Kiero Kettu♥

Kiero Kettu♥ — CS2 Stats

FI76561198001078589[U:1:40812861]Steam profile ↗✓ No bans

941Tracked matches33%Win rate2020Tracked since
2,704Hours in CS
CSDB Rating3.9 LearningSupport
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Oct 2026 (16 days ago). Ranks are recorded once per day this page is viewed.

+5Tracked matches · now 941
+3.3ppWin rate · 30.0% → 33.3%

Rating over time

Premier CS Rating: 15,557 -299 24 May – 23 Jun · 5 days played
15,55716,259peak 16,25924 May23 Jun
16,259Peak Premier in tracked matches
40Days played since 2025-05-24

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=14,283), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 5 medianLevel 6 medianvs Level 6
Headshot rate34.8%43.8%44.8%10.0% short
Shot accuracy18.7%12.0%12.4%above
Kill/death ratio0.911.021.030.12 short
Match win rate42.5%44.7%45.2%2.8% short

This profile matches the typical Level 6 player on 1 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGKiero Kettu♥FACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim50
Positioning34
Utility52

0–100 skill scores via Leetify.

Recent form

COLD30–64–6Last 10030%Win rateWLWWLLLLLL

Last 10 vs previous 10: −20pp win rate · +0.03 avg rating · +4.9pp headshot accuracy · +98ms 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 (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 21%
  • Avg reaction 735ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 750ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 16%
  • Avg reaction 701ms

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 (+2.3 against its own average).

Aim5.0
Utility5.2
Positioning3.4
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 76% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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 39% on CT to 11% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 708ms 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

Aim5.0
Positioning3.4
Utility5.2
Mechanics5.2
Opening Duels1.1
Win Impact0.0

Composite 3.9/10 (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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time699ms−69ms
first ⅓ avg 768ms → last ⅓ avg 699ms
Headshot accuracy16.8%+1.0%
first ⅓ avg 15.8% → last ⅓ avg 16.8%

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

0.11Best match rating · 13–1 · mirage, 23 Jul →
53%Best headshot accuracy · 4–13 · mirage, 19 Aug →
484msFastest reaction time · 8–13 · cache, 29 Aug →
13–1Biggest win · mirage, 23 Jul →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

ancientBest map · 50% over 10mirageWeakest map · 15% over 13
MapGradePlayedRecordWin rateAvg rating
dust2D226–1627%-0.03
cacheD154–1127%-0.04
mirageD132–1115%-0.02
infernoD134–931%-0.02
ancientB105–550%-0.03
nukeC73–443%0.01
anubisC52–340%-0.02
italy—42–250%-0.01
overpass—31–233%-0.05
train—20–20%0.00
vertigo—20–20%-0.00
boulder—11–0100%0.00
shelter—10–10%0.05
office—10–10%-0.05
grail—10–10%-0.09

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (15% over 13). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

108,136Lifetime kills
0.91K/D
5,895Matches
42.5%Match win rate
34.8%Headshot %
18.7%Shot accuracy · Top 10% of Level 5 players
13,756MVPs
2,704Hours (in match)
7,362Bombs planted
1,318Bombs defused

Most-used weapons

AWP20,960
AK-4720,237
SG 5535,445
P2504,954
Tec-93,223
AUG2,982

Lifetime map wins

11,413dust2
7,115inferno
3,643nuke
1,877cbble
1,615train
491vertigo
450office
136italy

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

Faceit stats

Combat

135Matches
51%Win rate
1.03Avg K/D
—ADR
33%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
8Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Vertigo20%0.7112.0
Nuke10%0.7316.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

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

16.1%Headshot accuracy
34.8%Accuracy (enemy spotted)
39.7%Spray accuracy
73.3%Counter-strafing
11.0°Preaim
708msReaction time
11.5%T opening success
38.7%CT opening success
0.54Enemies flashed / flash
2.2%Flash assists
10.42HE damage / grenade
8.70Flashes / 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 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 707.7702ms — above the 700ms mark we flag

    Aim Training →
  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 11.4909% — below the 40% mark we flag

