Shakki

Shakki — CS2 Stats

76561197969147207[U:1:8881479]Steam profile ↗✓ No bans

1,959Tracked matches63%Win rate2020Tracked since
CSDB Rating5.4 DevelopingSupport
FaceitLevel 8Top 31.2% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGShakkiFACEITLevel 8STANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim46
Positioning50
Utility61

0–100 skill scores via Leetify.

Recent form

STEADY53–47Last 10053%Win rateLWLWWWWLLW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −1.7pp headshot accuracy · −123ms 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 -0.01
  • Avg headshot accuracy 9%
  • Avg reaction 466ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 10%
  • Avg reaction 515ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 576ms

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 (+1.6 against its own average).

Aim4.6
Utility6.1
Positioning5.0
Opening Duels3.5
Clutch3.4

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 72% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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. 586ms 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

Aim4.6
Positioning5.0
Utility6.1
Mechanics6.2
Opening Duels2.8
Win Impact9.4

Composite 5.4/10 (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 time601ms−20ms
first ⅓ avg 621ms → last ⅓ avg 601ms
Headshot accuracy9.8%−3.4%
first ⅓ avg 13.2% → last ⅓ avg 9.8%

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 · 13–3 · inferno, 25 Aug →
29%Best headshot accuracy · 13–1 · dust2, 23 Dec →
383msFastest reaction time · 6–13 · inferno, 19 Sept →
13–1Biggest win · dust2, 23 Dec →

Across the last 100 tracked matches.

Highlights

5Longest win streak
9–6In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 67% over 21mirageWeakest map · 31% over 13
MapGradePlayedRecordWin rateAvg rating
infernoC2610–1638%-0.01
dust2A2615–1158%0.00
anubisS2114–767%-0.01
mirageD134–931%-0.03
ancient—42–250%-0.04
cache—44–0100%-0.02
nuke—42–250%-0.02
train—22–0100%-0.01

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (31% over 13). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,512Matches
50%Win rate
1.03Avg K/D
74.0ADR
28%Headshot %

Clutches & streaks

37%1v1 clutch win
18%1v2 clutch win
10Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Dust225855%1.1015.1
Inferno21252%0.9914.6
Mirage18445%0.9514.1
Anubis14450%0.9113.4
Ancient6941%0.8213.2
Nuke5648%0.9613.3
Vertigo3030%0.7913.4
Cache2564%0.9114.2

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.

10.4%Headshot accuracy
32.3%Accuracy (enemy spotted)
32.9%Spray accuracy
77.8%Counter-strafing
11.6°Preaim
586msReaction time
35.0%T opening success
47.1%CT opening success
0.49Enemies flashed / flash
5.7%Flash assists
8.74HE damage / grenade
11.86Flashes / 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 10.3817% — 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 0.4867 — below the 0.5 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 34.9517% — 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.

31% 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
inferno6–13-0.069%19 Sept →
ancient13–30.058%6 Sept →
inferno9–13-0.095%6 Sept →
cache13–10-0.0311%2 Sept →
cache13–70.0611%25 Aug →
inferno13–30.118%25 Aug →
cache13–7-0.0914%24 Aug →
inferno4–13-0.0212%23 Aug →
inferno2–13-0.0712%22 Aug →
mirage13–11-0.0812%22 Aug →
inferno4–13-0.046%22 Aug →
inferno5–13-0.0312%19 Aug →
inferno22–190.0521%1 Aug →
dust213–100.0517%28 Jul →
mirage20–22-0.038%25 Jul →
nuke13–8-0.017%21 Jul →
ancient13–2-0.018%17 Jul →
cache13–4-0.0114%15 Jul →
dust213–11-0.0412%15 Jul →
mirage13–5-0.0114%4 Jul →
dust28–13-0.0713%26 Jun →
inferno16–130.0111%13 Jun →
anubis16–13-0.0012%1 Jun →
dust213–50.078%31 Jan →
dust213–40.0513%24 Jan →
mirage13–2-0.048%24 Jan →
inferno11–130.024%24 Jan →
inferno7–20.030%24 Jan →
inferno13–16-0.048%10 Jan →
inferno4–13-0.040%22 Mar →
mirage8–13-0.0115%22 Mar →
anubis13–9-0.046%15 Mar →
inferno13–100.037%14 Mar →
dust210–130.0215%8 Mar →
mirage5–13-0.038%7 Mar →
dust20–10-0.079%7 Mar →
anubis13–8-0.0010%6 Mar →
inferno13–16-0.0312%5 Mar →
dust29–13-0.0725%2 Mar →
dust213–7-0.0414%31 Jan →
mirage10–130.0217%30 Jan →
dust213–70.0317%26 Jan →
dust26–13-0.0415%20 Jan →
mirage1–13-0.0416%18 Jan →
anubis13–30.019%18 Jan →
inferno13–6-0.018%17 Jan →
train13–11-0.0410%16 Jan →
dust27–130.0311%12 Jan →
dust216–130.0314%11 Jan →
nuke14–16-0.026%10 Jan →
dust26–12-0.028%9 Jan →
anubis13–8-0.019%8 Jan →
mirage16–19-0.073%7 Jan →
mirage10–13-0.056%7 Jan →
inferno13–11-0.026%5 Jan →
dust213–80.0613%5 Jan →
dust213–110.0511%4 Jan →
anubis13–10-0.038%1 Jan →
inferno8–13-0.0111%1 Jan →
anubis9–00.019%1 Jan →
anubis19–17-0.056%1 Jan →
anubis2–13-0.0815%31 Dec →
anubis13–20.0610%31 Dec →
dust213–90.018%29 Dec →
anubis13–80.015%29 Dec →
ancient8–13-0.0912%26 Dec →
anubis6–130.006%24 Dec →
dust213–100.0521%24 Dec →
dust213–10.0729%23 Dec →
inferno8–13-0.0119%23 Dec →
anubis11–13-0.0421%23 Dec →
dust213–11-0.0312%19 Dec →
inferno19–17-0.046%18 Dec →
anubis7–13-0.0212%17 Dec →
inferno9–13-0.0613%16 Dec →
inferno10–13-0.033%15 Dec →
anubis13–80.0611%14 Dec →
mirage4–13-0.082%10 Dec →
anubis11–13-0.036%7 Dec →
dust213–100.027%7 Dec →
anubis16–120.0124%7 Dec →
inferno2–13-0.033%7 Dec →
dust210–13-0.0516%27 Nov →
inferno13–110.0714%27 Nov →
anubis6–13-0.0410%26 Nov →
dust26–13-0.025%24 Nov →
anubis13–80.1010%24 Nov →
anubis13–70.0920%20 Nov →
dust213–90.0117%16 Nov →
train13–50.027%14 Nov →
inferno9–13-0.038%12 Nov →
dust211–130.0512%10 Nov →
mirage9–13-0.0422%27 Oct →
inferno13–8-0.0523%11 Oct →
dust29–13-0.0414%11 Oct →
nuke7–13-0.1118%11 Oct →
ancient8–13-0.100%11 Oct →
anubis4–13-0.1228%5 Oct →
mirage13–60.0511%5 Oct →
nuke13–50.0613%5 Oct →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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