the davils green grass

the davils green grass — CS2 Stats

76561199490995182[U:1:1530729454]Steam profile ↗✓ No bans

268Tracked matches68%Win rate2025Tracked since
CSDB Rating4.7 DevelopingPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 25 Sep 2026 (21 days ago). Ranks are recorded once per day this page is viewed.

+2Tracked matches · now 268
−3.6ppWin rate · 71.4% → 67.9%

Rating over time

31Days played since 2026-06-09

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Performance scores

Aim57
Positioning42
Utility7

0–100 skill scores via Leetify.

Recent form

STEADY54–37–9Last 10054%Win rateLLWWTLWWLL

Last 10 vs previous 10: −40pp win rate · +0.02 avg rating · +5.9pp headshot accuracy · +30ms reaction

Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–2–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 664ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 22%
  • Avg reaction 642ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 19%
  • Avg reaction 627ms

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 (+2.4 against its own average).

Aim5.7
Utility0.7
Positioning4.2
Opening Duels0.4

Limited utility dependence

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

ropz

Plays most like ropz 85% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 654ms 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

Aim5.7
Positioning4.2
Utility0.7
Mechanics6.6
Opening Duels0.9
Win Impact10.0

Composite 4.7/10 (Developing), 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-0.04−0.06
first ⅓ avg 0.02 → last ⅓ avg -0.04
Reaction time651ms−34ms
first ⅓ avg 685ms → last ⅓ avg 651ms
Headshot accuracy21.3%+7.2%
first ