Dastaguy

Dastaguy — CS2 Stats

76561198918850897[U:1:958585169]Steam profile ↗✓ No bans

132Tracked matches46%Win rate2023Tracked since
CSDB Rating5.2 DevelopingPositional Player
Ladder ranks via Leetify

Performance scores

Aim68
Positioning58
Utility28

0–100 skill scores via Leetify.

Recent form

COLD29–47–11Last 8733%Win rateLTWWLWLTLL

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · −4.8pp headshot accuracy · −75ms 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 20%
  • Avg reaction 491ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 22%
  • Avg reaction 498ms

Last 20

  • 8–9–3 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 24%
  • Avg reaction 535ms

Newest first, from the last 87 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 (+1.8 against its own average).

Aim6.8
Utility2.8
Positioning5.8
Opening Duels3.4

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

donk

Plays most like donk 92% 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 574ms 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

Aim6.8
Positioning5.8
Utility2.8
Mechanics6.2
Opening Duels3.1
Win Impact3.7

Composite 5.2/10 (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 rating0.02+0.04
first ⅓ avg -0.01 → last ⅓ avg 0.02
Reaction time569ms−32ms
first ⅓ avg 601ms → last ⅓ avg 569ms
Headshot accuracy21.4%+7.4%
first ⅓ avg 14.0% → last ⅓ avg 21.4%

Rolling 5-match average across the last 87 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.24Best match rating · 13–0 · inferno, 18 May →
56%Best headshot accuracy · 12–12 · mirage, 13 May →
359msFastest reaction time · 0–8 · ancient, 25 Aug →
13–0Biggest win · inferno, 18 May →

Across the last 87 tracked matches.

Highlights

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

Map breakdown

infernoBest map · 57% over 7mirageWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
dust2C249–1538%0.01
nukeC176–1135%0.00
ancientD144–1029%0.01
mirageD92–722%-0.03
infernoA74–357%0.04
trainC52–340%-0.02
vertigo—21–150%0.01
cache—20–20%-0.01
overpass—21–150%0.01
anubis—20–20%-0.06
warden—10–10%-0.01
italy—10–10%0.03
office—10–10%0.01

Across the last 87 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (22% over 9). Start with the 5 essential Mirage 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.

20.9%Headshot accuracy
36.9%Accuracy (enemy spotted)
42.2%Spray accuracy
77.8%Counter-strafing
14.0°Preaim
574msReaction time
45.2%T opening success
39.6%CT opening success
0.39Enemies flashed / flash
4.4%Flash assists
1.55HE damage / grenade
13.86Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 14.0068° — above the 12° 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 0.3899 — below the 0.5 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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient5–13-0.0018%9 Sept →
vertigo12–12-0.0220%5 Sept →
vertigo13–80.0513%5 Sept →
dust213–70.1130%3 Sept →
ancient2–130.0619%2 Sept →
nuke13–80.0020%2 Sept →
dust25–130.0521%30 Aug →
dust212–12-0.0021%30 Aug →
ancient0–8-0.0538%25 Aug →
train5–13-0.0317%25 Aug →
dust26–130.0330%12 Aug →
train13–50.0617%12 Aug →
cache4–13-0.0241%31 Jul →
dust213–60.0026%30 Jul →
nuke13–100.0719%30 Jul →
cache5–130.0119%29 Jul →
inferno12–12-0.0220%28 Jul →
dust29–20.2030%28 Jul →
dust29–40.1035%13 Jul →
mirage5–130.0227%25 Jun →
dust213–10-0.0615%18 Jun →
nuke0–13-0.040%4 Jun →
nuke13–60.0218%2 Jun →
nuke7–130.0718%2 Jun →
ancient11–13-0.0015%1 Jun →
dust213–20.0914%1 Jun →
dust212–12-0.0717%23 May →
dust211–13-0.0123%21 May →
dust213–70.0417%21 May →
mirage0–13-0.0424%19 May →
inferno13–00.2436%18 May →
dust213–20.0628%18 May →
mirage12–12-0.0056%13 May →
ancient13–110.1422%13 May →
ancient13–80.0415%11 May →
ancient13–11-0.0019%5 May →
dust212–120.0219%3 May →
overpass13–4-0.0319%3 May →
dust213–30.0413%2 May →
inferno10–13-0.0115%24 Apr →
mirage13–90.0222%24 Apr →
inferno13–110.0916%19 Apr →
dust28–13-0.0519%17 Apr →
dust24–130.0120%10 Apr →
ancient1–5-0.0729%10 Apr →
mirage12–12-0.1024%9 Apr →
mirage5–13-0.0414%7 Apr →
nuke3–13-0.0219%7 Apr →
mirage5–130.0330%7 Apr →
mirage6–13-0.0826%7 Apr →
dust22–8-0.0730%7 Apr →
dust28–13-0.0126%7 Apr →
nuke8–13-0.0720%7 Apr →
mirage13–7-0.0620%6 Apr →
ancient2–13-0.0920%5 Apr →
ancient12–120.0820%3 Apr →
nuke13–90.0419%3 Apr →
nuke1–13-0.0419%2 Apr →
nuke4–130.0114%26 Mar →
warden5–13-0.0121%24 Mar →
ancient8–130.070%22 Mar →
inferno13–4-0.029%22 Mar →
dust26–13-0.0514%16 Mar →
ancient4–130.0419%16 Mar →
dust25–13-0.0720%9 Mar →
italy9–130.0316%4 Mar →
office8–130.0119%4 Mar →
nuke4–130.0113%4 Mar →
train12–12-0.040%2 Mar →
ancient13–8-0.024%2 Mar →
nuke11–30.0033%1 Mar →
nuke13–00.0613%18 Feb →
nuke2–130.0120%15 Feb →
dust211–13-0.0615%3 Feb →
dust27–13-0.0217%3 Feb →
nuke12–120.016%19 Jan →
ancient6–13-0.0720%19 Jan →
nuke7–13-0.0216%19 Jan →
train1–13-0.093%19 Jan →
dust24–13-0.094%19 Jan →
train13–90.017%18 Jan →
overpass1–130.0525%15 Jan →
anubis1–13-0.0812%15 Jan →
anubis6–13-0.0320%14 Jan →
inferno12–120.0013%8 Oct →
inferno13–70.010%1 Jul →
nuke1–13-0.1033%26 May →

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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