BigCheese

BigCheese — CS2 Stats

76561198992283559[U:1:1032017831]Steam profile ↗

395Tracked matches52%Win rate2023Tracked since
CSDB Rating3.5 Learning
Premier CS Rating8,750Light Blue band · top ~60.9% of ranked players (population est.)
CSDB Leaderboard#35468 of 48243 tracked
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanSilver Elite Master
Ladder ranks via Leetify

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CSDB.GGBigCheeseFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER8,750 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim28
Positioning29
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY40546Last 10040%Win rateLWLWLLTLWW

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

Player DNA

Aim2.8
Aggression3.2
Utility5.8
Positioning2.9
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 69% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 38% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 728ms 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

Aim2.8
Positioning2.9
Utility5.8
Mechanics6.4
Opening Duels1.1
Win Impact5.6

Composite 3.5/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03+0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time700ms−18ms
first ⅓ avg 718ms → last ⅓ avg 700ms
Headshot accuracy11.4%−2.2%
first ⅓ avg 13.6% → last ⅓ avg 11.4%

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

0.08Best rating — overpass 13–4
131Biggest win — nuke
4Longest win streak
58In matches decided by ≤2 rounds
7Overtime games

Map breakdown

cacheBest map · 67% over 12ancientWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
nukeB168850%-0.02
dust2B168850%-0.03
mirageD134931%-0.02
cacheS128467%-0.03
infernoC114736%-0.04
ancientD81713%-0.04
trainD72529%-0.02
vertigoD72529%-0.04
anubisD61517%-0.04
overpass21150%0.00
office21150%0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (13% over 8). 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.

11.2%Headshot accuracy
29.7%Accuracy (enemy spotted)
29.2%Spray accuracy
79.0%Counter-strafing
11.4°Preaim
728msReaction time
21.7%T opening success
38.5%CT opening success
0.78Enemies flashed / flash
5.3%Flash assists
15.79HE damage / grenade
5.44Flashes / 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 11.1518% — below the 15% mark we flag

    Aim Training
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 727.7614ms — above the 700ms mark we flag

    Aim Training
  3. 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 21.704% — 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.

13% 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
nuke5–13-0.038%5 Aug
nuke13–30.0622%4 Aug
nuke8–13-0.0316%3 Aug
cache13–7-0.0412%3 Aug
dust23–130.0110%28 Jul
ancient11–13-0.037%26 Jul
mirage15–15-0.0512%25 Jul
anubis6–13-0.0322%24 Jul
cache13–9-0.019%22 Jul
dust213–7-0.0411%20 Jul
dust213–3-0.0713%20 Jul
inferno3–13-0.0615%19 Jul
nuke10–13-0.0116%19 Jul
cache13–6-0.017%18 Jul
dust213–11-0.0113%17 Jul
nuke13–7-0.047%17 Jul
cache11–13-0.066%16 Jul
dust213–7-0.0110%16 Jul
mirage13–8-0.0512%16 Jul
ancient7–13-0.046%15 Jul
nuke13–11-0.0313%15 Jul
anubis1–50.000%14 Jul
nuke11–13-0.0310%14 Jul
mirage6–13-0.0315%13 Jul
nuke13–4-0.025%13 Jul
anubis11–2-0.045%13 Jul
dust24–13-0.0410%13 Jul
dust213–8-0.017%12 Jul
inferno13–5-0.0120%11 Jul
nuke1–13-0.060%11 Jul
cache16–13-0.0616%10 Jul
inferno8–13-0.0322%10 Jul
cache13–4-0.0321%9 Jul
mirage13–4-0.0110%9 Jul
cache13–9-0.0317%7 Jul
dust29–130.0012%6 Jul
mirage10–13-0.0215%6 Jul
inferno8–13-0.069%3 Jul
inferno1–9-0.0610%2 Jul
inferno13–11-0.0314%2 Jul
nuke13–110.018%1 Jul
mirage9–13-0.039%1 Jul
inferno16–13-0.098%30 Jun
mirage15–15-0.0113%30 Jun
mirage13–16-0.0010%27 Jun
dust213–8-0.0510%27 Jun
ancient1–13-0.0823%27 Jun
overpass13–40.0814%26 Jun
inferno16–13-0.0210%26 Jun
train12–120.0111%25 Jun
dust27–0-0.059%25 Jun
mirage11–130.0115%24 Jun
dust20–13-0.012%24 Jun
nuke5–13-0.0810%23 Jun
dust213–3-0.0123%23 Jun
train8–13-0.0320%22 Jun
vertigo8–13-0.1010%22 Jun
nuke9–130.0522%21 Jun
nuke13–11-0.034%21 Jun
train13–9-0.0011%20 Jun
vertigo10–2-0.048%20 Jun
train13–8-0.0615%20 Jun
vertigo9–13-0.1118%18 Jun
train12–12-0.0617%17 Jun
train3–13-0.0710%17 Jun
cache8–13-0.099%16 Jun
ancient3–13-0.080%16 Jun
anubis7–13-0.070%16 Jun
mirage11–13-0.0417%15 Jun
dust23–13-0.067%15 Jun
mirage13–7-0.0611%15 Jun
cache9–13-0.0225%13 Jun
vertigo13–6-0.023%13 Jun
mirage13–90.0113%13 Jun
inferno4–5-0.0411%13 Jun
cache13–80.006%12 Jun
office10–13-0.0022%12 Jun
ancient4–130.0018%12 Jun
dust27–130.0215%12 Jun
dust210–13-0.0912%11 Jun
train2–130.0219%11 Jun
overpass2–13-0.0810%10 Jun
anubis7–13-0.0519%10 Jun
dust28–13-0.047%10 Jun
ancient13–90.0310%9 Jun
vertigo5–13-0.0111%9 Jun
vertigo3–130.0322%8 Jun
anubis5–13-0.069%8 Jun
vertigo11–13-0.075%7 Jun
inferno3–13-0.0517%7 Jun
inferno7–13-0.0322%5 Jun
ancient6–13-0.0920%5 Jun
nuke7–13-0.0818%4 Jun
nuke13–6-0.069%1 Jun
ancient15–15-0.0310%1 Jun
cache11–13-0.0314%1 Jun
mirage12–12-0.0418%31 May
nuke13–10.0212%31 May
office13–60.0120%31 May
cache13–6-0.0418%30 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 →