MercDoe

MercDoe — CS2 Stats

76561198190585446[U:1:230319718]Steam profile ↗✓ No bans

190Tracked matches43%Win rate2021Tracked since
689Hours in CS
CSDB Rating2.9 LearningSupport
WingmanSilver III
Ladder ranks via Leetify

Performance scores

Aim39
Positioning32
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY45–49–6Last 10045%Win rateWLLWLWLLLW

Last 10 vs previous 10: +10pp win rate · −0.03 avg rating · −0.7pp headshot accuracy · −28ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 16%
  • Avg reaction 627ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 16%
  • Avg reaction 652ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 666ms

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: Support — Utility contribution stands above the rest of this profile (+1.3 against its own average).

Aim3.9
Utility3.6
Positioning3.2
Opening Duels0.1

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

ZywOo

Plays most like ZywOo 84% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 681ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 59% 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

Aim3.9
Positioning3.2
Utility3.6
Mechanics2.1
Opening Duels0.2
Win Impact2.6

Composite 2.9/10 (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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time688ms+18ms
first ⅓ avg 670ms → last ⅓ avg 688ms
Headshot accuracy16.9%+1.9%
first ⅓ avg 15.0% → last ⅓ avg 16.9%

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

0.26Best match rating · 9–2 · rooftop, 26 Oct →
38%Best headshot accuracy · 9–2 · rooftop, 26 Oct →
422msFastest reaction time · 13–9 · nuke, 11 Jan →
13–1Biggest win · nuke, 11 May →

Across the last 100 tracked matches.

Highlights

6Longest win streak
7–9In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 67% over 12infernoWeakest map · 28% over 18
MapGradePlayedRecordWin rateAvg rating
infernoD185–1328%-0.01
ancientB168–850%-0.03
mirageB147–750%-0.02
nukeS128–467%-0.02
dust2D124–833%-0.03
trainC83–538%-0.02
officeC73–443%-0.04
overpass—42–250%-0.01
anubis—44–0100%-0.02
cache—20–20%-0.05
vertigo—20–20%0.01
rooftop—11–0100%0.26

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (28% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

41,066Lifetime kills
0.99K/D
2,726Matches
40.6%Match win rate
48.3%Headshot % · Top 50% of tracked players
17.6%Shot accuracy · Top 25% of tracked players
7,156MVPs
689Hours (in match)
1,915Bombs planted
383Bombs defused

Most-used weapons

AK-477,926
AWP2,432
AUG1,685
MP71,455
SG 5531,351

Lifetime map wins

3,382inferno
1,726vertigo
1,210dust2
1,107nuke
887train
623cbble
513office
321lake

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

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
34.9%Accuracy (enemy spotted)
34.1%Spray accuracy
59.5%Counter-strafing
10.6°Preaim
681msReaction time
26.3%T opening success
31.4%CT opening success
0.58Enemies flashed / flash
4.1%Flash assists
6.13HE damage / grenade
5.94Flashes / 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 26.2862% — below the 40% mark we flag

Spend your practice time on Inferno

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

28% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–7-0.0611%15 Aug →
inferno11–13-0.0715%14 Aug →
train11–13-0.0220%14 Aug →
ancient13–7-0.0517%11 Aug →
cache13–16-0.0718%27 Jul →
ancient13–30.0111%27 Jul →
inferno11–13-0.069%27 Jul →
mirage9–13-0.0410%21 Jul →
ancient2–13-0.0435%27 Jun →
ancient16–14-0.0718%28 May →
ancient11–13-0.0322%11 May →
nuke13–1-0.0617%11 May →
cache10–13-0.0311%5 May →
inferno10–13-0.039%30 Apr →
train11–13-0.0113%28 Apr →
inferno13–20.1422%28 Apr →
mirage2–13-0.0414%5 Apr →
inferno12–12-0.0323%5 Apr →
dust29–13-0.0315%5 Apr →
overpass13–7-0.0125%5 Apr →
mirage13–11-0.0523%5 Apr →
mirage7–13-0.0025%4 Apr →
dust29–13-0.0618%3 Apr →
nuke13–11-0.0220%31 Mar →
mirage13–20.0919%31 Mar →
overpass13–5-0.0410%2 Mar →
inferno12–12-0.0615%26 Jan →
anubis6–5-0.049%26 Jan →
office4–13-0.0513%26 Jan →
inferno6–13-0.0419%26 Jan →
overpass5–130.0615%26 Jan →
mirage13–50.0426%26 Jan →
nuke13–3-0.0514%26 Jan →
office13–8-0.0413%29 Nov →
office12–12-0.044%29 Nov →
rooftop9–20.2638%26 Oct →
office13–9-0.0633%26 Oct →
dust27–13-0.0518%25 Oct →
vertigo6–130.0116%25 Oct →
office6–13-0.0438%25 Oct →
ancient1–13-0.0721%25 Oct →
vertigo6–130.0115%27 Aug →
inferno3–13-0.0110%27 Aug →
nuke7–13-0.0320%21 Apr →
inferno11–13-0.0225%20 Apr →
ancient13–8-0.0113%20 Apr →
office7–130.0111%19 Apr →
mirage6–13-0.0117%19 Apr →
dust26–2-0.0317%19 Apr →
nuke13–70.089%19 Apr →
ancient2–13-0.0714%18 Apr →
inferno5–13-0.0315%18 Apr →
dust29–130.0518%18 Apr →
ancient13–60.0815%1 Apr →
ancient6–13-0.0510%16 Feb →
nuke10–13-0.0417%16 Feb →
nuke13–6-0.0127%8 Feb →
inferno13–3-0.0211%3 Feb →
train9–13-0.057%3 Feb →
dust213–10-0.0117%3 Feb →
ancient1–13-0.0412%2 Feb →
mirage13–70.0412%2 Feb →
dust212–12-0.0711%2 Feb →
dust213–100.0220%1 Feb →
train5–13-0.059%1 Feb →
mirage3–13-0.115%1 Feb →
anubis13–11-0.049%31 Jan →
inferno12–12-0.0411%28 Jan →
dust213–7-0.0818%26 Jan →
mirage13–7-0.0121%26 Jan →
train13–110.0413%23 Jan →
mirage11–0-0.0114%23 Jan →
dust29–13-0.0222%23 Jan →
mirage13–10-0.0520%23 Jan →
nuke13–20.0619%23 Jan →
anubis13–50.0119%17 Jan →
train13–9-0.048%16 Jan →
ancient2–11-0.0533%15 Jan →
train13–4-0.049%12 Jan →
anubis13–3-0.0116%12 Jan →
inferno13–80.0416%12 Jan →
nuke13–9-0.0611%11 Jan →
ancient6–30.020%11 Jan →
ancient13–5-0.0211%9 Jan →
ancient11–13-0.0315%8 Jan →
inferno13–110.0417%7 Jan →
dust211–13-0.0111%5 Jan →
mirage11–13-0.056%5 Jan →
inferno13–6-0.0315%4 Jan →
nuke3–13-0.0614%2 Jan →
inferno8–130.0213%1 Jan →
mirage7–13-0.0618%1 Jan →
train12–120.0317%25 Dec →
overpass8–13-0.0521%24 Dec →
inferno8–13-0.084%14 Dec →
dust29–13-0.0717%6 Dec →
office13–8-0.078%1 Dec →
nuke10–130.0425%1 Dec →
ancient13–8-0.0221%1 Dec →
inferno9–130.0112%1 Dec →

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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