KATTIMATIKAINEN

KATTIMATIKAINEN — CS2 Stats

FI76561198156670286[U:1:196404558]Steam profile ↗✓ No bans

129Tracked matches63%Win rate2021Tracked since
804Hours in CS
CSDB Rating4.7 DevelopingPositional Player
Ladder ranks via Leetify

Performance scores

Aim43
Positioning54
Utility34

0–100 skill scores via Leetify.

Recent form

STEADY56–38–6Last 10056%Win rateLLLLLWWWTW

Last 10 vs previous 10: −10pp win rate · −0.03 avg rating · +1.7pp headshot accuracy · −68ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 18%
  • Avg reaction 517ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 20%
  • Avg reaction 579ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 613ms

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

Aim4.3
Utility3.4
Positioning5.4
Opening Duels2.7

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

m0NESY

Plays most like m0NESY 78% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Reaction time. 635ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim4.3
Positioning5.4
Utility3.4
Mechanics4.2
Opening Duels2.5
Win Impact9.3

Composite 4.7/10 (Developing), 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+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time623ms−74ms
first ⅓ avg 697ms → last ⅓ avg 623ms
Headshot accuracy21.4%+0.8%
first ⅓ avg 20.5% → last ⅓ avg 21.4%

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.

Personal bests

0.15Best match rating · 13–1 · dust2, 9 Nov →
38%Best headshot accuracy · 6–13 · dust2, 8 Feb →
500msFastest reaction time · 13–0 · nuke, 20 Feb →
13–0Biggest win · inferno, 13 Apr →

Across the last 100 tracked matches.

Highlights

9Longest win streak
L5Current streak
5–3In matches decided by ≤2 rounds
1Overtime games

Map breakdown

nukeBest map · 90% over 10trainWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
infernoA2112–957%0.02
mirageB199–1047%-0.02
dust2B189–950%0.01
cacheS108–280%0.01
nukeS109–190%0.05
ancientB84–450%-0.02
trainD62–433%-0.02
overpass—42–250%0.00
anubis—31–233%-0.01
vertigo—10–10%-0.10

Across the last 100 tracked matches.

Lifetime stats

60,556Lifetime kills
1.33K/D · Top 10% of tracked players
1,955Matches
34.9%Match win rate
47.5%Headshot % · Top 50% of tracked players
18.2%Shot accuracy · Top 10% of tracked players
4,281MVPs
804Hours (in match)
1,911Bombs planted
426Bombs defused

Most-used weapons

Lifetime map wins

5,700dust2
2,664inferno
929nuke
492train
372cbble
49aztec
43vertigo
43ar_shoots

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.

21.2%Headshot accuracy
28.1%Accuracy (enemy spotted)
30.8%Spray accuracy
69.1%Counter-strafing
10.7°Preaim
635msReaction time
39.5%T opening success
40.2%CT opening success
0.43Enemies flashed / flash
6.3%Flash assists
8.45HE damage / grenade
2.69Flashes / 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. 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 0.4347 — below the 0.5 mark we flag

    Grenade Lineups →
  2. 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 39.5088% — below the 40% mark we flag

Spend your practice time on Train

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

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage7–13-0.150%17 Oct →
mirage4–13-0.0633%10 Oct →
ancient2–8-0.0230%10 Oct →
dust27–13-0.0613%10 Oct →
inferno7–13-0.0515%27 May →
train13–110.0135%27 May →
cache13–10.0327%27 May →
cache13–70.0413%22 May →
mirage12–12-0.0211%22 May →
cache13–9-0.0625%13 May →
ancient13–2-0.044%7 May →
mirage3–130.0126%7 May →
nuke13–4-0.0314%7 May →
overpass12–120.0327%7 May →
mirage13–11-0.0424%3 May →
mirage10–13-0.0215%3 May →
cache13–100.0622%3 May →
cache13–8-0.0327%3 May →
cache7–13-0.064%3 May →
cache11–130.0224%3 May →
cache13–2-0.0325%29 Apr →
cache8–00.0329%29 Apr →
cache13–20.0732%29 Apr →
inferno13–50.0325%28 Apr →
dust213–9-0.0513%28 Apr →
anubis8–130.0228%27 Apr →
inferno13–110.0628%27 Apr →
inferno5–0-0.0411%27 Apr →
inferno12–120.0123%26 Apr →
dust213–70.0524%26 Apr →
overpass13–4-0.0324%26 Apr →
inferno10–100.0326%26 Apr →
inferno6–130.0230%26 Apr →
dust27–130.0630%26 Apr →
anubis4–13-0.0718%26 Apr →
ancient12–12-0.0025%26 Apr →
overpass13–90.0936%24 Apr →
inferno13–60.0932%24 Apr →
dust23–130.0329%24 Apr →
mirage13–60.1013%24 Apr →
ancient13–80.0327%24 Apr →
mirage13–7-0.0114%17 Apr →
anubis13–70.0218%17 Apr →
nuke13–60.0228%17 Apr →
inferno9–13-0.0016%14 Apr →
inferno8–13-0.0410%14 Apr →
nuke8–130.0326%14 Apr →
inferno13–00.0229%13 Apr →
mirage12–30.0733%19 Mar →
nuke13–90.0926%19 Mar →
dust213–90.0519%5 Mar →
nuke13–8-0.0016%3 Mar →
train13–30.0033%25 Feb →
inferno13–50.1115%21 Feb →
dust213–110.0419%21 Feb →
nuke13–00.1413%20 Feb →
dust210–13-0.0115%18 Feb →
nuke13–60.1424%17 Feb →
mirage13–80.1225%16 Feb →
inferno4–10.0421%12 Feb →
nuke13–90.0424%12 Feb →
mirage13–16-0.0317%12 Feb →
mirage13–9-0.037%8 Feb →
dust26–13-0.0438%8 Feb →
mirage13–10-0.0413%7 Feb →
ancient13–9-0.0213%7 Feb →
inferno11–130.1131%4 Feb →
dust213–50.1223%4 Feb →
inferno13–70.1118%4 Feb →
train7–130.0530%4 Feb →
dust213–10.1518%9 Nov →
inferno13–30.0015%9 Nov →
mirage10–13-0.0413%9 Nov →
ancient13–8-0.0521%4 Oct →
dust24–13-0.0128%20 Sept →
nuke13–70.0119%20 Sept →
mirage13–5-0.0220%20 Sept →
mirage13–40.0830%20 Sept →
inferno13–60.0410%20 Sept →
dust213–50.0525%19 Sept →
mirage2–13-0.1116%19 Sept →
dust21–11-0.0833%23 Aug →
train9–13-0.0915%23 Aug →
inferno2–13-0.0228%23 Aug →
mirage11–13-0.0821%23 Aug →
inferno5–13-0.0519%23 Aug →
dust213–90.0526%23 Aug →
ancient8–13-0.0414%23 Aug →
train10–13-0.0316%23 Aug →
inferno5–1-0.0420%23 Aug →
dust27–13-0.075%9 Aug →
dust213–7-0.0411%9 Aug →
vertigo5–13-0.1023%1 Aug →
inferno3–13-0.0329%31 Jul →
mirage2–13-0.0632%31 Jul →
dust24–13-0.079%31 Jul →
ancient12–12-0.0210%31 Jul →
train12–12-0.0422%31 Jul →
nuke13–60.0935%31 Jul →
overpass3–13-0.0824%31 Jul →

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 →

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