Dutchy

Dutchy — CS2 Stats

GB76561198204052613[U:1:243786885]Steam profile ↗✓ No bans

2,508Tracked matches30%Win rate2020Tracked since
12,489Hours in CS27Hrs last 2 wks
CSDB Rating5.2 DevelopingPositional Player
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Sep 2026 (19 days ago). Ranks are recorded once per day this page is viewed.

+6Tracked matches · now 2,508
0.0ppWin rate · 30.0% → 30.0%

Rating over time

66Days played since 2024-01-18

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches18——
Win rate56%——
K/D0.20——
Headshot %49%——

Measured 7 Sep 2026 → 8 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

Performance scores

Aim77
Positioning50
Utility42

0–100 skill scores via Leetify.

Recent form

STEADY54–46Last 10054%Win rateWLWLWWLLLL

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · −8.4pp headshot accuracy · −27ms reaction

Win rate +10pp 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

  • 3–2 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 577ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 16%
  • Avg reaction 592ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 20%
  • Avg reaction 606ms

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 (+1.7 against its own average).

Aim7.7
Utility4.2
Positioning5.0
Opening Duels1.0
Clutch3.0

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

sh1ro

Plays most like sh1ro 89% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; 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

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

Reaction time. 606ms 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

Aim7.7
Positioning5.0
Utility4.2
Mechanics8.0
Opening Duels0.6
Win Impact0.0

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 rating0.00−0.00
first ⅓ avg 0.00 → last ⅓ avg 0.00
Reaction time608ms+80ms
first ⅓ avg 528ms → last ⅓ avg 608ms
Headshot accuracy18.4%−2.0%
first ⅓ avg 20.5% → last ⅓ avg 18.4%

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 · 13–2 · nuke, 28 Nov →
44%Best headshot accuracy · 9–4 · inferno, 9 Oct →
266msFastest reaction time · 13–0 · nuke, 15 Dec →
13–0Biggest win · nuke, 15 Dec →

Across the last 100 tracked matches.

Highlights

14Longest win streak
7–8In matches decided by ≤2 rounds
10Overtime games

Map breakdown

anubisBest map · 78% over 9trainWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
ancientA2213–959%0.01
nukeC208–1240%-0.01
overpassS118–373%0.01
mirageA106–460%-0.01
infernoB105–550%0.01
anubisS97–278%0.01
trainC83–538%0.01
vertigo—31–233%-0.03
office—22–0100%0.04
dust2—20–20%0.08
cache—10–10%-0.01
palacio—10–10%0.12
thera—11–0100%0.15

Across the last 100 tracked matches.

Lifetime stats

278,864Lifetime kills
0.97K/D
9,581Matches
49.3%Match win rate · Top 25% of tracked players
51.6%Headshot % · Top 25% of tracked players
19.8%Shot accuracy · Top 5% of tracked players
29,306MVPs
11,871Hours (in match)
15,030Bombs planted
3,692Bombs defused

Most-used weapons

AK-47108,366
AWP19,832
SG 5538,876
AUG6,257
Knife5,691
P2505,072

Lifetime map wins

19,652inferno
13,433nuke
12,528dust2
9,005vertigo
7,505train
1,122cbble
116lake
106office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

4,337Matches
54%Win rate
1.13Avg K/D
72.2ADR
47%Headshot %

Clutches & streaks

35%1v1 clutch win
19%1v2 clutch win
11Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient23858%1.0614.7
Anubis14555%1.1015.3
Nuke12858%1.1514.4
Mirage11848%0.9414.1
Inferno6757%1.0813.6
Overpass5467%1.2515.8
Train4159%1.1113.8
Vertigo2763%1.2716.5

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.

