DDNC

DDNC — CS2 Stats

76561198169294373[U:1:209028645]Steam profile ↗

179Tracked matches67%Win rate2020Tracked since
CSDB Rating5.5 Solid
Premier CS Rating19,178Purple band · top ~11.8% of ranked players (population est.)
CSDB Leaderboard#18403 of 41641 tracked
Ladder ranks via Leetify

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CSDB.GGDDNCPREMIER19,178 · Purple bandcsdb.gg/stats

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Performance scores

Aim58
Positioning43
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY57376Last 10057%Win rateWLWLWWWTLW

Last 10 vs previous 10: +10pp win rate · +0.00 avg rating

Player DNA

Aim5.8
Aggression5.7
Utility4.6
Positioning4.3
Opening Duels2.8

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 85% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower positioning profile; 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 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 669ms 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

Aim5.8
Positioning4.3
Utility4.6
Mechanics5.9
Opening Duels2.8
Win Impact10.0

Composite 5.5/10 (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 rating0.00−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.00
Reaction time668ms+29ms
first ⅓ avg 639ms → last ⅓ avg 668ms
Headshot accuracy16.4%−0.4%
first ⅓ avg 16.9% → last ⅓ avg 16.4%

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.

Highlights

0.17Best rating — anubis 13–2
132Biggest win — anubis
6Longest win streak
52In matches decided by ≤2 rounds
6Overtime games

Map breakdown

ancientBest map · 70% over 10infernoWeakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
nukeA2012860%0.00
dust2C1881044%0.01
mirageB147750%0.01
infernoC135838%0.01
overpassS139469%0.01
ancientS107370%0.01
cacheS64267%0.02
anubis43175%0.03
train220100%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Inferno 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.

16.9%Headshot accuracy
35.9%Accuracy (enemy spotted)
36.9%Spray accuracy
76.4%Counter-strafing
10.6°Preaim
669msReaction time
31.4%T opening success
50.7%CT opening success
0.50Enemies flashed / flash
4.3%Flash assists
7.59HE damage / grenade
7.91Flashes / 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 31.3649% — 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.

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
cache13–11-0.0132%5 May
cache5–13-0.0220%1 May
mirage13–90.0215%1 May
dust28–13-0.0123%1 May
cache13–90.0411%30 Apr
cache13–90.0417%29 Apr
cache13–110.0411%29 Apr
cache12–120.0628%29 Apr
mirage3–13-0.055%28 Apr
inferno13–60.0523%28 Apr
ancient13–90.0117%27 Apr
overpass11–130.0819%27 Apr
overpass13–100.0118%26 Apr
mirage9–130.0119%26 Apr
nuke4–13-0.0724%25 Apr
overpass13–80.0316%25 Apr
ancient13–4-0.0413%25 Apr
dust212–120.0212%24 Apr
mirage13–50.0332%24 Apr
inferno8–130.0319%24 Apr
train13–10-0.0512%22 Apr
ancient13–8-0.038%22 Apr
dust213–50.0117%20 Apr
inferno13–60.0514%20 Apr
nuke13–7-0.0416%20 Apr
mirage12–12-0.0416%20 Apr
nuke13–80.0115%19 Apr
dust213–10-0.0313%19 Apr
nuke4–13-0.0310%19 Apr
anubis5–13-0.0110%19 Apr
dust213–8-0.0015%19 Apr
inferno7–130.017%19 Apr
ancient13–8-0.0117%19 Apr
dust26–130.0421%18 Apr
mirage5–13-0.059%17 Apr
nuke13–7-0.0117%17 Apr
anubis13–5-0.0212%15 Apr
inferno4–130.0330%15 Apr
anubis13–20.1717%15 Apr
nuke10–130.0614%15 Apr
overpass13–90.0615%14 Apr
nuke10–13-0.007%13 Apr
ancient9–13-0.0514%10 Apr
mirage9–13-0.0022%9 Apr
inferno9–13-0.0311%9 Apr
nuke13–10-0.0313%8 Apr
dust213–8-0.0113%7 Apr
overpass12–30.002%7 Apr
inferno13–70.0521%4 Apr
dust215–15-0.0121%4 Apr
ancient16–130.1017%4 Apr
nuke9–13-0.0222%3 Apr
mirage13–110.0820%3 Apr
overpass13–9-0.0318%3 Apr
ancient13–160.0016%2 Apr
dust26–13-0.0510%1 Apr
ancient13–9-0.0412%30 Mar
mirage9–130.0416%30 Mar
nuke15–150.0414%24 Mar
dust29–13-0.066%24 Mar
inferno13–80.0321%24 Mar
mirage13–50.1013%23 Mar
nuke13–6-0.0610%23 Mar
dust26–13-0.0525%23 Mar
dust213–40.1020%20 Mar
ancient13–40.1724%20 Mar
mirage4–13-0.0117%20 Mar
overpass13–60.0724%19 Mar
overpass13–70.0521%19 Mar
dust213–40.1020%19 Mar
nuke13–2-0.0522%19 Mar
anubis13–11-0.0219%19 Mar
overpass13–100.0311%19 Mar
ancient5–130.0312%18 Mar
mirage13–70.0114%18 Mar
overpass9–130.029%18 Mar
mirage13–70.0914%18 Mar
inferno5–13-0.035%17 Mar
nuke13–6-0.0216%17 Mar
nuke13–80.0327%17 Mar
nuke15–150.0123%17 Mar
nuke8–13-0.0318%17 Mar
dust26–130.0518%17 Mar
dust213–70.0412%16 Mar
dust213–70.0719%13 Mar
inferno10–130.0819%13 Mar
nuke13–40.1019%13 Mar
overpass10–13-0.059%12 Mar
inferno4–130.014%12 Mar
nuke13–80.0110%11 Mar
overpass14–16-0.0412%11 Mar
inferno7–13-0.0612%9 Mar
nuke13–60.1322%8 Mar
overpass13–6-0.0816%8 Mar
inferno13–8-0.0510%7 Mar
mirage13–9-0.0123%6 Mar
dust25–13-0.0415%4 Mar
nuke13–110.0312%27 Feb
train13–60.0337%26 Feb
dust26–130.0334%26 Feb

Match data via Leetify.

Recent teammates

Milestones

100 Matches
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