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mclnb — CS2 Stats

76561198076533223[U:1:116267495]

635Tracked matches37%Win rate2020Tracked since
1,135Hours in CS4Hrs last 2 wks
CSDB Rating2.8 Learning
Ladder ranks via Leetify

Performance scores

Aim39
Positioning24
Utility11

0–100 skill scores via Leetify.

Recent form

STEADY36–54–10Last 10036%Win rateTLWWWWWLLL

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

Player DNA

Aim3.9
Aggression0.6
Utility1.1
Positioning2.4
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 59% playstyle similarity

Most alike: opening-duel success, 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. 642ms 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

Aim3.9
Positioning2.4
Utility1.1
Mechanics6.3
Opening Duels0.0
Win Impact0.7

Composite 2.8/10 (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-0.04−0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time651ms+22ms
first ⅓ avg 629ms → last ⅓ avg 651ms
Headshot accuracy12.9%+2.4%
first ⅓ avg 10.5% → last ⅓ avg 12.9%

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 — ancient 13–3
13–0Biggest win — mirage
5Longest win streak
5–11In matches decided by ≤2 rounds

Map breakdown

trainBest map · 57% over 7infernoWeakest map · 23% over 13
MapGradePlayedRecordWin rateAvg rating
dust2C269–1735%-0.04
ancientD165–1131%-0.04
mirageB137–654%-0.04
infernoD133–1023%-0.06
anubisD82–625%-0.04
trainA74–357%-0.03
nukeB63–350%-0.02
cache—40–40%-0.05
overpass—32–167%-0.05
boulder—10–10%-0.03
shelter—10–10%-0.03
warden—11–0100%-0.01
alpine—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (23% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

24,193Lifetime kills
0.65K/D
1,800Matches
34.7%Match win rate
32.5%Headshot %
18.8%Shot accuracy · Top 10% of tracked players
1,980MVPs
679Hours (in match)
1,297Bombs planted
306Bombs defused

Most-used weapons

AK-477,626
M4A4 / M4A1-S5,123
P901,424
AWP1,144
P2000 / USP-S1,048
Galil AR987
SG 553850
Glock-18769
FAMAS695
UMP-45674

Lifetime map wins

1,847inferno
1,695dust2
888train
698nuke
584vertigo
143bank
123lake
77safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

13.1%Headshot accuracy
30.0%Accuracy (enemy spotted)
29.0%Spray accuracy
78.5%Counter-strafing
11.1°Preaim
642msReaction time
13.4%T opening success
27.2%CT opening success
0.12Enemies flashed / flash
3.5%Flash assists
6.45HE damage / grenade
0.64Flashes / 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 13.0503% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.1217 — below the 0.5 mark we flag

    Grenade Lineups →
  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 13.4157% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

23% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke12–120.0013%27 Aug →
cache7–13-0.079%27 Aug →
mirage13–0-0.024%26 Aug →
mirage13–10-0.0714%18 Aug →
ancient13–30.1313%16 Aug →
dust213–7-0.037%13 Aug →
dust213–9-0.0425%5 Aug →
ancient8–13-0.094%5 Aug →
cache10–13-0.0910%30 Jul →
boulder5–13-0.0310%18 Jul →
dust29–130.0312%18 Jul →
shelter7–13-0.0314%16 Jul →
dust211–13-0.092%16 Jul →
train2–13-0.1014%7 Jul →
dust213–8-0.0216%7 Jul →
nuke13–8-0.0415%4 Jun →
dust213–4-0.0117%3 Jun →
inferno6–13-0.0418%3 Jun →
inferno12–12-0.1125%1 Jun →
anubis4–13-0.0719%1 Jun →
ancient11–13-0.0617%28 May →
cache5–13-0.029%28 May →
dust211–13-0.069%20 May →
overpass13–8-0.069%19 May →
ancient11–13-0.049%17 May →
anubis13–4-0.0510%7 May →
cache2–13-0.0418%7 May →
anubis6–130.0120%24 Apr →
inferno12–12-0.0621%16 Apr →
dust27–13-0.058%16 Apr →
ancient13–11-0.0614%14 Apr →
train13–11-0.064%13 Apr →
dust211–13-0.0917%27 Mar →
ancient13–9-0.0113%24 Mar →
overpass13–7-0.0717%23 Mar →
dust28–13-0.1012%17 Mar →
nuke4–13-0.063%15 Mar →
nuke11–13-0.0216%14 Mar →
anubis8–13-0.1113%13 Mar →
mirage13–30.0519%13 Mar →
ancient11–13-0.037%10 Mar →
anubis8–13-0.0419%10 Mar →
inferno8–13-0.029%5 Mar →
dust212–12-0.058%5 Mar →
dust25–5-0.0713%26 Feb →
inferno3–13-0.0713%26 Feb →
train13–110.0212%25 Feb →
dust213–90.0124%23 Feb →
dust26–13-0.088%22 Feb →
mirage11–13-0.0210%22 Feb →
dust211–13-0.037%19 Feb →
mirage12–9-0.1211%19 Feb →
mirage13–9-0.0518%13 Feb →
nuke12–1-0.043%12 Feb →
dust27–13-0.0518%12 Feb →
dust213–9-0.0121%8 Feb →
mirage6–13-0.1011%8 Feb →
mirage13–9-0.069%5 Feb →
dust212–12-0.0210%1 Feb →
mirage8–13-0.0515%28 Jan →
dust211–4-0.046%27 Jan →
overpass5–13-0.036%27 Jan →
inferno11–13-0.0413%26 Jan →
mirage10–13-0.0510%25 Jan →
warden13–3-0.0113%23 Jan →
alpine5–13-0.053%23 Jan →
anubis3–13-0.1014%22 Jan →
anubis13–50.0815%20 Jan →
train12–120.018%16 Jan →
ancient5–13-0.047%14 Jan →
mirage5–13-0.077%11 Jan →
dust212–12-0.049%9 Jan →
ancient12–12-0.087%9 Jan →
dust21–13-0.114%8 Jan →
inferno13–8-0.089%8 Jan →
inferno2–13-0.1111%6 Jan →
ancient1–13-0.0916%6 Jan →
dust213–100.0116%5 Jan →
ancient13–7-0.0216%30 Dec →
inferno13–7-0.050%23 Dec →
ancient13–70.0110%23 Dec →
dust210–13-0.090%21 Dec →
nuke13–70.0514%21 Dec →
mirage13–40.0415%21 Dec →
inferno10–13-0.067%19 Dec →
ancient6–13-0.0319%19 Dec →
train13–10.0111%18 Dec →
mirage2–7-0.0225%18 Dec →
inferno13–11-0.0714%18 Dec →
ancient7–13-0.0715%18 Dec →
dust212–12-0.0818%17 Dec →
train11–10.0310%17 Dec →
dust213–11-0.037%15 Dec →
ancient9–13-0.067%15 Dec →
dust210–13-0.017%11 Dec →
train8–13-0.104%9 Dec →
inferno6–13-0.0311%9 Dec →
anubis10–13-0.077%9 Dec →
ancient4–13-0.0612%11 Nov →
inferno12–12-0.068%11 Nov →

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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