16.8%Headshot accuracy
39.0%Accuracy (enemy spotted)
43.5%Spray accuracy
86.1%Counter-strafing
11.4°Preaim
606msReaction time
24.4%T opening success
34.4%CT opening success
0.55Enemies flashed / flash
7.9%Flash assists
9.56HE damage / grenade
13.55Flashes / 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 24.4% — below the 40% mark we flag

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.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
office13–60.0725%18 Sept →
cache11–13-0.0125%20 May →
nuke13–100.0112%20 May →
mirage13–16-0.068%11 May →
nuke13–6-0.0510%19 Mar →
overpass13–30.0414%19 Mar →
nuke14–160.0210%18 Mar →
dust210–130.1519%17 Jan →
overpass9–13-0.0630%20 Nov →
nuke6–130.048%20 Nov →
overpass13–110.1014%13 Nov →
nuke4–13-0.0517%25 Oct →
palacio9–130.1221%21 Oct →
train13–30.1131%21 Oct →
inferno9–40.1244%9 Oct →
ancient1–13-0.0621%30 Sept →
train2–13-0.0640%30 Sept →
overpass5–13-0.0128%29 Sept →
mirage8–13-0.0524%29 Sept →
inferno5–130.026%27 Sept →
mirage5–13-0.0625%17 Sept →
nuke6–130.0216%17 Sept →
inferno16–120.0217%13 Sept →
overpass13–10-0.0120%13 Sept →
nuke8–13-0.0515%26 Aug →
inferno15–19-0.046%26 Aug →
inferno7–13-0.0510%13 Aug →
nuke13–11-0.0316%13 Aug →
overpass7–13-0.0219%13 Aug →
nuke10–13-0.0510%19 Jul →
inferno11–13-0.0111%19 Jul →
ancient11–130.0018%19 Jul →
nuke2–13-0.0118%19 Jul →
ancient13–10.1226%18 Jul →
nuke13–4-0.0112%18 Jul →
ancient13–6-0.0329%14 Jul →
inferno13–90.0216%13 Jul →
anubis13–4-0.0321%2 Jul →
ancient13–30.0239%2 Jul →
mirage13–80.0123%12 Jun →
dust25–130.0228%30 May →
mirage13–70.0624%30 May →
train3–13-0.0629%30 May →
inferno6–13-0.0418%29 May →
train1–13-0.0323%29 May →
train7–13-0.0314%26 May →
mirage13–60.0227%26 May →
anubis13–30.0512%26 May →
ancient9–130.0317%14 May →
train17–190.0219%14 May →
inferno19–17-0.038%13 May →
ancient13–60.0113%13 May →
mirage13–10-0.0316%11 May →
ancient13–9-0.0321%27 Feb →
anubis13–30.1236%9 Feb →
anubis13–3-0.0027%24 Jan →
anubis22–20-0.0232%10 Jan →
ancient13–50.0624%20 Dec →
office13–50.0233%19 Dec →
train13–50.0713%19 Dec →
overpass13–80.0323%19 Dec →
nuke13–00.0222%15 Dec →
nuke13–20.1618%28 Nov →
train13–90.0626%21 Nov →
anubis5–13-0.0711%15 Nov →
mirage13–30.0424%12 Nov →
anubis4–13-0.0912%20 Oct →
ancient11–13-0.0214%15 Oct →
nuke3–12-0.0618%11 Oct →
ancient13–100.0217%11 Oct →
nuke4–13-0.0324%7 Oct →
nuke5–13-0.0518%6 Oct →
nuke14–160.0118%17 Sept →
inferno13–70.0631%21 Aug →
ancient5–13-0.1022%7 Jul →
thera13–60.1528%5 Jul →
ancient19–160.0118%30 Apr →
overpass13–11-0.0122%7 Apr →
ancient13–40.0640%6 Apr →
anubis13–50.0631%6 Apr →
mirage16–120.0428%6 Apr →
overpass13–9-0.0013%4 Apr →
ancient13–110.0816%4 Apr →
vertigo9–13-0.1310%6 Mar →
nuke13–6-0.0410%6 Mar →
nuke10–13-0.0419%29 Feb →
ancient12–80.1013%28 Feb →
overpass13–6-0.0117%28 Feb →
overpass13–90.0323%28 Feb →
ancient8–13-0.0418%26 Feb →
vertigo9–130.0224%25 Feb →
vertigo13–70.0325%21 Feb →
ancient13–110.0031%21 Feb →
mirage8–13-0.0613%20 Feb →
ancient11–13-0.0638%16 Feb →
ancient2–130.000%25 Jan →
ancient13–20.0217%23 Jan →
ancient2–13-0.0417%21 Jan →
nuke13–80.0324%18 Jan →
anubis13–30.0818%18 Jan →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches14-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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