-kmb

-kmb — CS2 Stats

SE76561198030359459[U:1:70093731]Steam profile ↗✓ No bans

86Tracked matches37%Win rate2020Tracked since
702Hours in CS
CSDB Rating3.8 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim54
Positioning37
Utility25

0–100 skill scores via Leetify.

Recent form

COLD35–44–6Last 8541%Win rateLWLLLLWLLL

Last 10 vs previous 10: −20pp win rate · +0.01 avg rating · −3.7pp headshot accuracy · −2ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 13%
  • Avg reaction 627ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 621ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 16%
  • Avg reaction 622ms

Newest first, from the last 85 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.6 against its own average).

Aim5.4
Utility2.5
Positioning3.7
Opening Duels0.0

Limited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

iM

Plays most like iM 95% 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. 632ms 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

Aim5.4
Positioning3.7
Utility2.5
Mechanics6.6
Opening Duels0.0
Win Impact0.6

Composite 3.8/10 (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-0.05−0.02
first ⅓ avg -0.03 → last ⅓ avg -0.05
Reaction time635ms+32ms
first ⅓ avg 603ms → last ⅓ avg 635ms
Headshot accuracy14.4%+2.4%
first ⅓ avg 12.0% → last ⅓ avg 14.4%

Rolling 5-match average across the last 85 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.05Best match rating · 13–5 · inferno, 6 Mar →
39%Best headshot accuracy · 13–6 · dust2, 17 Apr →
453msFastest reaction time · 5–13 · overpass, 7 May →
13–0Biggest win · overpass, 4 Aug →

Across the last 85 tracked matches.

Highlights

4Longest win streak
6–5In matches decided by ≤2 rounds
14Overtime games

Map breakdown

overpassBest map · 60% over 15ancientWeakest map · 20% over 15
MapGradePlayedRecordWin rateAvg rating
infernoA3117–1455%-0.03
ancientD153–1220%-0.04
overpassA159–660%-0.03
dust2D113–827%-0.04
anubisD62–433%-0.07
mirage—41–325%-0.04
nuke—20–20%-0.07
cache—10–10%-0.04

Across the last 85 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 15). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

29,861Lifetime kills
1.00K/D
1,489Matches
40.2%Match win rate
36.9%Headshot %
18.2%Shot accuracy
2,631MVPs
702Hours (in match)
1,048Bombs planted
258Bombs defused

Most-used weapons

Lifetime map wins

3,715inferno
1,862dust2
642nuke
278train
259cbble
49assault
38dust
31office

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.

13.9%Headshot accuracy
31.6%Accuracy (enemy spotted)
36.8%Spray accuracy
79.9%Counter-strafing
10.3°Preaim
632msReaction time
25.0%T opening success
12.9%CT opening success
0.33Enemies flashed / flash
0.0%Flash assists
7.00HE damage / grenade
4.46Flashes / 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 13.8525% — 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 0.3331 — 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 24.9886% — 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.

20% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient2–13-0.057%11 Nov →
anubis13–8-0.088%4 Nov →
cache8–13-0.0410%1 Nov →
mirage2–13-0.0531%1 Nov →
inferno10–130.017%18 Jun →
anubis11–13-0.0713%16 Jun →
inferno13–6-0.0014%16 Jun →
anubis13–16-0.086%15 Jun →
nuke7–13-0.0515%14 Jun →
dust210–13-0.0225%14 Jun →
overpass5–13-0.0824%7 May →
ancient2–13-0.099%6 May →
dust26–13-0.1114%3 May →
ancient9–13-0.0321%3 May →
inferno13–10-0.017%20 Apr →
inferno13–3-0.0519%18 Apr →
inferno4–13-0.0011%18 Apr →
ancient13–10-0.0825%17 Apr →
dust213–60.0339%17 Apr →
nuke4–13-0.085%17 Apr →
inferno9–13-0.028%16 Apr →
ancient4–13-0.0610%16 Apr →
inferno13–7-0.079%14 Apr →
anubis13–7-0.098%12 Apr →
overpass16–14-0.048%10 Apr →
inferno13–10-0.0112%1 Apr →
inferno8–13-0.0718%23 Mar →
dust23–13-0.0818%23 Mar →
overpass3–13-0.036%18 Mar →
inferno13–11-0.0414%17 Mar →
dust21–13-0.1214%17 Mar →
overpass13–11-0.0613%10 Mar →
inferno3–13-0.0813%9 Mar →
inferno4–13-0.0816%7 Mar →
overpass13–3-0.0116%7 Mar →
overpass13–7-0.0413%6 Mar →
inferno13–50.0517%6 Mar →
ancient13–50.0111%6 Mar →
dust25–13-0.0719%5 Mar →
ancient10–13-0.0417%5 Mar →
ancient15–150.0012%4 Mar →
anubis4–13-0.056%4 Mar →
dust28–13-0.038%2 Mar →
inferno1–13-0.110%2 Mar →
dust211–13-0.0219%1 Mar →
inferno13–6-0.0411%1 Mar →
ancient11–13-0.0713%1 Mar →
dust213–6-0.0711%1 Mar →
mirage2–13-0.039%1 Mar →
overpass13–9-0.0617%27 Feb →
inferno13–11-0.0210%27 Feb →
ancient13–20.019%25 Feb →
ancient15–15-0.057%25 Feb →
dust213–60.0417%25 Feb →
inferno13–4-0.0514%23 Feb →
ancient8–13-0.0412%22 Feb →
dust28–13-0.0110%22 Feb →
ancient7–13-0.0212%22 Feb →
inferno15–15-0.0618%22 Feb →
ancient11–13-0.027%21 Feb →
overpass13–100.0212%20 Feb →
inferno13–5-0.0511%14 Feb →
ancient8–13-0.0317%14 Feb →
inferno15–15-0.0218%14 Feb →
anubis8–13-0.0510%24 Jan →
inferno11–13-0.0512%20 Sept →
inferno13–80.010%12 Sept →
overpass3–13-0.0215%12 Sept →
inferno9–13-0.0917%6 Sept →
inferno13–11-0.0516%19 Aug →
overpass13–11-0.0415%17 Aug →
inferno12–12-0.0414%8 Aug →
overpass13–5-0.057%6 Aug →
overpass13–00.0212%4 Aug →
overpass12–12-0.0910%4 Aug →
inferno13–30.028%4 Aug →
inferno10–13-0.0016%3 Aug →
inferno12–16-0.0611%29 Apr →
overpass12–160.0012%29 Apr →
mirage3–160.0013%29 Apr →
inferno15–100.008%29 Apr →
inferno16–110.0020%24 Apr →
inferno16–60.004%7 Mar →
overpass11–160.0013%29 Jan →
mirage16–9-0.068%11 Dec →

Match data via Leetify.

Recent teammates

Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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