Spend your practice time on Mirage

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

15% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
italy11–40.0517%30 Oct →
italy8–13-0.0017%29 Oct →
boulder13–20.0032%29 Oct →
italy13–8-0.0113%29 Oct →
shelter10–130.0524%29 Oct →
train1–13-0.0228%8 Oct →
mirage3–13-0.0611%8 Oct →
ancient7–13-0.0216%4 Sept →
inferno3–13-0.0412%4 Sept →
cache11–13-0.0511%2 Sept →
dust213–9-0.078%1 Sept →
inferno3–13-0.0717%31 Aug →
cache13–4-0.076%31 Aug →
inferno10–13-0.0316%31 Aug →
nuke8–130.0229%31 Aug →
cache13–8-0.099%30 Aug →
mirage3–13-0.0410%30 Aug →
anubis13–7-0.038%30 Aug →
cache8–13-0.0219%29 Aug →
ancient13–20.0212%29 Aug →
dust24–13-0.060%29 Aug →
mirage7–13-0.0318%26 Aug →
dust29–13-0.0323%21 Aug →
dust213–50.0111%20 Aug →
mirage8–13-0.037%20 Aug →
dust22–13-0.078%20 Aug →
mirage4–13-0.0453%19 Aug →
cache11–130.0015%18 Aug →
anubis4–13-0.0921%18 Aug →
ancient13–9-0.0517%18 Aug →
nuke10–130.0612%18 Aug →
anubis13–30.0241%18 Aug →
dust29–13-0.0714%18 Aug →
dust213–6-0.036%18 Aug →
dust29–13-0.0722%18 Aug →
ancient10–13-0.0713%4 Aug →
cache9–13-0.0116%4 Aug →
inferno15–15-0.0311%4 Aug →
inferno11–130.0425%1 Aug →
inferno6–13-0.0325%31 Jul →
inferno13–7-0.0110%31 Jul →
ancient10–13-0.0616%31 Jul →
train8–130.0220%31 Jul →
vertigo3–13-0.0533%31 Jul →
dust26–130.0111%25 Jul →
anubis8–130.0027%9 Jul →
nuke8–130.0124%9 Jul →
cache9–13-0.078%9 Jul →
mirage3–13-0.0711%3 Jul →
mirage6–130.0210%5 Jun →
office6–13-0.0536%5 Jun →
vertigo8–130.0425%4 Jun →
dust25–13-0.0615%4 Jun →
anubis8–13-0.019%2 Jun →
italy4–13-0.0621%2 Jun →
cache10–13-0.0515%2 Jun →
nuke3–13-0.0822%20 May →
inferno6–13-0.0629%20 May →
inferno4–13-0.058%10 May →
ancient6–13-0.0113%10 May →
overpass3–13-0.0820%10 May →
cache3–13-0.0938%10 May →
cache6–13-0.0425%10 May →
cache13–8-0.0217%30 Apr →
cache10–130.0213%29 Apr →
cache13–7-0.0624%29 Apr →
cache12–12-0.043%29 Apr →
cache10–13-0.0311%29 Apr →
nuke13–8-0.0012%24 Oct →
nuke13–70.0323%24 Oct →
inferno11–13-0.0111%24 Oct →
overpass8–13-0.0322%24 Oct →
dust213–10-0.0119%28 Sept →
dust210–13-0.1013%28 Sept →
dust27–13-0.0129%28 Sept →
inferno16–14-0.0110%26 Jul →
mirage13–50.0619%26 Jul →
dust213–100.0012%26 Jul →
overpass13–11-0.0422%26 Jul →
dust27–13-0.0418%23 Jul →
mirage13–10.1121%23 Jul →
dust29–13-0.0610%23 Jul →
ancient13–90.0211%23 Jul →
dust25–13-0.066%23 Jul →
mirage6–13-0.0428%23 Jul →
dust215–15-0.0015%19 Jul →
dust215–150.0010%19 Jul →
mirage12–120.0018%15 Jul →
mirage4–13-0.103%23 Jun →
inferno13–8-0.0417%23 Jun →
dust29–130.019%23 Jun →
ancient13–100.0216%7 Jun →
grail9–13-0.0917%3 Jun →
inferno13–80.0423%3 Jun →
mirage8–13-0.0615%31 May →
ancient8–13-0.049%31 May →
nuke13–10-0.0127%30 May →
dust213–6-0.0214%28 May →
dust215–15-0.0323%28 May →
ancient16–12-0.0613%24 May →

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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