mr dracula

mr dracula — CS2 Stats

KZ76561198001857405[U:1:41591677]Steam profile ↗✓ No bans

1,135Tracked matches48%Win rate2020Tracked since
CSDB Rating5.2 DevelopingPositional Player
Ladder ranks via Leetify
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 49 days played since 25 Jan 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 15,890 -4,224 15 Apr4 Jul · 31 days played
15,89020,951peak 20,95115 Apr4 Jul
21,061Peak Premier in tracked matches
49Days played since 2026-01-25

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

Performance scores

Aim60
Positioning58
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY40573Last 10040%Win rateLLWWWTWLWW

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating · −0.0pp headshot accuracy · −77ms reaction

Win rate up 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

  • 32 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 22%
  • Avg reaction 484ms

Last 10

  • 631 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 16%
  • Avg reaction 563ms

Last 20

  • 9101 · 45% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 601ms

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 PlayerPositioning stands above the rest of this profile (+0.9 against its own average).

Aim6.0
Utility5.1
Positioning5.8
Opening Duels3.7

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

jL

Plays most like jL 83% 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

T-side openings. Opening success drops from 51% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 568ms 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

Aim6.0
Positioning5.8
Utility5.1
Mechanics5.0
Opening Duels3.2
Win Impact4.4

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 rating-0.02−0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time583ms+32ms
first ⅓ avg 551ms → last ⅓ avg 583ms
Headshot accuracy15.9%−0.6%
first ⅓ avg 16.4% → last ⅓ avg 15.9%

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

0.19Best match rating · 6–1 · ancient, 16 Jun
43%Best headshot accuracy · 1–13 · office, 26 Apr
398msFastest reaction time · 8–13 · ancient, 30 Apr
13–1Biggest win · dust2, 16 Apr

Across the last 100 tracked matches.

Highlights

7Longest win streak
L2Current streak
811In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 54% over 13ancientWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
nukeB2091145%-0.02
dust2D1961332%-0.04
anubisC1871139%-0.02
infernoB137654%-0.03
mirageC125742%-0.02
ancientD92722%-0.03
cache43175%-0.03
overpass41325%-0.01
office1010%-0.10

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6Matches
50%Win rate
0.91Avg K/D
ADR
38%Headshot %

Clutches & streaks

1v1 clutch win
1v2 clutch win
2Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Ancient333%0.8716.0
Anubis10%0.335.0
Nuke1100%1.1011.0
Inferno1100%1.4124.0

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.

17.0%Headshot accuracy
34.3%Accuracy (enemy spotted)
34.6%Spray accuracy
72.6%Counter-strafing
10.5°Preaim
568msReaction time
34.2%T opening success
51.3%CT opening success
0.62Enemies flashed / flash
1.8%Flash assists
8.98HE damage / grenade
5.86Flashes / 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

    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 34.1864% — below the 40% mark we flag

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.

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

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
dust25–13-0.0521%19 Sept
dust210–13-0.0222%16 Sept
nuke13–40.0521%16 Sept
cache13–11-0.0111%16 Sept
anubis13–60.0037%16 Sept
anubis15–15-0.0116%9 Sept
nuke13–6-0.0311%8 Sept
anubis3–7-0.078%2 Sept
inferno13–8-0.057%1 Sept
nuke13–5-0.079%1 Sept
dust27–13-0.0533%10 Jul
nuke5–13-0.039%4 Jul
dust20–4-0.070%2 Jul
mirage6–13-0.0528%2 Jul
overpass14–16-0.0116%30 Jun
anubis7–3-0.094%30 Jun
ancient5–13-0.0418%26 Jun
mirage13–5-0.0220%23 Jun
mirage13–10-0.0314%23 Jun
ancient3–13-0.0722%22 Jun
nuke5–130.0330%22 Jun
anubis13–40.0621%20 Jun
ancient10–13-0.0613%19 Jun
dust213–9-0.029%19 Jun
nuke13–4-0.0619%18 Jun
inferno3–13-0.056%18 Jun
nuke8–13-0.0111%16 Jun
ancient6–10.1926%16 Jun
inferno13–30.0117%16 Jun
mirage2–13-0.0021%9 Jun
nuke11–13-0.0611%4 Jun
dust211–13-0.106%4 Jun
overpass13–11-0.017%31 May
dust26–13-0.0415%29 May
nuke13–11-0.0412%28 May
dust211–130.0016%27 May
ancient11–13-0.0119%27 May
dust213–9-0.0317%26 May
ancient13–9-0.0519%26 May
anubis13–20.1014%23 May
nuke13–8-0.0525%14 May
anubis13–110.0012%13 May
dust213–100.0119%13 May
mirage2–13-0.048%13 May
inferno13–10-0.0016%12 May
anubis4–13-0.0612%12 May
dust29–13-0.0718%12 May
dust211–13-0.0315%12 May
anubis11–13-0.055%9 May
inferno6–13-0.0121%9 May
dust26–13-0.0517%8 May
anubis13–50.0519%8 May
mirage7–130.0326%8 May
nuke10–13-0.0818%3 May
overpass11–13-0.0312%3 May
anubis3–13-0.0715%30 Apr
cache13–9-0.030%30 Apr
cache8–13-0.0413%30 Apr
mirage11–130.0012%30 Apr
ancient8–13-0.070%30 Apr
ancient5–13-0.0416%29 Apr
cache13–2-0.0533%29 Apr
office1–13-0.1043%26 Apr
mirage13–16-0.0534%26 Apr
nuke12–16-0.0430%26 Apr
nuke3–130.038%26 Apr
anubis2–13-0.118%25 Apr
nuke12–16-0.0417%25 Apr
inferno9–13-0.0626%25 Apr
overpass11–130.0019%25 Apr
dust215–15-0.057%25 Apr
inferno3–13-0.0615%25 Apr
anubis4–13-0.0216%21 Apr
mirage13–10-0.0122%21 Apr
dust29–13-0.0713%21 Apr
dust213–10.0419%16 Apr
inferno13–7-0.018%15 Apr
nuke13–50.0916%15 Apr
nuke13–8-0.0222%15 Apr
dust213–100.0121%15 Apr
inferno16–14-0.075%15 Apr
dust213–11-0.0721%15 Apr
ancient6–13-0.0714%13 Apr
anubis6–130.0531%12 Apr
mirage3–13-0.0426%25 Mar
dust28–13-0.0524%25 Mar
inferno8–13-0.0316%19 Mar
nuke12–16-0.059%14 Mar
inferno13–11-0.035%14 Mar
anubis14–16-0.0526%24 Feb
anubis10–130.0417%23 Feb
inferno8–13-0.020%22 Feb
inferno13–11-0.0518%2 Feb
nuke13–8-0.043%2 Feb
anubis15–15-0.0132%2 Feb
nuke8–13-0.0119%26 Jan
mirage13–9-0.049%26 Jan
nuke9–130.0114%25 Jan
anubis13–6-0.0513%25 Jan
mirage13–50.0219%25 Jan

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 →