New Year Dodo

New Year Dodo — CS2 Stats

76561198105936449[U:1:145670721]Steam profile ↗

675Tracked matches41%Win rate2022Tracked since
CSDB Rating1.7 Learning
Ladder ranks via Leetify

Performance scores

Aim21
Positioning30
Utility2

0–100 skill scores via Leetify.

Recent form

COLD37585Last 10037%Win rateLLLWLLLLWL

Last 10 vs previous 10: -30pp win rate · -0.00 avg rating

Player DNA

Aim2.1
Aggression0.0
Utility0.2
Positioning3.0
Opening Duels0.0
Clutch0.0

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 54% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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. 582ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 58% 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

Aim2.1
Positioning3.0
Utility0.2
Mechanics1.7
Opening Duels0.0
Win Impact2.1

Composite 1.7/10 (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-0.05−0.01
first ⅓ avg -0.04 → last ⅓ avg -0.05
Reaction time584ms−82ms
first ⅓ avg 666ms → last ⅓ avg 584ms
Headshot accuracy10.1%+0.9%
first ⅓ avg 9.2% → last ⅓ avg 10.1%

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

0.22Best rating — dust2 7–1
132Biggest win — mirage
6Longest win streak
L3Current streak
45In matches decided by ≤2 rounds

Map breakdown

trainBest map · 60% over 10ancientWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
cacheB157847%-0.06
officeC104640%-0.05
nukeD103730%-0.06
trainA106460%-0.02
mirageC94544%-0.05
ancientD82625%-0.08
dust2D72529%-0.00
infernoA53260%-0.05
overpass4040%-0.05
agency43175%-0.07
italy3030%0.00
vertigo2020%-0.03
shelter2020%-0.05
fachwerk21150%-0.01
boulder2020%-0.06
alpine21150%-0.02
anubis1010%-0.10
warden1010%-0.04
golden1010%-0.01
palacio1010%-0.04
grail110100%-0.08

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6Matches
17%Win rate
0.75Avg K/D
40.3ADR
31%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsWLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage10%0.569.0
Ancient10%0.326.0

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.

10.6%Headshot accuracy
30.2%Accuracy (enemy spotted)
26.9%Spray accuracy
57.7%Counter-strafing
13.0°Preaim
582msReaction time
12.7%T opening success
22.2%CT opening success
0.05Enemies flashed / flash
1.8%Flash assists
0.00HE damage / grenade
0.11Flashes / 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 12.9893° — 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 10.6404% — below the 15% mark we flag

    Aim Training
  3. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.0546 — below the 0.5 mark we flag

    Grenade Lineups
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.

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
vertigo1–13-0.0620%29 Aug
ancient8–13-0.1025%26 Jul
shelter6–13-0.050%12 Jul
fachwerk13–80.0325%12 Jul
fachwerk10–13-0.0550%10 Jul
shelter6–13-0.050%10 Jul
boulder2–13-0.0620%10 Jul
boulder1–13-0.060%9 Jul
cache13–10-0.0712%5 Jul
cache1–13-0.140%5 Jul
italy12–120.0120%30 Jun
mirage13–9-0.050%13 Jun
italy11–130.0016%23 May
office3–13-0.110%20 May
nuke13–3-0.060%20 May
ancient13–7-0.060%20 May
office8–13-0.020%17 May
office13–7-0.090%17 May
cache13–5-0.074%14 May
cache7–13-0.110%12 May
cache6–13-0.130%12 May
cache13–8-0.058%12 May
cache13–6-0.0150%5 May
cache7–4-0.0750%5 May
cache4–13-0.080%5 May
cache6–13-0.068%5 May
cache13–11-0.1011%2 May
cache13–11-0.033%2 May
cache8–130.040%30 Apr
cache5–13-0.020%29 Apr
cache4–13-0.050%29 Apr
nuke9–13-0.024%27 Apr
train13–100.008%27 Apr
train13–100.000%26 Apr
train13–7-0.0750%26 Apr
italy10–130.00100%25 Apr
office13–10-0.014%26 Mar
office3–13-0.100%26 Mar
office10–13-0.110%26 Mar
vertigo10–13-0.000%21 Mar
office13–5-0.0520%21 Mar
office13–11-0.0113%21 Mar
mirage13–7-0.020%21 Mar
ancient13–8-0.090%21 Mar
inferno13–5-0.090%21 Mar
nuke13–9-0.110%20 Mar
mirage11–13-0.0618%20 Mar
ancient11–13-0.090%12 Mar
overpass8–13-0.083%12 Mar
ancient8–13-0.100%11 Mar
alpine6–13-0.0111%25 Feb
anubis7–13-0.1010%19 Feb
warden11–13-0.043%14 Feb
alpine13–5-0.047%8 Feb
mirage8–13-0.0529%3 Feb
mirage8–13-0.044%3 Feb
nuke3–13-0.120%6 Jan
mirage13–4-0.150%6 Dec
train9–13-0.0225%22 Nov
office8–130.046%22 Nov
mirage13–20.010%25 Oct
train12–120.0222%25 Oct
inferno13–8-0.0313%25 Oct
ancient4–13-0.070%24 Oct
dust24–13-0.0620%24 Oct
office9–13-0.070%8 Oct
golden12–12-0.010%7 Oct
palacio8–13-0.0413%5 Oct
train9–13-0.024%28 Sept
overpass10–130.029%27 Sept
nuke10–13-0.0429%27 Sept
nuke10–13-0.020%26 Sept
train13–5-0.050%26 Sept
mirage6–13-0.060%26 Sept
inferno3–13-0.0325%21 Sept
overpass6–13-0.1017%21 Sept
dust28–13-0.030%20 Sept
ancient6–13-0.080%20 Sept
mirage2–13-0.0633%20 Sept
dust27–13-0.040%20 Sept
train13–9-0.010%16 Sept
nuke8–13-0.070%14 Sept
nuke7–13-0.0614%8 Sept
train12–12-0.0510%7 Sept
dust25–13-0.108%23 Aug
dust213–6-0.0219%23 Aug
ancient8–13-0.010%15 Aug
overpass12–12-0.0513%29 Jul
inferno13–8-0.0215%29 Jul
nuke13–8-0.0310%23 Jul
nuke3–13-0.1010%19 Jul
dust28–130.029%12 Jul
dust27–10.2222%12 Jul
agency13–10-0.0312%13 Jun
agency13–6-0.110%13 Jun
inferno11–13-0.070%9 Jun
grail13–11-0.0816%30 May
agency13–5-0.078%22 May
train13–5-0.047%22 May
agency8–13-0.070%19 May

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →