dry water

dry water — CS2 Stats

76561198167358745[U:1:207093017]Steam profile ↗✓ No bans

1,612Tracked matches50%Win rate2020Tracked since
CSDB Rating5.8 SolidPositional Player
CSDB Leaderboard#53150 of 251469 tracked
FaceitLevel 6Top 54.0% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 22,080 +62 21 Aug – 8 Oct · 18 days played
21,64323,750peak 23,75021 Aug8 Oct
23,750Peak Premier in tracked matches
32Days played since 2025-08-21

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

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CSDB.GGdry waterFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

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Performance scores

Aim63
Positioning63
Utility40

0–100 skill scores via Leetify.

Recent form

STEADY49–42–9Last 10049%Win rateWTWLLWLWLL

Last 10 vs previous 10: 0pp win rate · −0.04 avg rating · +7.4pp headshot accuracy · −7ms reaction

Win rate 0pp 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 563ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 15%
  • Avg reaction 599ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 12%
  • Avg reaction 602ms

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 (+2.1 against its own average).

Aim6.3
Utility4.0
Positioning6.3
Opening Duels3.7
Clutch3.0

Strong CT-side opener

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 89% 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

Areas to improve

Reaction time. 629ms 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

Aim6.3
Positioning6.3
Utility4.0
Mechanics7.0
Opening Duels5.4
Win Impact5.0

Composite 5.8/10 (Solid), 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 rating0.02−0.01
first ⅓ avg 0.03 → last ⅓ avg 0.02
Reaction time624ms+11ms
first ⅓ avg 612ms → last ⅓ avg 624ms
Headshot accuracy12.3%+2.8%
first ⅓ avg 9.5% → last ⅓ avg 12.3%

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

0.14Best match rating · 13–5 · overpass, 6 Sept →
24%Best headshot accuracy · 13–1 · cache, 12 Oct →
422msFastest reaction time · 13–4 · inferno, 13 Oct →
13–0Biggest win · ancient, 12 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
10–8In matches decided by ≤2 rounds
15Overtime games

Map breakdown

overpassBest map · 55% over 11trainWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
dust2B2915–1452%0.02
infernoB168–850%0.02
ancientB126–650%0.04
overpassA116–555%0.03
mirageC94–544%0.00
trainD93–633%0.04
nukeC83–538%0.02
cache—43–175%0.07
anubis—21–150%0.02

Across the last 100 tracked matches.

Faceit stats

Combat

104Matches
58%Win rate
1.22Avg K/D
100.0ADR
34%Headshot %

Clutches & streaks

35%1v1 clutch win
17%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage2250%1.0316.1
Anubis2060%1.1316.8
Ancient1267%1.1915.8
Inferno1242%1.1316.5
Vertigo1050%1.0015.8
Nuke956%1.1718.4
Dust25100%2.1220.6
Overpass367%1.5422.3

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.

12.0%Headshot accuracy
38.9%Accuracy (enemy spotted)
42.6%Spray accuracy
81.3%Counter-strafing
12.2°Preaim
629msReaction time
48.6%T opening success
54.2%CT opening success
0.56Enemies flashed / flash
6.9%Flash assists
7.42HE damage / grenade
8.68Flashes / 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 12.221° — 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 11.9962% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Train

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

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage13–11-0.0310%13 Oct →
ancient15–150.0510%13 Oct →
inferno13–40.0518%13 Oct →
dust25–13-0.0512%12 Oct →
dust22–13-0.0816%12 Oct →
ancient13–00.0617%12 Oct →
mirage5–130.0219%12 Oct →
cache13–10.0524%12 Oct →
inferno2–13-0.0718%12 Oct →
nuke13–16-0.0111%11 Oct →
dust213–40.096%11 Oct →
cache16–120.087%11 Oct →
dust213–11-0.0313%11 Oct →
dust25–13-0.034%11 Oct →
cache13–90.108%11 Oct →
anubis15–150.025%10 Oct →
dust25–130.0111%10 Oct →
dust213–160.012%9 Oct →
cache11–130.0716%9 Oct →
inferno4–130.0311%9 Oct →
ancient8–13-0.0511%8 Oct →
dust213–70.0815%8 Oct →
dust213–5-0.0223%8 Oct →
dust211–130.0913%8 Oct →
mirage4–13-0.0515%8 Oct →
train14–16-0.0112%7 Oct →
dust216–140.0216%7 Oct →
ancient13–100.0714%6 Oct →
mirage13–4-0.0010%6 Oct →
nuke16–140.0513%6 Oct →
ancient10–130.0310%6 Oct →
dust213–90.0310%6 Oct →
dust29–13-0.019%6 Oct →
overpass11–130.018%5 Oct →
dust213–110.094%5 Oct →
dust25–13-0.0122%5 Oct →
ancient6–130.0511%5 Oct →
dust213–80.1012%5 Oct →
train16–120.0720%5 Oct →
mirage8–130.0318%5 Oct →
dust210–130.0312%4 Oct →
inferno13–60.0214%4 Oct →
dust29–13-0.0313%4 Oct →
dust213–8-0.0211%4 Oct →
ancient11–130.109%4 Oct →
train11–130.0510%3 Oct →
ancient2–13-0.0015%3 Oct →
inferno16–140.019%2 Oct →
nuke15–150.0118%2 Oct →
dust210–130.008%2 Oct →
overpass13–50.0112%2 Oct →
inferno4–13-0.0621%2 Oct →
dust216–13-0.0118%1 Oct →
inferno13–20.1213%1 Oct →
dust213–70.0715%1 Oct →
overpass13–8-0.0210%30 Sept →
inferno13–6-0.007%30 Sept →
inferno5–13-0.077%30 Sept →
dust28–13-0.0320%27 Sept →
dust215–150.0313%27 Sept →
overpass16–14-0.0412%21 Sept →
nuke12–160.0013%21 Sept →
ancient13–70.0418%18 Sept →
nuke11–130.1111%17 Sept →
overpass13–20.087%17 Sept →
inferno13–40.1110%16 Sept →
mirage5–130.0618%16 Sept →
overpass13–110.0910%15 Sept →
nuke13–5-0.008%11 Sept →
anubis13–60.026%11 Sept →
dust213–4-0.0213%11 Sept →
nuke11–13-0.0017%11 Sept →
inferno12–120.046%11 Sept →
train13–100.1314%11 Sept →
dust213–80.099%10 Sept →
train10–130.0413%10 Sept →
inferno8–130.107%10 Sept →
inferno13–100.035%10 Sept →
dust213–40.0716%10 Sept →
dust212–120.017%10 Sept →
train12–120.0510%10 Sept →
overpass12–120.097%7 Sept →
mirage13–70.0713%7 Sept →
overpass13–50.140%6 Sept →
ancient13–70.0313%6 Sept →
nuke13–100.010%4 Sept →
overpass12–120.014%3 Sept →
mirage8–13-0.0915%3 Sept →
mirage13–110.036%2 Sept →
train13–90.068%29 Aug →
ancient13–11-0.0711%29 Aug →
dust213–50.0115%29 Aug →
overpass6–13-0.039%29 Aug →
inferno4–13-0.0310%29 Aug →
train9–130.019%27 Aug →
overpass2–13-0.0316%25 Aug →
ancient13–90.097%23 Aug →
train10–13-0.046%21 Aug →
inferno8–13-0.0111%21 Aug →
inferno13–60.0914%21 Aug →

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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