Tao

Tao — CS2 Stats

FR76561199066528746[U:1:1106263018]Steam profile ↗✓ No bans

69Tracked matches41%Win rate2025Tracked since
CSDB Rating4.3 DevelopingPositional Player
Ladder ranks via Leetify

Performance scores

Aim58
Positioning36
Utility34

0–100 skill scores via Leetify.

Recent form

COLD29–38–2Last 6942%Win rateLLLLLWWLLW

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · +0.3pp headshot accuracy · −5ms reaction

Win rate down 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

  • 0–5 · 0% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 19%
  • Avg reaction 741ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 644ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 17%
  • Avg reaction 646ms

Newest first, from the last 69 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 (+1.3 against its own average).

Aim5.8
Utility3.4
Positioning3.6
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

iM

Plays most like iM 91% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning profile; lower opening-duel success.

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. 647ms 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

Aim5.8
Positioning3.6
Utility3.4
Mechanics6.8
Opening Duels0.9
Win Impact2.1

Composite 4.3/10 (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-0.03−0.04
first ⅓ avg 0.01 → last ⅓ avg -0.03
Reaction time655ms−100ms
first ⅓ avg 755ms → last ⅓ avg 655ms
Headshot accuracy16.6%+0.1%
first ⅓ avg 16.5% → last ⅓ avg 16.6%

Rolling 5-match average across the last 69 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.16Best match rating · 13–3 · inferno, 1 Apr →
39%Best headshot accuracy · 5–13 · inferno, 15 Oct →
453msFastest reaction time · 5–13 · inferno, 1 Oct →
13–1Biggest win · mirage, 1 Oct →

Across the last 69 tracked matches.

Highlights

3Longest win streak
L5Current streak
5–3In matches decided by ≤2 rounds
1Overtime games

Map breakdown

anubisBest map · 60% over 5dust2Weakest map · 40% over 20
MapGradePlayedRecordWin rateAvg rating
dust2C208–1240%-0.02
mirageA1810–856%0.00
infernoC156–940%-0.03
anubisA53–260%-0.00
nuke—32–167%-0.03
vertigo—30–30%-0.03
cache—20–20%-0.04
poseidon—20–20%-0.05
ancient—10–10%-0.04

Across the last 69 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (40% over 20). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

15.8%Headshot accuracy
33.5%Accuracy (enemy spotted)
31.6%Spray accuracy
80.7%Counter-strafing
9.3°Preaim
647msReaction time
34.5%T opening success
32.6%CT opening success
0.59Enemies flashed / flash
1.9%Flash assists
4.50HE damage / grenade
4.06Flashes / 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. 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 34.5466% — below the 40% mark we flag

Spend your practice time on Dust 2

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

40% win rate across 20 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache4–13-0.0027%7 Oct →
anubis2–13-0.0738%7 Oct →
cache2–13-0.070%6 Oct →
poseidon2–9-0.0311%6 Oct →
inferno3–13-0.1020%5 Oct →
mirage13–11-0.0013%1 Oct →
nuke13–8-0.0525%1 Oct →
dust22–13-0.0916%1 Oct →
inferno5–13-0.0214%1 Oct →
mirage13–10.069%1 Oct →
ancient1–13-0.0421%1 Oct →
mirage13–60.0732%1 Oct →
anubis13–11-0.040%1 Oct →
nuke4–130.0021%30 Sept →
mirage13–40.0219%30 Sept →
inferno13–6-0.0718%30 Sept →
inferno5–9-0.0225%30 Sept →
dust24–13-0.0713%30 Sept →
anubis13–40.0511%29 Sept →
mirage9–13-0.0110%29 Sept →
vertigo4–13-0.0618%29 Sept →
dust29–3-0.078%29 Sept →
mirage11–13-0.0113%29 Sept →
anubis13–160.0520%28 Sept →
inferno11–13-0.056%28 Sept →
poseidon7–9-0.0719%28 Sept →
inferno13–11-0.0332%28 Sept →
mirage13–8-0.0312%28 Sept →
vertigo9–130.0211%27 Sept →
dust213–100.0114%27 Sept →
dust24–13-0.0926%13 Sept →
dust212–120.0317%26 Nov →
inferno8–13-0.090%26 Nov →
dust210–13-0.0815%20 Nov →
mirage13–4-0.0316%19 Nov →
inferno5–13-0.0339%15 Oct →
nuke13–9-0.0526%25 Sept →
dust26–13-0.0913%18 Sept →
mirage6–13-0.094%18 Sept →
anubis13–40.0026%18 Sept →
dust24–130.0710%24 Apr →
dust213–4-0.0120%24 Apr →
dust29–13-0.0120%24 Apr →
dust24–0-0.0320%24 Apr →
mirage13–8-0.0611%24 Apr →
mirage9–13-0.049%10 Apr →
dust213–5-0.0412%10 Apr →
dust28–130.025%10 Apr →
inferno9–130.0116%9 Apr →
mirage5–130.0015%9 Apr →
dust213–10.0718%9 Apr →
mirage12–120.0413%9 Apr →
dust213–80.0711%9 Apr →
inferno4–13-0.0211%8 Apr →
dust26–130.0115%8 Apr →
mirage13–110.1211%8 Apr →
mirage13–3-0.0711%8 Apr →
mirage13–10.1121%8 Apr →
inferno3–13-0.075%8 Apr →
vertigo2–6-0.0438%7 Apr →
inferno13–70.0114%7 Apr →
dust213–80.0519%7 Apr →
mirage5–13-0.037%7 Apr →
dust28–13-0.0419%6 Apr →
inferno13–11-0.0614%6 Apr →
inferno13–7-0.0721%6 Apr →
mirage8–130.0537%2 Apr →
dust28–13-0.0422%1 Apr →
inferno13–30.1623%1 Apr →

Match data via Leetify.

Recent teammates

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

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