Ilmar Iistata

Ilmar Iistata — CS2 Stats

HM76561199186657601[U:1:1226391873]Steam profile ↗✓ No bans

319Tracked matches62%Win rate2025Tracked since
326Hours in CS8Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
Premier CS Rating14,656Blue band · top ~30.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 21 Oct 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 14,656 +1,158 19 Jul – 21 Oct · 29 days played
12,42815,112peak 15,11219 Jul21 Oct
15,112Peak Premier in tracked matches
44Days played since 2026-07-19

Premier CS Rating

  • 456 below peak (15,112)
  • +1,297 over 30 days · improving
  • +1,158 over 90 days
  • Next: Purple band at 15,000 — 344 to go
  • Reached: Purple band · Blue band · Light Blue band

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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate37.1%42.0%44.3%7.2% short
Shot accuracy0.1%9.6%11.9%11.7% short
Kill/death ratio0.860.981.030.17 short
Match win rate51.5%43.8%45.2%above

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGIlmar IistataPREMIER14,656 · Blue bandcsdb.gg/stats

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Performance scores

Aim54
Positioning55
Utility21

0–100 skill scores via Leetify.

Recent form

STEADY54–39–7Last 10054%Win rateLWLWWLTWLW

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · −3.0pp headshot accuracy · −73ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 528ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 13%
  • Avg reaction 526ms

Last 20

  • 11–8–1 · 55% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 563ms

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 (+2 against its own average).

Aim5.4
Utility2.1
Positioning5.5
Opening Duels3.0
Clutch3.6

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

donk

Plays most like donk 86% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Counter-strafing. Only 64% 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

Aim5.4
Positioning5.5
Utility2.1
Mechanics3.1
Opening Duels3.6
Win Impact8.8

Composite 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time550ms−69ms
first ⅓ avg 619ms → last ⅓ avg 550ms
Headshot accuracy13.0%−3.0%
first ⅓ avg 16.1% → last ⅓ avg 13.0%

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 · 13–11 · vertigo, 30 Jul →
63%Best headshot accuracy · 13–7 · mirage, 12 Aug →
359msFastest reaction time · 6–13 · inferno, 10 Sept →
13–0Biggest win · vertigo, 23 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
5–4In matches decided by ≤2 rounds
9Overtime games

Map breakdown

dust2Best map · 69% over 13ancientWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
nukeA2313–1057%-0.03
mirageC146–843%-0.01
officeB137–654%-0.02
infernoB137–654%-0.03
dust2S139–469%-0.00
anubisS64–267%0.00
ancientD62–433%-0.04
cacheA53–260%-0.01
vertigo—42–250%0.03
train—20–20%-0.06
overpass—11–0100%-0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

7,215Lifetime kills
0.86K/D
513Matches
51.5%Match win rate · Top 10% of Blue band
37.1%Headshot %
0.1%Shot accuracy
951MVPs
188Hours (in match)
299Bombs planted
73Bombs defused

Most-used weapons

Lifetime map wins

691nuke
653dust2
621office
616inferno
204train
185vertigo
33lake
12italy

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

Faceit stats

Combat

10Matches
50%Win rate
0.97Avg K/D
64.7ADR
30%Headshot %

Clutches & streaks

38%1v1 clutch win
20%1v2 clutch win
3Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage475%1.2817.0
Dust2333%0.569.3
Cache10%0.8122.0
Overpass10%0.447.0
Nuke1100%1.7112.0

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.

12.7%Headshot accuracy
32.0%Accuracy (enemy spotted)
30.8%Spray accuracy
63.7%Counter-strafing
7.1°Preaim
543msReaction time
43.9%T opening success
45.2%CT opening success
0.48Enemies flashed / flash
3.5%Flash assists
2.32HE damage / grenade
3.70Flashes / 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 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 12.6872% — 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 0.4766 — below the 0.5 mark we flag

    Grenade Lineups →
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.

