–20.0216%11 Oct →
vertigo7–13-0.0417%11 Oct →
ancient13–110.0110%11 Oct →
train13–50.0218%9 Oct →
dust213–20.0225%9 Oct →
ancient11–130.0214%9 Oct →
train9–13-0.0715%8 Oct →
dust26–13-0.066%8 Oct →
mirage12–12-0.0312%4 Oct →
train13–40.0417%4 Oct →
dust25–13-0.0321%4 Oct →
train2–13-0.069%2 Oct →
dust212–12-0.0516%2 Oct →
inferno5–100.0613%2 Oct →
anubis13–80.037%1 Oct →
train13–5-0.0321%1 Oct →
inferno13–4-0.005%1 Oct →
vertigo4–13-0.0828%27 Sept →
dust213–10-0.028%27 Sept →
overpass13–6-0.0515%27 Sept →
dust28–13-0.0812%27 Sept →
vertigo11–13-0.0617%27 Sept →
mirage13–2-0.0421%26 Sept →
train13–9-0.0319%26 Sept →
dust210–130.0126%26 Sept →
dust213–40.069%26 Sept →
ancient13–6-0.0117%25 Sept →
overpass10–130.0122%25 Sept →
overpass13–11-0.0420%24 Sept →
nuke7–13-0.0212%23 Sept →
inferno13–40.0212%21 Sept →
anubis13–50.0221%20 Sept →

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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