RatataK

RatataK — CS2 Stats

76561197986184754[U:1:25919026]Steam profile ↗✓ No bans

702Tracked matches15%Win rate2020Tracked since
CSDB Rating3.5 LearningSupport
Ladder ranks via Leetify

Performance scores

Aim45
Positioning33
Utility38

0–100 skill scores via Leetify.

Recent form

COLD24–70–6Last 10024%Win rateLLWLLWLLLL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −5.8pp headshot accuracy · −38ms reaction

Win rate 0pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 12%
  • Avg reaction 714ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 10%
  • Avg reaction 691ms

Last 20

  • 4–16 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 710ms

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 (+1.4 against its own average).

Aim4.5
Utility3.8
Positioning3.3
Opening Duels0.0

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

Twistzz

Plays most like Twistzz 86% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 721ms 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

Aim4.5
Positioning3.3
Utility3.8
Mechanics5.9
Opening Duels0.0
Win Impact0.0

Composite 3.5/10 (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-0.05+0.03
first ⅓ avg -0.08 → last ⅓ avg -0.05
Reaction time721ms−45ms
first ⅓ avg 766ms → last ⅓ avg 721ms
Headshot accuracy13.7%−1.9%
first ⅓ avg 15.6% → last ⅓ avg 13.7%

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

0.07Best match rating · 12–12 · dust2, 21 Sept →
36%Best headshot accuracy · 13–9 · inferno, 15 Nov →
453msFastest reaction time · 7–13 · ancient, 3 Sept →
13–3Biggest win · vertigo, 18 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L2Current streak
6–7In matches decided by ≤2 rounds
3Overtime games

Map breakdown

cacheBest map · 40% over 5mirageWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
dust2D408–3220%-0.06
infernoD143–1121%-0.05
nukeD92–722%-0.08
mirageD81–713%-0.07
anubisD82–625%-0.09
ancientD62–433%-0.10
cacheC52–340%-0.07
trainC52–340%-0.06
vertigo—21–150%-0.07
basalt—21–150%-0.07
edin—10–10%-0.08

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (13% over 8). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1Matches
0%Win rate
0.29Avg K/D
—ADR
40%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

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.

13.3%Headshot accuracy
31.8%Accuracy (enemy spotted)
30.9%Spray accuracy
76.5%Counter-strafing
7.9°Preaim
721msReaction time
23.4%T opening success
21.2%CT opening success
0.54Enemies flashed / flash
4.3%Flash assists
9.74HE damage / grenade
3.09Flashes / 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 13.2786% — 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 720.7063ms — above the 700ms mark we flag

    Aim Training →
  3. Grenades & Utility

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

    Flashes per match 3.0883 — below the 4 mark we flag

    Grenade Lineups →
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.

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

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno7–13-0.0116%3 Oct →
nuke3–13-0.0813%3 Oct →
mirage13–11-0.0415%3 Oct →
inferno1–13-0.120%2 Oct →
dust28–130.0118%2 Oct →
dust213–8-0.069%2 Oct →
nuke3–13-0.083%2 Oct →
anubis2–13-0.090%2 Oct →
dust210–13-0.0613%2 Oct →
inferno14–160.0017%2 Oct →
inferno6–13-0.0229%2 Oct →
mirage9–13-0.0214%2 Oct →
inferno9–13-0.0420%2 Oct →
mirage4–13-0.0415%2 Oct →
cache4–13-0.1122%29 Sept →
dust24–13-0.0715%29 Sept →
dust28–13-0.084%29 Sept →
ancient13–5-0.0427%29 Sept →
inferno4–00.038%29 Sept →
dust28–13-0.018%27 Sept →
inferno4–13-0.0029%27 Sept →
dust26–13-0.0613%25 Sept →
dust212–12-0.0413%25 Sept →
dust25–13-0.0313%25 Sept →
dust26–13-0.0911%23 Sept →
dust26–13-0.1012%23 Sept →
dust211–13-0.045%21 Sept →
nuke12–12-0.089%21 Sept →
vertigo10–13-0.0513%21 Sept →
dust212–120.079%21 Sept →
ancient3–13-0.1613%21 Sept →
inferno1–13-0.1024%19 Sept →
dust24–13-0.0923%19 Sept →
dust213–11-0.068%19 Sept →
dust28–13-0.0611%19 Sept →
dust24–13-0.100%19 Sept →
dust24–13-0.120%19 Sept →
mirage8–13-0.0510%19 Sept →
cache2–13-0.085%19 Sept →
dust23–13-0.0713%19 Sept →
vertigo13–3-0.1016%18 Sept →
dust29–13-0.0614%18 Sept →
inferno16–13-0.0611%17 Sept →
nuke13–8-0.0311%16 Sept →
dust23–13-0.0712%16 Sept →
anubis11–13-0.0814%14 Sept →
dust210–13-0.0633%14 Sept →
inferno14–16-0.0717%13 Sept →
nuke13–7-0.0514%13 Sept →
nuke3–13-0.1212%12 Sept →
dust213–6-0.0022%12 Sept →
inferno4–13-0.0319%12 Sept →
anubis4–13-0.027%12 Sept →
dust28–13-0.0324%12 Sept →
cache12–12-0.0629%11 Sept →
dust211–13-0.0810%11 Sept →
inferno6–13-0.1118%11 Sept →
mirage10–13-0.107%11 Sept →
anubis11–13-0.117%11 Sept →
nuke8–13-0.065%11 Sept →
train12–12-0.046%11 Sept →
anubis6–13-0.100%11 Sept →
cache13–11-0.0711%11 Sept →
dust26–13-0.0431%6 Sept →
dust29–13-0.088%6 Sept →
dust213–10-0.059%5 Sept →
nuke2–13-0.1518%3 Sept →
ancient7–13-0.0816%3 Sept →
dust213–9-0.074%3 Sept →
dust29–13-0.0518%3 Sept →
cache13–6-0.0422%2 Sept →
mirage4–13-0.090%2 Sept →
inferno5–13-0.0314%2 Sept →
nuke5–13-0.0810%2 Sept →
anubis7–13-0.093%2 Sept →
dust22–13-0.0915%2 Sept →
dust28–13-0.0620%1 Sept →
dust28–13-0.0511%1 Sept →
dust211–13-0.0520%17 Nov →
ancient9–13-0.118%16 Nov →
train13–5-0.0516%16 Nov →
train13–7-0.0511%16 Nov →
dust213–11-0.1224%16 Nov →
basalt4–13-0.0919%16 Nov →
mirage10–13-0.1118%15 Nov →
anubis13–11-0.1023%15 Nov →
inferno13–9-0.1136%15 Nov →
train12–12-0.0718%15 Nov →
dust213–11-0.0819%15 Nov →
basalt13–6-0.058%15 Nov →
ancient13–8-0.0818%15 Nov →
edin5–13-0.0829%15 Nov →
train4–13-0.1015%15 Nov →
dust21–13-0.1119%21 Sept →
dust24–13-0.0829%21 Sept →
dust213–8-0.0815%21 Sept →
dust24–13-0.0911%18 Sept →
mirage10–13-0.1018%18 Sept →
ancient9–13-0.118%18 Sept →
anubis13–10-0.080%18 Sept →

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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