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

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache6–13-0.103%22 Oct →
anubis13–60.0227%21 Oct →
office6–13-0.0417%21 Oct →
cache13–11-0.0212%21 Oct →
ancient13–7-0.0218%18 Oct →
inferno3–13-0.139%18 Oct →
nuke15–15-0.0710%17 Oct →
inferno13–60.009%15 Oct →
mirage4–13-0.0413%15 Oct →
inferno13–80.0415%15 Oct →
inferno1–13-0.0910%14 Oct →
dust212–16-0.0113%14 Oct →
office13–5-0.0216%9 Oct →
inferno13–40.0213%7 Oct →
train8–13-0.0316%7 Oct →
train7–13-0.0914%7 Oct →
mirage13–1-0.0338%5 Oct →
dust216–13-0.047%30 Sept →
anubis13–9-0.0218%28 Sept →
nuke13–10-0.0319%26 Sept →
dust215–150.0110%25 Sept →
office12–12-0.019%24 Sept →
nuke13–30.0313%24 Sept →
nuke13–40.045%23 Sept →
vertigo12–120.069%23 Sept →
vertigo13–00.024%23 Sept →
ancient12–16-0.024%23 Sept →
inferno13–90.0716%22 Sept →
ancient7–13-0.0816%22 Sept →
nuke13–10-0.0110%21 Sept →
mirage7–13-0.0212%21 Sept →
dust213–70.0223%21 Sept →
nuke13–9-0.065%21 Sept →
nuke12–12-0.0713%20 Sept →
nuke0–13-0.080%19 Sept →
anubis7–13-0.0212%18 Sept →
dust213–10-0.0125%18 Sept →
nuke13–7-0.0523%17 Sept →
anubis7–13-0.0612%17 Sept →
anubis13–90.0213%16 Sept →
office13–70.0615%12 Sept →
office8–13-0.073%12 Sept →
cache17–19-0.048%11 Sept →
mirage13–80.1026%11 Sept →
nuke13–70.0115%11 Sept →
mirage13–3-0.019%11 Sept →
office13–7-0.0417%10 Sept →
inferno6–13-0.050%10 Sept →
nuke4–13-0.0713%10 Sept →
dust28–13-0.0124%9 Sept →
mirage7–13-0.049%9 Sept →
cache13–110.0224%9 Sept →
office4–13-0.0925%9 Sept →
office11–13-0.0130%3 Sept →
office5–130.0018%3 Sept →
office13–6-0.0726%3 Sept →
dust213–60.0013%26 Aug →
cache13–90.0721%26 Aug →
mirage4–13-0.0217%20 Aug →
mirage9–130.0310%20 Aug →
nuke12–120.009%18 Aug →
office13–100.0512%18 Aug →
dust213–6-0.0214%17 Aug →
vertigo9–13-0.083%17 Aug →
inferno9–2-0.000%17 Aug →
office13–30.0017%15 Aug →
overpass13–5-0.0512%15 Aug →
mirage13–60.005%15 Aug →
ancient4–7-0.0622%14 Aug →
inferno6–13-0.0517%14 Aug →
inferno4–13-0.1229%14 Aug →
mirage14–160.009%13 Aug →
nuke11–4-0.036%12 Aug →
dust213–60.0013%12 Aug →
mirage13–70.0063%12 Aug →
nuke8–80.0012%10 Aug →
nuke5–9-0.073%10 Aug →
nuke9–30.0133%10 Aug →
nuke9–3-0.160%10 Aug →
dust213–100.0326%6 Aug →
mirage2–13-0.1127%6 Aug →
nuke9–13-0.0318%5 Aug →
anubis13–20.0611%5 Aug →
nuke13–110.029%5 Aug →
inferno13–60.0325%5 Aug →
ancient8–13-0.0814%5 Aug →
inferno10–13-0.040%5 Aug →
nuke2–13-0.1018%3 Aug →
nuke13–70.0614%2 Aug →
inferno14–12-0.028%2 Aug →
dust214–16-0.0924%31 Jul →
nuke13–60.017%31 Jul →
vertigo13–110.118%30 Jul →
mirage13–8-0.0317%30 Jul →
dust213–50.047%28 Jul →
dust213–60.0113%28 Jul →
office13–10-0.0114%28 Jul →
mirage8–13-0.0313%28 Jul →
nuke4–13-0.0331%19 Jul →
ancient13–8-0.0016%19 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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