Doc Holliday

Doc Holliday — CS2 Stats

US76561198037809779[U:1:77544051]Steam profile ↗✓ No bans

234Tracked matches41%Win rate2022Tracked since
CSDB Rating2.1 Learning
Ladder ranks via Leetify

Performance scores

Aim10
Positioning30
Utility32

0–100 skill scores via Leetify.

Recent form

STEADY38602Last 10038%Win rateLLLLWTWWWW

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating

Player DNA

Aim1.0
Aggression1.3
Utility3.2
Positioning3.0
Opening Duels0.0

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 60% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower opening-fight frequency; 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. 744ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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

Aim1.0
Positioning3.0
Utility3.2
Mechanics3.5
Opening Duels0.0
Win Impact2.1

Composite 2.1/10 (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 time734ms+40ms
first ⅓ avg 694ms → last ⅓ avg 734ms
Headshot accuracy10.0%−0.2%
first ⅓ avg 10.2% → last ⅓ avg 10.0%

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

0.05Best rating — inferno 13–10
120Biggest win — nuke
4Longest win streak
L4Current streak
67In matches decided by ≤2 rounds
4Overtime games

Map breakdown

nukeBest map · 56% over 16ancientWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
nukeA169756%-0.04
mirageD1541127%-0.05
trainB136746%-0.05
anubisC125742%-0.03
ancientD1221017%-0.08
dust2D124833%-0.04
infernoB115645%-0.05
overpassC52340%-0.03
vertigo31233%-0.02
office1010%-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 12). 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.

10.2%Headshot accuracy
18.8%Accuracy (enemy spotted)
33.7%Spray accuracy
65.9%Counter-strafing
11.6°Preaim
744msReaction time
25.6%T opening success
27.0%CT opening success
0.47Enemies flashed / flash
5.0%Flash assists
5.40HE damage / grenade
2.84Flashes / 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. 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 10.2457% — below the 15% mark we flag

    Aim Training
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 743.6422ms — above the 700ms 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 0.4694 — 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.

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke9–13-0.069%17 Jul
mirage2–13-0.0514%5 Jul
anubis10–13-0.0624%28 Jun
nuke12–16-0.098%28 Jun
anubis13–11-0.0912%20 Jun
ancient15–15-0.0810%25 Apr
inferno13–9-0.0312%12 Apr
nuke13–5-0.0117%12 Apr
anubis13–60.0122%12 Apr
nuke13–9-0.0211%11 Apr
inferno10–13-0.0812%7 Mar
anubis11–13-0.095%7 Mar
overpass3–13-0.056%21 Feb
ancient5–13-0.076%21 Feb
overpass13–10-0.056%8 Feb
mirage10–13-0.077%17 Jan
nuke9–13-0.063%17 Jan
ancient8–13-0.087%17 Jan
ancient4–13-0.099%12 Jan
train13–11-0.0610%12 Jan
ancient13–8-0.0916%19 Dec
mirage13–6-0.087%19 Dec
overpass13–110.0110%4 Oct
overpass2–13-0.057%11 Aug
overpass13–16-0.0411%10 Aug
dust213–10-0.0117%8 Aug
train13–3-0.056%4 Aug
nuke2–8-0.0612%4 Aug
office7–13-0.020%26 Jul
ancient2–13-0.0817%26 Jul
nuke1–13-0.020%19 Jul
ancient11–13-0.046%17 Jul
nuke12–00.0017%17 Jul
dust213–6-0.063%16 Jul
mirage8–13-0.088%12 Jul
train13–11-0.007%12 Jul
inferno7–13-0.0513%10 Jul
inferno5–13-0.0912%3 Jul
anubis2–13-0.013%3 Jul
mirage4–13-0.0312%30 Jun
inferno13–2-0.0213%29 Jun
ancient5–13-0.077%29 Jun
mirage2–13-0.047%29 Jun
anubis4–13-0.0412%29 Jun
nuke13–4-0.028%29 Jun
dust25–13-0.042%29 Jun
ancient8–13-0.0615%29 Jun
anubis12–12-0.093%28 Jun
train4–13-0.0511%28 Jun
nuke9–1-0.000%28 Jun
ancient13–3-0.0722%28 Jun
train9–13-0.0710%21 Jun
dust213–11-0.068%21 Jun
mirage3–13-0.0611%21 Jun
inferno11–13-0.088%20 Jun
ancient9–13-0.100%20 Jun
nuke13–6-0.0316%12 Jun
ancient4–13-0.098%12 Jun
train13–7-0.033%12 Jun
anubis5–130.0117%12 Jun
inferno13–10-0.060%7 Jun
mirage5–13-0.0420%7 Jun
inferno7–9-0.104%7 Jun
mirage13–7-0.0210%29 May
dust29–13-0.0611%29 May
train1–6-0.080%29 May
vertigo10–13-0.0717%25 May
mirage7–13-0.1211%25 May
nuke13–5-0.050%25 May
train5–13-0.1410%23 Apr
anubis13–50.0117%22 Apr
nuke13–11-0.066%10 Apr
train13–16-0.037%10 Apr
mirage13–8-0.017%10 Apr
nuke4–13-0.0215%9 Apr
mirage1–8-0.0112%9 Apr
train8–13-0.049%9 Apr
inferno13–100.0510%8 Apr
anubis6–13-0.0810%8 Apr
dust211–13-0.0117%8 Apr
nuke11–13-0.079%4 Apr
inferno11–13-0.052%30 Mar
anubis13–80.0316%29 Mar
dust28–13-0.0817%29 Mar
dust23–13-0.049%2 Mar
train7–13-0.079%2 Mar
train10–10.026%1 Mar
mirage9–13-0.0516%3 Feb
dust213–3-0.0122%2 Feb
mirage6–13-0.124%2 Feb
train8–13-0.076%1 Feb
dust26–13-0.0611%1 Feb
mirage13–70.0410%31 Jan
nuke13–7-0.0714%26 Jan
inferno13–4-0.048%26 Jan
vertigo13–6-0.014%15 Jan
vertigo7–130.0211%14 Jan
dust27–13-0.0316%12 Jan
anubis13–40.048%12 Jan
dust25–13-0.0610%10 Jan

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 →