Been Geek — CS2 Stats

76561198170208377[U:1:209942649]✓ No bans

446Tracked matches52%Win rate2022Tracked since
CSDB Rating6.4 SolidAggressive Rifler
Ladder ranks via Leetify

Performance scores

Aim74
Positioning52
Utility66

0–100 skill scores via Leetify.

Recent form

STEADY49474Last 10049%Win rateLLLWLLLWWW

Last 10 vs previous 10: -20pp win rate · -0.00 avg rating

Player DNA

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

Aim7.4
Aggression7.5
Utility6.6
Positioning5.2
Opening Duels3.4
Clutch1.0

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

b1t

Plays most like b1t 91% playstyle similarity

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

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. 618ms 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

Aim7.4
Positioning5.2
Utility6.6
Mechanics8.1
Opening Duels3.4
Win Impact5.6

Composite 6.4/10 (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 rating0.01+0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time595ms−1ms
first ⅓ avg 596ms → last ⅓ avg 595ms
Headshot accuracy23.0%+0.0%
first ⅓ avg 23.0% → last ⅓ avg 23.0%

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

0.15Best rating — cache 13–4
131Biggest win — inferno
5Longest win streak
L3Current streak
124In matches decided by ≤2 rounds
7Overtime games

Map breakdown

nukeBest map · 67% over 6ancientWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
infernoA27151256%0.01
mirageC1881044%0.00
cacheA116555%0.03
overpassA95456%-0.01
ancientC83538%0.01
nukeS64267%0.00
anubisB63350%0.00
officeC52340%-0.01
train42250%0.02
vertigo3030%-0.00
dust231233%0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

58Matches
62%Win rate
1.18Avg K/D
85.7ADR
47%Headshot %

Clutches & streaks

25%1v1 clutch win
38%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno1753%1.1717.1
Mirage1250%1.0716.4
Train6100%1.6416.7
Ancient560%1.2219.0
Anubis450%0.9312.0
Dust2450%1.1618.5
Nuke3100%1.1717.3
Overpass367%1.1317.7

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.

22.6%Headshot accuracy
33.9%Accuracy (enemy spotted)
38.1%Spray accuracy
86.6%Counter-strafing
10.7°Preaim
618msReaction time
46.5%T opening success
40.4%CT opening success
0.55Enemies flashed / flash
8.7%Flash assists
13.67HE damage / grenade
12.12Flashes / match

Recommended for you

Spend your practice time on Ancient

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.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
inferno0–8-0.0550%18 Aug
inferno11–13-0.0429%2 Jul
ancient8–13-0.0719%2 Jul
cache13–30.0743%2 Jul
vertigo10–130.0121%8 Jun
vertigo8–13-0.0111%8 Jun
inferno7–13-0.0316%3 Jun
cache13–110.0216%2 Jun
mirage13–70.1317%28 May
mirage13–70.0515%26 May
cache4–13-0.0312%23 May
cache4–13-0.0919%22 May
cache4–130.0424%19 May
mirage13–50.000%14 May
mirage13–50.0133%12 May
mirage9–130.0629%11 May
mirage6–0-0.0636%11 May
cache13–90.0616%11 May
cache13–100.0832%9 May
cache13–30.0230%9 May
cache13–40.1526%9 May
cache0–30.0017%9 May
mirage9–13-0.0530%7 May
mirage5–13-0.0613%4 May
cache12–120.019%3 May
overpass13–110.0518%27 Apr
office11–130.0127%27 Apr
train13–110.0232%24 Apr
nuke13–90.0025%24 Apr
mirage19–170.0019%23 Apr
mirage13–60.0127%22 Apr
anubis8–13-0.0322%20 Apr
mirage6–13-0.0326%20 Apr
anubis9–13-0.0130%20 Apr
inferno13–1-0.0325%20 Apr
dust25–130.0150%20 Apr
dust213–80.0032%20 Apr
inferno13–110.0722%20 Apr
nuke13–11-0.0015%20 Apr
inferno13–100.0730%20 Apr
mirage10–10.0620%20 Apr
mirage6–130.0135%20 Apr
inferno6–130.0917%20 Apr
mirage12–12-0.0517%18 Apr
overpass6–13-0.0921%18 Apr
inferno13–90.0528%16 Apr
inferno5–130.0837%15 Apr
overpass13–80.0822%15 Apr
ancient13–90.1328%14 Apr
inferno16–140.0220%13 Apr
inferno13–4-0.0312%31 Mar
inferno6–13-0.0622%31 Mar
ancient13–70.0620%31 Mar
train9–130.0331%27 Mar
inferno13–7-0.0619%27 Mar
ancient8–13-0.0310%27 Mar
nuke7–130.0018%24 Mar
inferno12–12-0.0124%23 Mar
office13–3-0.0140%23 Mar
mirage5–130.0114%23 Mar
dust212–120.018%23 Mar
ancient7–13-0.0418%23 Mar
vertigo3–13-0.0114%23 Mar
overpass9–13-0.0619%23 Mar
train13–50.0512%23 Mar
inferno13–160.0518%19 Mar
overpass13–11-0.0624%19 Mar
ancient4–13-0.0218%19 Mar
inferno13–110.0525%19 Mar
office5–13-0.0325%18 Mar
office13–6-0.0629%18 Mar
anubis13–100.0314%17 Mar
overpass16–130.0015%17 Mar
anubis13–7-0.0427%17 Mar
overpass7–13-0.0019%17 Mar
inferno13–110.0118%17 Mar
inferno13–70.0117%13 Mar
nuke6–13-0.0611%13 Mar
ancient13–160.0315%13 Mar
anubis16–140.0318%12 Mar
ancient13–60.0319%12 Mar
overpass13–40.0123%12 Mar
nuke13–9-0.0024%12 Mar
inferno12–160.0318%11 Mar
inferno8–13-0.0526%10 Mar
inferno13–70.0516%6 Mar
overpass9–130.0016%6 Mar
mirage11–13-0.0550%6 Mar
nuke13–30.0621%6 Mar
inferno13–10.0724%6 Mar
inferno10–130.069%2 Mar
office5–130.0130%27 Feb
inferno13–110.0144%19 Feb
train11–13-0.0217%6 Feb
mirage8–13-0.0136%6 Feb
inferno10–130.0427%6 Feb
mirage4–130.0022%3 Feb
anubis8–130.0435%3 Feb
inferno13–90.0528%3 Feb
inferno13–8-0.0522%10 Oct

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 →