Funny Bricks

Funny Bricks — CS2 Stats

VE76561198216639917[U:1:256374189]Steam profile ↗✓ No bans

622Tracked matches31%Win rate2023Tracked since
CSDB Rating4.4 Developing
Ladder ranks via Leetify

Performance scores

Aim59
Positioning47
Utility31

0–100 skill scores via Leetify.

Recent form

COLD47476Last 10047%Win rateLLWLLLLLWW

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

Player DNA

Aim5.9
Aggression4.1
Utility3.1
Positioning4.7
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 75% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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. 665ms 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

Aim5.9
Positioning4.7
Utility3.1
Mechanics7.6
Opening Duels0.6
Win Impact0.0

Composite 4.4/10 (Developing), 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-0.02−0.03
first ⅓ avg 0.00 → last ⅓ avg -0.02
Reaction time674ms−9ms
first ⅓ avg 683ms → last ⅓ avg 674ms
Headshot accuracy17.3%−3.7%
first ⅓ avg 20.9% → last ⅓ avg 17.3%

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 — inferno 13–4
131Biggest win — nuke
6Longest win streak
L2Current streak
510In matches decided by ≤2 rounds
2Overtime games

Map breakdown

trainBest map · 71% over 7ancientWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
dust2B22101245%-0.01
infernoC1881044%-0.00
nukeC146843%-0.01
mirageC104640%-0.02
cacheC83538%-0.03
anubisA85363%-0.00
ancientD72529%-0.01
trainS75271%-0.02
vertigo42250%-0.03
overpass110100%-0.03
italy110100%0.09

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Ancient 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.

17.6%Headshot accuracy
30.5%Accuracy (enemy spotted)
31.2%Spray accuracy
84.2%Counter-strafing
8.5°Preaim
665msReaction time
24.1%T opening success
34.8%CT opening success
0.53Enemies flashed / flash
4.4%Flash assists
9.51HE damage / grenade
3.71Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.7148 — below the 4 mark we flag

    Grenade Lineups
  2. 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 24.1304% — below the 40% mark we flag

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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
cache1–13-0.0717%27 Aug
cache7–13-0.0630%16 Aug
inferno13–6-0.0427%11 Aug
mirage5–13-0.058%30 Jun
dust29–130.029%30 Jun
dust22–13-0.0428%28 Jun
inferno11–13-0.047%28 Jun
cache9–13-0.0422%14 Jun
cache13–9-0.0020%11 Jun
cache13–100.0217%10 Jun
cache3–13-0.039%25 May
anubis10–13-0.0516%25 May
nuke2–13-0.0925%21 May
cache13–9-0.0216%21 May
cache6–13-0.0214%13 May
dust26–13-0.0421%23 Feb
dust27–130.0020%24 Jan
inferno3–130.0123%14 Jan
anubis2–6-0.060%14 Jan
dust213–11-0.0128%14 Jan
vertigo4–13-0.038%20 Dec
ancient12–12-0.0717%20 Dec
anubis13–100.0220%28 Sept
mirage13–8-0.0215%28 Sept
ancient5–130.0120%23 Sept
inferno13–60.0413%23 Sept
inferno13–50.0220%30 Aug
dust24–13-0.0916%16 Jul
nuke4–130.0417%16 Jul
inferno7–13-0.0914%16 Jul
ancient13–9-0.0216%12 Jul
train13–90.0515%29 Jun
overpass13–11-0.0319%29 Jun
nuke13–90.029%29 Jun
anubis13–5-0.008%29 Jun
dust213–8-0.0421%29 Jun
nuke5–13-0.0613%14 Jun
dust25–130.0219%14 Jun
dust213–5-0.047%25 May
inferno13–50.0120%25 May
train13–10-0.0510%25 May
dust213–100.0121%7 May
nuke7–1-0.025%7 May
ancient12–12-0.005%7 May
nuke12–12-0.0216%2 May
inferno8–13-0.0317%2 May
vertigo3–13-0.0817%2 May
anubis13–7-0.0521%27 Apr
mirage5–13-0.0725%27 Apr
inferno13–90.0213%27 Apr
anubis13–100.0311%27 Apr
mirage11–13-0.0026%19 Apr
dust213–11-0.0018%19 Apr
inferno9–13-0.0812%11 Apr
nuke13–5-0.0011%11 Apr
mirage13–50.0622%11 Apr
ancient4–130.0215%11 Apr
nuke7–13-0.052%5 Apr
dust213–90.0216%5 Apr
inferno15–15-0.0211%5 Apr
inferno13–100.0016%28 Mar
ancient13–90.0316%27 Mar
dust213–9-0.0222%22 Mar
nuke13–10.0118%22 Mar
vertigo11–3-0.0119%4 Mar
inferno13–100.0513%4 Mar
mirage3–13-0.1216%4 Mar
inferno13–40.1323%22 Feb
mirage8–13-0.0611%22 Feb
dust211–130.0925%8 Feb
inferno9–130.0416%8 Feb
dust26–13-0.0718%8 Feb
nuke3–130.0223%8 Feb
nuke14–16-0.0015%2 Feb
train13–5-0.0121%2 Feb
ancient11–13-0.0320%30 Jan
dust213–40.0311%30 Jan
nuke13–70.0817%20 Jan
dust211–130.0421%20 Jan
mirage13–7-0.0222%17 Jan
train9–13-0.0515%17 Jan
inferno7–13-0.0324%17 Jan
dust22–00.03100%17 Jan
dust212–12-0.0119%16 Jan
nuke13–6-0.0220%10 Jan
train13–90.0115%10 Jan
train11–13-0.0619%31 Dec
anubis9–10.1012%31 Dec
vertigo13–11-0.0117%31 Dec
mirage13–70.0415%23 Dec
inferno11–130.034%23 Dec
dust25–13-0.0127%17 Dec
train13–8-0.0523%17 Dec
dust212–12-0.0417%8 Nov
inferno3–13-0.0629%8 Nov
nuke11–13-0.0518%2 Nov
mirage4–60.0031%14 Oct
italy13–70.0919%14 Oct
dust213–6-0.0512%14 Oct
anubis4–100.0111%31 Aug

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 →