Daryl

Daryl — CS2 Stats

US76561199019341399[U:1:1059075671]Steam profile ↗✓ No bans

274Tracked matches59%Win rate2020Tracked since
1,255Hours in CS87Hrs last 2 wks
CSDB Rating6.2 SolidPositional Player
WingmanGold Nova II
Ladder ranks via Leetify

Performance scores

Aim67
Positioning56
Utility54

0–100 skill scores via Leetify.

Recent form

HOT46–45–9Last 10046%Win rateWWWWWWLWWL

Last 10 vs previous 10: 0pp win rate · −0.04 avg rating · −0.7pp headshot accuracy · +30ms reaction

Win rate 0pp 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

  • 5–0 · 100% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 548ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 16%
  • Avg reaction 581ms

Last 20

  • 16–4 · 80% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 16%
  • Avg reaction 566ms

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 (+1.2 against its own average).

Aim6.7
Utility5.4
Positioning5.6
Opening Duels2.2

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

iM

Plays most like iM 86% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: 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. 601ms 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

Aim6.7
Positioning5.6
Utility5.4
Mechanics8.2
Opening Duels1.9
Win Impact8.1

Composite 6.2/10 (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 rating0.01+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time558ms−15ms
first ⅓ avg 573ms → last ⅓ avg 558ms
Headshot accuracy15.4%−3.6%
first ⅓ avg 19.0% → last ⅓ avg 15.4%

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.

Personal bests

0.38Best match rating · 9–1 · inferno, 13 Oct →
40%Best headshot accuracy · 3–9 · inferno, 21 Oct →
391msFastest reaction time · 4–9 · inferno, 28 Oct →
13–1Biggest win · ancient, 12 Nov →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W6Current streak
7–6In matches decided by ≤2 rounds
1Overtime games

Map breakdown

dust2Best map · 73% over 11infernoWeakest map · 38% over 61
MapGradePlayedRecordWin rateAvg rating
infernoC6123–3838%-0.02
dust2S118–373%-0.02
nukeA85–363%-0.04
mirageS75–271%-0.00
vertigoC52–340%-0.01
office—30–30%0.01
ancient—22–0100%-0.02
anubis—10–10%-0.06
boulder—10–10%-0.02
cache—11–0100%-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 61). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

33,556Lifetime kills
1.16K/D · Top 25% of tracked players
2,315Matches
57.5%Match win rate · Top 5% of tracked players
51.6%Headshot % · Top 25% of tracked players
18.1%Shot accuracy · Top 10% of tracked players
7,314MVPs
728Hours (in match)
1,016Bombs planted
1,040Bombs defused

Most-used weapons

AK-4712,719
AWP2,260
Knife796
MP9749

Lifetime map wins

2,666dust2
2,554inferno
2,521vertigo
921train
645nuke
135cbble
108office
97lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

15.0%Headshot accuracy
31.6%Accuracy (enemy spotted)
34.1%Spray accuracy
87.0%Counter-strafing
8.8°Preaim
601msReaction time
37.7%T opening success
37.9%CT opening success
0.68Enemies flashed / flash
11.5%Flash assists
12.14HE 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

    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 37.6712% — 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 61 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–10-0.0218%14 Nov →
dust213–7-0.0210%14 Nov →
ancient13–10.0325%12 Nov →
ancient13–3-0.0617%11 Nov →
dust27–60.048%8 Nov →
mirage13–2-0.019%8 Nov →
inferno3–9-0.1715%7 Nov →
inferno9–50.1519%7 Nov →
inferno9–20.1725%7 Nov →
vertigo3–9-0.0915%7 Nov →
vertigo9–10.1917%7 Nov →
dust213–3-0.0019%7 Nov →
dust213–1-0.063%7 Nov →
inferno1–9-0.2017%7 Nov →
inferno9–40.1814%7 Nov →
inferno9–10.2314%7 Nov →
inferno9–10.1823%7 Nov →
inferno5–9-0.0320%5 Nov →
inferno9–6-0.0516%5 Nov →
mirage13–110.0125%4 Nov →
inferno9–10.2419%4 Nov →
inferno6–9-0.140%4 Nov →
inferno2–9-0.1220%4 Nov →
inferno9–40.1524%3 Nov →
inferno3–9-0.1811%3 Nov →
inferno9–6-0.0221%3 Nov →
inferno9–60.119%3 Nov →
inferno2–9-0.1311%3 Nov →
office5–130.0011%2 Nov →
mirage7–130.0217%2 Nov →
office12–12-0.0411%2 Nov →
dust28–13-0.069%2 Nov →
inferno8–8-0.0317%2 Nov →
inferno9–7-0.0525%31 Oct →
inferno8–80.1118%31 Oct →
nuke9–7-0.0318%31 Oct →
inferno9–10.2613%31 Oct →
office5–130.0627%31 Oct →
vertigo3–9-0.0817%30 Oct →
inferno6–90.0122%30 Oct →
inferno1–9-0.1213%30 Oct →
nuke9–20.098%29 Oct →
inferno4–9-0.0917%28 Oct →
inferno7–9-0.0917%28 Oct →
inferno0–9-0.2516%28 Oct →
dust213–7-0.0431%25 Oct →
dust213–7-0.0212%25 Oct →
inferno9–70.0816%24 Oct →
inferno0–9-0.2711%24 Oct →
inferno3–9-0.138%24 Oct →
inferno9–6-0.018%24 Oct →
nuke9–00.0417%24 Oct →
vertigo9–5-0.057%23 Oct →
nuke5–9-0.1419%21 Oct →
inferno8–8-0.0912%21 Oct →
inferno9–20.0417%21 Oct →
inferno5–9-0.0621%21 Oct →
inferno6–9-0.0425%21 Oct →
inferno3–9-0.1840%21 Oct →
inferno5–9-0.057%20 Oct →
nuke4–9-0.1914%20 Oct →
inferno7–9-0.1022%20 Oct →
nuke9–40.008%19 Oct →
nuke9–70.0013%18 Oct →
inferno5–9-0.0427%18 Oct →
inferno9–20.0727%18 Oct →
inferno9–5-0.0221%18 Oct →
inferno7–90.0515%17 Oct →
inferno8–80.0211%17 Oct →
inferno5–9-0.137%15 Oct →
inferno8–8-0.073%15 Oct →
inferno9–60.0915%15 Oct →
inferno9–20.0918%15 Oct →
inferno6–90.0223%14 Oct →
inferno7–9-0.0320%14 Oct →
inferno8–80.0217%14 Oct →
inferno9–5-0.0024%14 Oct →
inferno9–30.076%14 Oct →
inferno8–8-0.1031%14 Oct →
anubis2–13-0.064%14 Oct →
inferno2–9-0.0632%14 Oct →
vertigo8–8-0.0524%14 Oct →
inferno9–50.1627%14 Oct →
dust211–13-0.0021%13 Oct →
dust213–40.0615%13 Oct →
boulder6–13-0.027%13 Oct →
inferno3–9-0.0415%13 Oct →
inferno7–9-0.0326%13 Oct →
inferno3–9-0.1136%13 Oct →
nuke9–13-0.096%13 Oct →
inferno2–9-0.1028%13 Oct →
inferno9–10.3836%13 Oct →
inferno0–9-0.308%13 Oct →
inferno3–9-0.1633%13 Oct →
cache13–11-0.0712%13 Oct →
mirage6–13-0.0513%13 Oct →
dust25–9-0.0821%25 Jul →
dust29–3-0.0536%24 Jul →
mirage9–4-0.0123%24 Jul →
mirage16–40.0512%23 Jul →

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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