Screambath

Screambath — CS2 Stats

76561198079435996[U:1:119170268]Steam profile ↗✓ No bans

364Tracked matches21%Win rate2020Tracked since
CSDB Rating3.1 LearningPositional Player
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 4,094 -905 5 Nov – 15 Jan · 10 days played
3,6685,376peak 5,3765 Nov15 Jan
5,493Peak Premier in tracked matches
45Days played since 2024-11-05

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim25
Positioning57
Utility35

0–100 skill scores via Leetify.

Recent form

COLD38–55–7Last 10038%Win rateLLLLLLLLLW

Last 10 vs previous 10: −30pp win rate · −0.02 avg rating · +0.4pp headshot accuracy · +92ms reaction

Win rate down 30pp 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 -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 675ms

Last 10

  • 1–9 · 10% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 708ms

Last 20

  • 5–14–1 · 25% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 13%
  • Avg reaction 662ms

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: Positional Player — Positioning stands above the rest of this profile (+1.9 against its own average).

Aim2.5
Utility3.5
Positioning5.7
Opening Duels2.1

Strong CT-side openerEffective flashes

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 61% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 49% on CT to 21% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 647ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim2.5
Positioning5.7
Utility3.5
Mechanics3.2
Opening Duels2.4
Win Impact0.0

Composite 3.1/10 (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-0.01−0.02
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time637ms−15ms
first ⅓ avg 653ms → last ⅓ avg 637ms
Headshot accuracy12.5%+1.3%
first ⅓ avg 11.2% → last ⅓ avg 12.5%

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

0.16Best match rating · 13–0 · nuke, 15 Dec →
32%Best headshot accuracy · 3–13 · dust2, 1 Jun →
438msFastest reaction time · 4–13 · dust2, 10 Sept →
13–0Biggest win · nuke, 15 Dec →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L9Current streak
8–4In matches decided by ≤2 rounds
2Overtime games

Map breakdown

trainBest map · 64% over 11ancientWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
dust2C4014–2635%-0.01
nukeC145–936%-0.00
mirageA116–555%0.00
trainA117–464%0.02
vertigoD103–730%-0.04
ancientD81–713%-0.02
overpass—20–20%-0.01
inferno—22–0100%0.04
cache—10–10%-0.14
dogtown—10–10%-0.04

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Ancient 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.

12.7%Headshot accuracy
29.8%Accuracy (enemy spotted)
37.7%Spray accuracy
64.3%Counter-strafing
14.3°Preaim
647msReaction time
20.9%T opening success
49.1%CT opening success
0.78Enemies flashed / flash
4.5%Flash assists
7.00HE damage / grenade
6.86Flashes / 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 14.3152° — above the 12° mark we flag

    Aim Training →
  2. 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 12.7145% — below the 15% mark we flag

    Aim Training →
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.

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

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo6–13-0.0610%23 Sept →
nuke5–130.0512%23 Sept →
dust23–13-0.0916%23 Sept →
dust27–130.1120%31 Aug →
nuke6–13-0.0511%28 May →
dust23–13-0.0411%28 May →
dust29–130.0111%14 May →
cache4–13-0.149%29 Apr →
mirage11–13-0.0115%17 Apr →
dust213–70.0916%17 Apr →
nuke13–110.007%16 Apr →
dust213–100.0723%16 Apr →
dust26–13-0.0617%12 Apr →
dust29–130.0317%15 Mar →
mirage13–11-0.0211%15 Mar →
overpass1–130.038%15 Mar →
mirage8–130.0118%8 Mar →
dust213–110.046%8 Mar →
nuke12–12-0.0111%8 Mar →
dust28–130.0110%30 Nov →
vertigo1–13-0.080%25 Oct →
dust26–13-0.0510%25 Oct →
dust29–13-0.0615%21 Oct →
dust28–13-0.0212%21 Oct →
overpass7–9-0.0517%14 Sept →
dogtown8–8-0.040%14 Sept →
inferno9–40.0324%14 Sept →
dust212–120.0011%11 Sept →
ancient2–13-0.0022%10 Sept →
dust24–13-0.0710%10 Sept →
nuke7–13-0.007%7 Sept →
dust213–9-0.0014%7 Sept →
ancient2–8-0.0613%2 Sept →
vertigo3–13-0.068%2 Sept →
dust210–13-0.0415%2 Sept →
mirage10–10-0.036%31 Aug →
ancient12–12-0.029%31 Aug →
dust213–50.018%31 Aug →
nuke13–90.0114%28 Aug →
dust210–13-0.0412%28 Aug →
dust23–130.0011%28 Aug →
dust213–9-0.1210%24 Aug →
nuke10–13-0.0913%17 Aug →
dust25–130.0413%17 Aug →
dust26–130.0110%10 Aug →
dust28–130.0011%10 Aug →
nuke0–13-0.0510%10 Aug →
dust26–13-0.038%10 Aug →
dust24–13-0.0619%13 Jul →
dust21–13-0.0827%13 Jul →
nuke2–13-0.066%1 Jun →
dust23–13-0.0532%1 Jun →
dust21–1-0.180%1 Jun →
dust213–40.0815%2 Mar →
dust213–7-0.0511%23 Feb →
train13–10.068%16 Feb →
mirage13–5-0.0226%26 Jan →
nuke13–80.0810%26 Jan →
dust27–13-0.0014%26 Jan →
vertigo7–9-0.1610%26 Jan →
dust213–11-0.0315%20 Jan →
train11–130.0511%20 Jan →
vertigo13–11-0.0111%15 Jan →
train13–50.0813%15 Jan →
vertigo13–100.037%12 Jan →
nuke5–13-0.027%15 Dec →
ancient12–16-0.028%15 Dec →
nuke13–00.1612%15 Dec →
mirage13–40.0811%15 Dec →
ancient12–120.026%13 Dec →
nuke12–120.0217%13 Dec →
dust23–13-0.016%13 Dec →
ancient10–130.0212%11 Dec →
dust216–120.0216%11 Dec →
nuke13–5-0.0512%7 Dec →
train13–3-0.0113%7 Dec →
vertigo7–13-0.069%7 Dec →
train13–50.0310%1 Dec →
mirage12–120.007%1 Dec →
vertigo10–130.036%27 Nov →
mirage7–130.0624%27 Nov →
train13–20.0111%26 Nov →
dust213–90.058%26 Nov →
vertigo9–13-0.008%26 Nov →
dust213–50.0718%22 Nov →
train13–110.0610%22 Nov →
train13–60.0114%19 Nov →
ancient7–13-0.0612%19 Nov →
train2–130.0212%19 Nov →
train8–13-0.0611%17 Nov →
train9–13-0.0311%17 Nov →
mirage5–13-0.0415%13 Nov →
mirage13–90.0211%13 Nov →
dust21–13-0.129%13 Nov →
ancient13–4-0.038%6 Nov →
inferno13–50.048%6 Nov →
dust27–130.0211%6 Nov →
vertigo13–10-0.059%5 Nov →
dust213–80.025%5 Nov →
mirage13–20.0020%5 Nov →

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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