ivdza.

ivdza. — CS2 Stats

76561197991757836[U:1:31492108]Steam profile ↗✓ No bans

829Tracked matches33%Win rate2025Tracked since
CSDB Rating4.1 DevelopingSupport
Ladder ranks via Leetify

Performance scores

Aim48
Positioning49
Utility49

0–100 skill scores via Leetify.

Recent form

STEADY42–57–1Last 10042%Win rateLLLWWWLLWL

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −1.4pp headshot accuracy · −8ms reaction

Win rate up 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

  • 2–3 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 10%
  • Avg reaction 680ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 10%
  • Avg reaction 643ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 647ms

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 (+2.2 against its own average).

Aim4.8
Utility4.9
Positioning4.9
Opening Duels1.1
Clutch0.0

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

ZywOo

Plays most like ZywOo 77% 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. 610ms 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

Aim4.8
Positioning4.9
Utility4.9
Mechanics5.1
Opening Duels1.6
Win Impact0.0

Composite 4.1/10 (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-0.02−0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time615ms−70ms
first ⅓ avg 685ms → last ⅓ avg 615ms
Headshot accuracy10.8%−4.2%
first ⅓ avg 15.0% → last ⅓ avg 10.8%

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

0.12Best match rating · 13–2 · inferno, 6 Aug →
31%Best headshot accuracy · 5–13 · nuke, 27 Jun →
422msFastest reaction time · 6–13 · ancient, 24 Aug →
13–0Biggest win · inferno, 20 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L3Current streak
3–10In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 54% over 26ancientWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
dust2B2614–1254%-0.01
cacheB2110–1148%-0.01
infernoC198–1142%-0.02
mirageB136–746%-0.01
ancientD81–713%-0.04
anubisD62–433%-0.02
nuke—41–325%-0.03
train—20–20%-0.02
overpass—10–10%0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

14Matches
43%Win rate
0.74Avg K/D
66.0ADR
38%Headshot %

Clutches & streaks

0%1v1 clutch win
17%1v2 clutch win
4Longest win streak

Recent Faceit resultsLWWWW

MapMatchesWin rateAvg K/DAvg kills
Inferno425%0.7715.8
Ancient367%0.6310.7
Mirage250%0.8611.0
Anubis20%0.589.5
Nuke250%0.9615.0
Cache1100%0.678.0

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.

11.0%Headshot accuracy
37.4%Accuracy (enemy spotted)
31.6%Spray accuracy
72.9%Counter-strafing
11.4°Preaim
610msReaction time
38.6%T opening success
34.0%CT opening success
0.55Enemies flashed / flash
3.1%Flash assists
9.76HE damage / grenade
2.91Flashes / 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 10.9642% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.9138 — below the 4 mark we flag

    Grenade Lineups →
  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 38.5572% — below the 40% mark we flag

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.

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache4–13-0.0413%10 Oct →
cache11–13-0.058%26 Sept →
mirage4–13-0.086%26 Sept →
dust213–80.0411%25 Sept →
dust213–90.0213%20 Sept →
inferno13–10-0.039%20 Sept →
cache7–13-0.0113%6 Sept →
dust23–100.008%6 Sept →
cache13–80.0211%4 Sept →
mirage10–130.028%4 Sept →
dust210–13-0.029%4 Sept →
dust213–90.0313%3 Sept →
inferno13–90.0012%31 Aug →
dust27–13-0.0715%31 Aug →
cache6–13-0.0311%31 Aug →
overpass7–130.039%29 Aug →
train6–13-0.0015%29 Aug →
cache3–13-0.016%29 Aug →
inferno5–13-0.0711%29 Aug →
dust27–13-0.0214%29 Aug →
mirage13–11-0.0114%25 Aug →
ancient6–13-0.0714%24 Aug →
inferno13–20.020%23 Aug →
dust211–13-0.099%22 Aug →
inferno9–13-0.0310%22 Aug →
cache13–10-0.0114%20 Aug →
inferno13–0-0.0817%20 Aug →
dust25–13-0.0215%20 Aug →
inferno9–130.0213%19 Aug →
anubis10–13-0.017%19 Aug →
dust213–40.058%19 Aug →
train10–13-0.0313%17 Aug →
cache13–5-0.058%15 Aug →
ancient11–130.0118%13 Aug →
mirage2–13-0.0914%13 Aug →
inferno9–13-0.0510%12 Aug →
dust213–8-0.0217%12 Aug →
dust213–40.0311%11 Aug →
mirage11–13-0.028%9 Aug →
cache13–8-0.0312%9 Aug →
dust28–13-0.0914%9 Aug →
mirage10–13-0.0413%7 Aug →
cache4–13-0.027%7 Aug →
inferno13–20.1214%6 Aug →
cache7–130.0521%5 Aug →
anubis2–13-0.0917%5 Aug →
inferno1–13-0.143%4 Aug →
dust213–4-0.0116%3 Aug →
inferno13–4-0.0613%3 Aug →
mirage13–11-0.0218%3 Aug →
cache6–13-0.054%2 Aug →
anubis4–13-0.0915%2 Aug →
ancient8–13-0.0527%1 Aug →
dust213–100.0814%1 Aug →
inferno11–130.0610%30 Jul →
dust26–13-0.0315%30 Jul →
cache13–50.0412%28 Jul →
anubis13–50.074%28 Jul →
ancient9–13-0.0811%27 Jul →
mirage13–100.079%27 Jul →
cache13–50.0412%26 Jul →
mirage11–130.0210%26 Jul →
dust210–130.0316%26 Jul →
inferno13–40.0215%26 Jul →
cache13–70.1014%25 Jul →
dust211–130.0124%22 Jul →
nuke11–13-0.0121%22 Jul →
dust212–12-0.0013%20 Jul →
dust213–30.0426%19 Jul →
anubis8–13-0.039%19 Jul →
inferno11–13-0.056%19 Jul →
cache13–9-0.0017%18 Jul →
dust26–13-0.0219%17 Jul →
cache13–5-0.0224%16 Jul →
inferno5–13-0.0211%15 Jul →
ancient10–13-0.0015%15 Jul →
ancient13–60.0311%12 Jul →
mirage13–80.089%9 Jul →
anubis13–100.0110%8 Jul →
inferno4–13-0.0316%5 Jul →
cache13–11-0.0015%4 Jul →
inferno13–7-0.058%4 Jul →
dust213–4-0.0317%4 Jul →
dust213–5-0.068%2 Jul →
dust213–60.0113%1 Jul →
mirage3–13-0.085%1 Jul →
cache9–13-0.048%29 Jun →
nuke10–130.0219%29 Jun →
mirage13–7-0.0224%29 Jun →
cache5–13-0.0426%28 Jun →
ancient9–13-0.0622%28 Jun →
nuke5–13-0.0431%27 Jun →
cache10–130.0115%27 Jun →
inferno11–13-0.016%27 Jun →
inferno9–130.0212%26 Jun →
mirage13–50.0113%26 Jun →
dust213–9-0.0118%25 Jun →
ancient4–13-0.0615%24 Jun →
nuke5–0-0.0820%24 Jun →
dust213–8-0.0312%24 Jun →

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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