Dodo

Dodo — CS2 Stats

76561198017941683[U:1:57675955]Steam profile ↗✓ No bans

226Tracked matches54%Win rate2020Tracked since
CSDB Rating3.9 LearningPositional Player
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 12,191 +4,460 21 Mar – 5 Apr · 4 days played
6,79212,223peak 12,22321 Mar5 Apr
12,467Peak Premier in tracked matches
27Days played since 2021-11-12

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

Performance scores

Aim32
Positioning51
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY49–44–7Last 10049%Win rateLLLWLWWLWW

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +1.3pp headshot accuracy · +13ms 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

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 11%
  • Avg reaction 658ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 642ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 636ms

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 (+0.9 against its own average).

Aim3.2
Utility4.5
Positioning5.1
Opening Duels3.0

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

m0NESY

Plays most like m0NESY 66% 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. 633ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 62% 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

Aim3.2
Positioning5.1
Utility4.5
Mechanics2.6
Opening Duels2.3
Win Impact6.2

Composite 3.9/10 (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-0.00−0.03
first ⅓ avg 0.02 → last ⅓ avg -0.00
Reaction time637ms−0ms
first ⅓ avg 637ms → last ⅓ avg 637ms
Headshot accuracy11.7%−0.9%
first ⅓ avg 12.6% → last ⅓ avg 11.7%

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

0.22Best match rating · 13–6 · anubis, 30 Jan →
29%Best headshot accuracy · 6–13 · inferno, 13 Mar →
469msFastest reaction time · 13–5 · anubis, 14 Mar →
13–1Biggest win · anubis, 5 Apr →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L3Current streak
5–4In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 88% over 8ancientWeakest map · 33% over 15
MapGradePlayedRecordWin rateAvg rating
mirageB1910–953%0.03
infernoC166–1038%0.03
ancientD155–1033%0.01
nukeB126–650%0.01
dust2C104–640%0.03
anubisS87–188%0.04
overpassB84–450%0.01
trainS64–267%0.05
vertigo—43–175%0.05
cache—20–20%-0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Ancient 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.

11.7%Headshot accuracy
34.4%Accuracy (enemy spotted)
37.8%Spray accuracy
61.8%Counter-strafing
13.4°Preaim
633msReaction time
38.4%T opening success
40.2%CT opening success
0.52Enemies flashed / flash
3.8%Flash assists
10.91HE damage / grenade
5.76Flashes / 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 13.4051° — 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 11.6712% — below the 15% mark we flag

    Aim Training →
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.

33% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust29–130.0111%26 Aug →
inferno6–130.058%26 Aug →
mirage9–13-0.0413%5 Apr →
anubis13–1-0.0110%5 Apr →
inferno10–130.0113%5 Apr →
nuke13–11-0.0618%4 Apr →
ancient13–4-0.0017%4 Apr →
ancient11–13-0.033%4 Apr →
anubis13–10-0.0221%4 Apr →
overpass13–90.0314%4 Apr →
mirage13–6-0.046%4 Apr →
nuke3–13-0.0815%4 Apr →
anubis15–150.0212%4 Apr →
dust213–11-0.0211%4 Apr →
ancient9–13-0.0811%4 Apr →
mirage13–100.0216%4 Apr →
inferno7–13-0.012%4 Apr →
ancient13–50.057%4 Apr →
inferno15–15-0.0414%4 Apr →
dust210–130.0317%3 Apr →
inferno5–13-0.0315%3 Apr →
inferno9–13-0.0316%3 Apr →
anubis13–100.0015%3 Apr →
ancient9–130.024%3 Apr →
nuke7–13-0.093%3 Apr →
mirage13–10.0611%3 Apr →
mirage13–9-0.016%14 Mar →
train13–70.0111%14 Mar →
anubis13–5-0.0315%14 Mar →
inferno13–10.1116%14 Mar →
ancient13–20.019%14 Mar →
overpass9–130.0215%14 Mar →
dust213–100.0313%14 Mar →
vertigo7–2-0.0113%14 Mar →
nuke13–20.0810%14 Mar →
train13–20.058%14 Mar →
mirage6–13-0.024%14 Mar →
vertigo13–60.1113%14 Mar →
ancient13–90.0311%14 Mar →
anubis13–40.0511%14 Mar →
dust213–50.0711%14 Mar →
inferno7–10.0914%14 Mar →
overpass13–60.0218%14 Mar →
nuke10–13-0.0217%14 Mar →
nuke13–50.1312%13 Mar →
vertigo13–50.1511%13 Mar →
anubis13–70.0415%13 Mar →
inferno6–130.0029%13 Mar →
mirage12–12-0.0114%13 Mar →
train12–12-0.0114%13 Mar →
dust213–100.1118%13 Mar →
overpass5–130.047%13 Mar →
anubis13–60.2225%30 Jan →
dust25–130.0420%24 Jan →
inferno13–20.174%24 Jan →
nuke13–60.0715%24 Jan →
mirage9–100.017%4 Jan →
ancient8–130.0513%4 Jan →
overpass13–11-0.0213%11 Oct →
ancient5–13-0.0519%11 Oct →
overpass9–13-0.0610%9 Oct →
mirage12–120.1011%9 Oct →
dust22–13-0.0118%9 Oct →
overpass13–30.049%23 Sept →
dust23–13-0.0217%20 Sept →
train13–80.1013%20 Sept →
ancient10–130.059%20 Sept →
overpass10–130.0412%20 Sept →
mirage8–130.057%20 Sept →
inferno13–40.1416%20 Sept →
ancient13–11-0.0119%18 Sept →
nuke13–60.065%18 Sept →
ancient11–130.058%15 Sept →
nuke10–13-0.0125%2 Apr →
ancient9–13-0.0013%2 Apr →
inferno4–13-0.0010%2 Apr →
mirage13–90.0212%21 Mar →
inferno11–130.0010%11 Mar →
mirage13–10.0810%11 Mar →
mirage13–90.0915%10 Mar →
dust215–150.0313%10 Mar →
train13–100.066%9 Mar →
inferno13–10-0.0415%9 Mar →
mirage7–130.0116%9 Mar →
nuke13–20.109%27 Feb →
mirage15–150.0714%18 Feb →
mirage13–70.0311%18 Feb →
train10–130.056%18 Feb →
mirage3–130.0825%10 Feb →
ancient11–130.0910%10 Feb →
mirage12–10.0614%10 Feb →
inferno8–130.0316%10 Feb →
cache7–16-0.0627%14 Apr →
nuke5–16-0.064%14 Apr →
mirage8–16-0.054%10 May →
cache9–16-0.0112%10 May →
nuke4–16-0.0311%10 May →
vertigo2–9-0.0710%7 Jan →
inferno16–13-0.0217%12 Nov →
ancient4–16-0.0711%12 Nov →

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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