ICESWALAWKUM

ICESWALAWKUM — CS2 Stats

US76561198393601945[U:1:433336217]Steam profile ↗✓ No bans

702Tracked matches61%Win rate2020Tracked since
853Hours in CS
CSDB Rating5.7 SolidAll-Rounder
Ladder ranks via Leetify

Performance scores

Aim57
Positioning47
Utility47

0–100 skill scores via Leetify.

Recent form

STEADY46–44–10Last 10046%Win rateWWWWLWLLLL

Last 10 vs previous 10: −20pp win rate · −0.02 avg rating · −2.4pp headshot accuracy · −32ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 647ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 626ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 642ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim5.7
Utility4.7
Positioning4.7
Opening Duels3.7

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

ZywOo

Plays most like ZywOo 85% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Areas to improve

Reaction time. 649ms 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

Aim5.7
Positioning4.7
Utility4.7
Mechanics7.9
Opening Duels2.8
Win Impact8.6

Composite 5.7/10 (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 rating-0.01+0.02
first ⅓ avg -0.03 → last ⅓ avg -0.01
Reaction time652ms−30ms
first ⅓ avg 682ms → last ⅓ avg 652ms
Headshot accuracy14.7%+0.3%
first ⅓ avg 14.5% → last ⅓ avg 14.7%

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.

Personal bests

0.10Best match rating · 5–13 · mirage, 3 Jan →
35%Best headshot accuracy · 5–13 · mirage, 4 Sept →
469msFastest reaction time · 5–16 · inferno, 9 Aug →
16–1Biggest win · mirage, 19 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W4Current streak
6–5In matches decided by ≤2 rounds
58Overtime games

Map breakdown

mirageBest map · 54% over 41infernoWeakest map · 36% over 25
MapGradePlayedRecordWin rateAvg rating
mirageB4122–1954%-0.01
infernoC259–1636%-0.03
dust2B157–847%-0.02
ancientC52–340%-0.03
cache—43–175%-0.04
nuke—31–233%-0.00
overpass—31–233%-0.02
anubis—21–150%-0.01
train—10–10%-0.08
vertigo—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (36% over 25). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

50,639Lifetime kills
1.20K/D · Top 25% of tracked players
1,980Matches
45.0%Match win rate · Top 50% of tracked players
36.9%Headshot %
19.2%Shot accuracy · Top 5% of tracked players
6,335MVPs
853Hours (in match)
1,390Bombs planted
416Bombs defused

Most-used weapons

AK-4713,217
AWP8,106
MAC-101,970
MP91,864
SG 5531,836
AUG1,817

Lifetime map wins

1,925dust2
1,188inferno
387nuke
294vertigo
155train
37cbble
27lake
19office

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.

14.0%Headshot accuracy
33.3%Accuracy (enemy spotted)
35.6%Spray accuracy
85.6%Counter-strafing
10.8°Preaim
649msReaction time
41.0%T opening success
41.3%CT opening success
0.56Enemies flashed / flash
8.5%Flash assists
8.19HE damage / grenade
8.55Flashes / 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 14.034% — below the 15% mark we flag

    Aim Training →
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.

36% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–9-0.0221%7 May →
dust213–6-0.0721%24 Jan →
mirage13–5-0.047%24 Jan →
inferno13–11-0.026%24 Jan →
ancient5–13-0.0215%24 Jan →
nuke13–10-0.078%24 Jan →
inferno10–13-0.0710%24 Jan →
anubis9–13-0.036%24 Jan →
dust24–13-0.0619%24 Jan →
inferno5–130.0620%23 Nov →
ancient13–9-0.0322%22 Nov →
dust27–20.0627%22 Nov →
inferno5–13-0.1017%22 Nov →
train0–13-0.0815%15 Nov →
overpass13–60.066%10 Nov →
inferno13–50.0620%10 Nov →
mirage13–16-0.045%9 Nov →
inferno13–11-0.0624%9 Nov →
mirage13–8-0.0215%8 Nov →
mirage13–100.029%8 Nov →
inferno11–10.0113%8 Nov →
mirage12–120.0718%7 Nov →
mirage13–110.0421%4 Nov →
mirage13–10-0.027%30 Oct →
nuke10–13-0.0411%30 Oct →
dust213–60.0220%30 Oct →
inferno12–120.0117%18 Oct →
dust25–130.0125%18 Oct →
mirage13–70.076%18 Oct →
mirage9–13-0.035%17 Oct →
mirage12–120.0412%17 Oct →
mirage13–60.0618%28 Jan →
vertigo12–12-0.0520%28 Jan →
ancient13–60.0421%28 Jan →
mirage5–130.1015%3 Jan →
inferno7–13-0.0317%5 Sept →
nuke9–130.0927%4 Sept →
inferno13–70.0015%4 Sept →
mirage5–130.0335%4 Sept →
inferno13–6-0.0220%4 Sept →
overpass3–13-0.0616%4 Sept →
mirage16–10-0.0416%19 Aug →
mirage15–15-0.0717%19 Aug →
mirage16–9-0.0211%19 Aug →
mirage16–10.0427%19 Aug →
cache16–13-0.079%18 Aug →
mirage13–16-0.036%16 Aug →
inferno9–16-0.0613%16 Aug →
mirage16–3-0.058%16 Aug →
mirage7–160.0413%14 Aug →
dust26–16-0.0720%14 Aug →
mirage6–16-0.0912%14 Aug →
mirage15–15-0.0713%14 Aug →
inferno6–16-0.0610%14 Aug →
mirage12–16-0.067%11 Aug →
mirage9–16-0.039%11 Aug →
mirage8–00.008%11 Aug →
mirage16–13-0.054%10 Aug →
inferno2–16-0.089%9 Aug →
mirage16–90.048%9 Aug →
inferno5–16-0.0729%9 Aug →
mirage10–16-0.0710%9 Aug →
mirage15–15-0.093%9 Aug →
mirage16–60.0513%8 Aug →
inferno9–16-0.0814%8 Aug →
mirage16–70.008%7 Aug →
mirage16–100.0412%7 Aug →
ancient3–16-0.0714%7 Aug →
overpass4–16-0.054%5 Aug →
cache16–14-0.0413%5 Aug →
anubis16–130.002%5 Aug →
inferno14–16-0.0310%4 Aug →
dust215–15-0.0114%3 Aug →
dust214–16-0.0315%3 Aug →
mirage16–110.0111%3 Aug →
inferno16–9-0.0215%2 Aug →
dust214–16-0.0413%2 Aug →
mirage16–100.0110%2 Aug →
dust25–16-0.0814%2 Aug →
cache7–16-0.0613%2 Aug →
mirage16–40.0225%1 Aug →
dust216–14-0.0425%1 Aug →
mirage16–6-0.037%1 Aug →
inferno4–16-0.0515%31 Jul →
inferno14–16-0.0410%30 Jul →
mirage15–15-0.0614%30 Jul →
mirage12–16-0.0017%29 Jul →
inferno10–16-0.068%29 Jul →
inferno9–16-0.0013%29 Jul →
ancient9–16-0.0913%29 Jul →
inferno16–80.0217%29 Jul →
dust216–9-0.049%28 Jul →
mirage16–130.0112%28 Jul →
inferno16–14-0.0612%27 Jul →
dust216–120.0216%27 Jul →
cache16–70.0118%27 Jul →
inferno10–16-0.0528%27 Jul →
dust212–16-0.0126%27 Jul →
mirage15–15-0.0323%27 Jul →
mirage7–9-0.0323%26 Jul →

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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