Takgar

Takgar — CS2 Stats

FR76561199176977134[U:1:1216711406]Steam profile ↗✓ No bans

341Tracked matches59%Win rate2023Tracked since
CSDB Rating5.0 DevelopingClutch Specialist
WingmanMaster Guardian I
Ladder ranks via Leetify

Performance scores

Aim39
Positioning51
Utility28

0–100 skill scores via Leetify.

Recent form

HOT48–41–11Last 10048%Win rateWWWWWTWWLW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −6.3pp headshot accuracy · −23ms 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

  • 5–0 · 100% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 16%
  • Avg reaction 656ms

Last 10

  • 8–1–1 · 80% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 15%
  • Avg reaction 705ms

Last 20

  • 14–5–1 · 70% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 716ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+1.1 against its own average).

Aim3.9
Utility2.8
Positioning5.1
Opening Duels3.8
Clutch5.4

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

device

Plays most like device 77% 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. 772ms 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

Aim3.9
Positioning5.1
Utility2.8
Mechanics7.9
Opening Duels4.0
Win Impact7.9

Composite 5.0/10 (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 rating0.03+0.04
first ⅓ avg -0.01 → last ⅓ avg 0.03
Reaction time725ms−29ms
first ⅓ avg 754ms → last ⅓ avg 725ms
Headshot accuracy18.2%+3.7%
first ⅓ avg 14.5% → last ⅓ avg 18.2%

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

0.31Best match rating · 9–4 · inferno, 13 Jun →
46%Best headshot accuracy · 9–7 · vertigo, 15 Jun →
445msFastest reaction time · 9–3 · inferno, 12 Feb →
13–0Biggest win · dust2, 4 Nov →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W5Current streak
3–5In matches decided by ≤2 rounds
1Overtime games

Map breakdown

mirageBest map · 67% over 9ancientWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoC2812–1643%0.02
vertigoB209–1145%0.01
dust2C135–838%-0.01
nukeA127–558%-0.01
mirageS96–367%0.02
ancientD51–420%-0.01
anubis—42–250%0.00
overpass—42–250%0.01
office—22–0100%0.03
cache—21–150%0.07
italy—11–0100%0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

23Matches
35%Win rate
1.05Avg K/D
80.7ADR
40%Headshot %

Clutches & streaks

47%1v1 clutch win
29%1v2 clutch win
2Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage838%1.0515.6
Dust2757%1.2115.6
Ancient40%0.7712.5
Inferno333%1.1412.3
Nuke10%0.8814.0

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.

16.7%Headshot accuracy
31.2%Accuracy (enemy spotted)
31.6%Spray accuracy
85.6%Counter-strafing
11.7°Preaim
772msReaction time
41.3%T opening success
50.8%CT opening success
0.42Enemies flashed / flash
3.1%Flash assists
6.77HE damage / grenade
5.05Flashes / 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 771.863ms — above the 700ms 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 0.418 — 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.

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–5-0.008%4 Nov →
office13–100.0515%4 Nov →
inferno13–10-0.0814%4 Nov →
dust213–00.1120%4 Nov →
ancient13–90.0321%4 Nov →
inferno8–8-0.0015%4 Nov →
mirage13–20.176%3 Nov →
inferno13–5-0.0816%3 Nov →
vertigo5–13-0.0611%3 Nov →
nuke13–60.1023%3 Nov →
anubis13–60.1011%2 Nov →
office13–70.0118%2 Nov →
inferno6–90.0530%20 Jun →
anubis10–13-0.0525%20 Jun →
inferno9–4-0.0726%16 Jun →
inferno5–13-0.0621%16 Jun →
vertigo9–70.0946%15 Jun →
dust27–13-0.0214%15 Jun →
mirage13–10-0.0210%15 Jun →
dust213–100.0811%14 Jun →
vertigo8–80.1222%13 Jun →
inferno9–20.1916%13 Jun →
inferno8–80.1030%13 Jun →
inferno9–6-0.0712%13 Jun →
nuke4–9-0.060%13 Jun →
inferno8–80.0320%13 Jun →
nuke3–90.0429%13 Jun →
inferno9–40.3120%13 Jun →
inferno2–13-0.0611%12 Jun →
dust213–8-0.0511%12 Jun →
overpass13–40.0428%12 Jun →
ancient7–130.0024%12 Jun →
mirage11–130.0816%12 Jun →
vertigo8–80.0624%12 Jun →
vertigo9–40.2524%12 Jun →
nuke13–2-0.0313%11 Jun →
dust212–12-0.119%11 Jun →
vertigo3–9-0.0536%11 Jun →
dust28–130.0727%11 Jun →
vertigo9–20.1618%11 Jun →
inferno8–80.0318%11 Jun →
inferno8–80.0920%11 Jun →
nuke9–3-0.0219%11 Jun →
vertigo2–13-0.0318%10 Jun →
ancient5–13-0.0014%10 Jun →
vertigo9–50.0333%10 Jun →
nuke1–9-0.2417%10 Jun →
inferno9–60.0924%10 Jun →
inferno8–80.0521%10 Jun →
nuke9–60.0616%10 Jun →
inferno9–30.0820%10 Jun →
vertigo9–70.029%9 Jun →
dust28–13-0.0817%9 Jun →
dust213–9-0.0527%9 Jun →
nuke2–13-0.0125%9 Jun →
cache13–90.0717%8 Jun →
dust28–13-0.0229%7 Jun →
cache11–130.0825%7 Jun →
nuke2–9-0.1032%7 Jun →
inferno8–80.0214%7 Jun →
vertigo9–40.0529%7 Jun →
inferno2–9-0.1032%7 Jun →
vertigo4–13-0.0225%6 Jun →
inferno13–4-0.068%21 Feb →
inferno11–13-0.0211%20 Feb →
anubis11–13-0.0719%20 Feb →
dust28–13-0.0517%20 Feb →
nuke9–20.1029%19 Feb →
inferno6–9-0.0816%19 Feb →
vertigo9–50.0414%19 Feb →
mirage5–130.0019%17 Feb →
inferno4–13-0.0113%17 Feb →
mirage10–13-0.0226%16 Feb →
ancient13–160.006%13 Feb →
vertigo5–9-0.1115%13 Feb →
vertigo7–9-0.1210%13 Feb →
mirage8–2-0.027%13 Feb →
vertigo9–4-0.0511%12 Feb →
inferno5–9-0.079%12 Feb →
inferno9–10.1310%12 Feb →
inferno9–30.0214%12 Feb →
italy13–50.028%12 Feb →
vertigo5–13-0.0114%11 Feb →
dust212–120.1014%11 Feb →
vertigo13–11-0.0723%11 Feb →
vertigo7–13-0.0215%11 Feb →
overpass6–13-0.028%11 Feb →
dust29–13-0.097%11 Feb →
anubis13–70.0418%10 Feb →
overpass13–60.0113%10 Feb →
inferno13–90.0420%10 Feb →
vertigo7–13-0.039%10 Feb →
nuke13–9-0.0111%10 Feb →
inferno8–13-0.0213%10 Feb →
mirage13–100.0615%9 Feb →
dust213–70.0325%9 Feb →
mirage13–4-0.0612%9 Feb →
overpass4–130.007%6 Feb →
nuke13–70.0017%6 Feb →
ancient1–13-0.0631%6 Feb →

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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