Mällisin käsi

Mällisin käsi — CS2 Stats

FI76561199121862167[U:1:1161596439]Steam profile ↗✓ No bans

101Tracked matches56%Win rate2024Tracked since
CSDB Rating2.3 LearningSupport
WingmanSilver II
Ladder ranks via Leetify

Performance scores

Aim10
Positioning25
Utility30

0–100 skill scores via Leetify.

Recent form

STEADY35–54–11Last 10035%Win rateLLLLWLWWTW

Last 10 vs previous 10: −20pp win rate · −0.04 avg rating · +3.0pp headshot accuracy · −25ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 11%
  • Avg reaction 748ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 11%
  • Avg reaction 799ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 9%
  • Avg reaction 811ms

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: Support — Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim1.0
Utility3.0
Positioning2.5
Opening Duels0.0

Strong CT-side opener

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

NiKo

Plays most like NiKo 63% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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

T-side openings. Opening success drops from 28% on CT to 8% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 804ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 62% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim1.0
Positioning2.5
Utility3.0
Mechanics2.6
Opening Duels0.0
Win Impact6.9

Composite 2.3/10 (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-0.07+0.03
first ⅓ avg -0.10 → last ⅓ avg -0.07
Reaction time805ms−21ms
first ⅓ avg 826ms → last ⅓ avg 805ms
Headshot accuracy8.7%−0.1%
first ⅓ avg 8.9% → last ⅓ avg 8.7%

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

0.21Best match rating · 9–3 · inferno, 3 Sept →
31%Best headshot accuracy · 9–7 · inferno, 22 Feb →
516msFastest reaction time · 2–9 · inferno, 19 Feb →
13–0Biggest win · ancient, 21 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L4Current streak
9–2In matches decided by ≤2 rounds

Map breakdown

overpassBest map · 67% over 6officeWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
infernoD215–1624%-0.07
nukeB178–947%-0.10
vertigoC176–1135%-0.10
officeD122–1017%-0.07
mirageC125–742%-0.07
dust2B84–450%-0.07
overpassS64–267%-0.06
ancient—21–150%-0.06
train—10–10%-0.13
warden—10–10%-0.10
alpine—10–10%-0.11
anubis—10–10%-0.10
sanctum—10–10%-0.29

Across the last 100 tracked matches.

Skill profile

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

8.2%Headshot accuracy
28.6%Accuracy (enemy spotted)
27.8%Spray accuracy
61.7%Counter-strafing
11.2°Preaim
804msReaction time
7.7%T opening success
27.7%CT opening success
0.54Enemies flashed / flash
5.9%Flash assists
3.35HE damage / grenade
10.02Flashes / 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 8.2389% — 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 803.7733ms — 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 7.7269% — 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.

24% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
office5–13-0.0614%23 Sept →
inferno6–13-0.0517%22 Sept →
ancient11–13-0.0512%22 Sept →
nuke9–13-0.0815%22 Sept →
nuke13–8-0.150%21 Sept →
train9–13-0.1314%21 Sept →
vertigo13–9-0.0510%21 Sept →
ancient13–0-0.0714%21 Sept →
dust212–12-0.113%21 Sept →
inferno13–4-0.0711%21 Sept →
overpass13–80.0011%21 Sept →
overpass12–12-0.122%20 Sept →
nuke13–10-0.084%20 Sept →
nuke9–7-0.200%3 Sept →
mirage1–13-0.075%3 Sept →
nuke9–70.1116%3 Sept →
mirage2–13-0.0920%3 Sept →
office13–5-0.0613%3 Sept →
inferno9–30.216%3 Sept →
dust21–13-0.090%8 Apr →
inferno6–9-0.1712%8 Apr →
vertigo8–8-0.128%8 Apr →
vertigo13–11-0.1010%3 Apr →
dust213–4-0.033%3 Apr →
inferno13–5-0.040%3 Apr →
nuke13–6-0.009%3 Apr →
mirage13–4-0.040%3 Apr →
nuke3–9-0.1813%3 Apr →
mirage13–10-0.0622%26 Mar →
office12–12-0.108%23 Mar →
office8–13-0.0611%22 Mar →
office13–5-0.015%20 Mar →
office4–13-0.070%18 Mar →
office7–13-0.120%18 Mar →
office5–13-0.0614%18 Mar →
dust213–11-0.040%18 Mar →
dust213–8-0.048%15 Mar →
overpass6–13-0.125%13 Mar →
overpass13–7-0.110%13 Mar →
mirage2–13-0.0714%2 Mar →
dust23–13-0.1115%2 Mar →
dust20–10-0.120%2 Mar →
inferno4–13-0.0728%25 Feb →
mirage13–11-0.0518%25 Feb →
warden1–13-0.105%24 Feb →
alpine1–13-0.1113%24 Feb →
nuke12–12-0.096%24 Feb →
inferno4–13-0.0721%24 Feb →
mirage13–7-0.0411%24 Feb →
inferno1–13-0.1113%23 Feb →
mirage12–12-0.056%23 Feb →
mirage10–13-0.0413%22 Feb →
inferno9–7-0.0531%22 Feb →
inferno2–9-0.0822%19 Feb →
overpass9–10.0814%19 Feb →
vertigo1–13-0.1130%17 Feb →
inferno2–8-0.110%17 Feb →
vertigo8–8-0.1112%17 Feb →
nuke0–9-0.2710%16 Feb →
inferno7–9-0.0915%16 Feb →
nuke13–10-0.0725%15 Feb →
nuke13–11-0.070%15 Feb →
dust213–10-0.0211%14 Feb →
nuke6–9-0.130%12 Feb →
vertigo12–12-0.0516%6 Feb →
nuke3–13-0.1410%6 Feb →
inferno4–13-0.0919%6 Feb →
vertigo10–13-0.044%6 Feb →
nuke2–13-0.0714%6 Feb →
office5–13-0.086%6 Feb →
office3–13-0.0312%6 Feb →
inferno5–9-0.0616%6 Feb →
inferno5–9-0.020%6 Feb →
anubis4–13-0.107%6 Feb →
inferno7–13-0.0716%5 Feb →
sanctum2–9-0.290%3 Feb →
overpass13–9-0.0714%3 Feb →
nuke3–13-0.1321%3 Feb →
inferno2–9-0.225%3 Feb →
nuke8–13-0.0914%28 Jan →
nuke13–8-0.047%28 Jan →
inferno3–90.013%28 Jan →
mirage9–13-0.130%28 Jan →
office12–12-0.078%28 Jan →
office6–13-0.070%28 Jan →
inferno4–9-0.206%26 Jan →
vertigo3–9-0.2010%26 Jan →
vertigo5–9-0.054%26 Jan →
vertigo9–7-0.0810%26 Jan →
vertigo2–9-0.200%26 Jan →
vertigo9–6-0.0113%22 Jan →
vertigo9–4-0.0113%22 Jan →
inferno9–70.0713%22 Jan →
inferno4–9-0.220%22 Jan →
vertigo8–8-0.0516%3 Jan →
mirage10–13-0.072%27 Dec →
mirage13–10-0.129%27 Dec →
vertigo3–9-0.2329%7 May →
vertigo9–6-0.138%15 Apr →
vertigo8–8-0.2013%15 Apr →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.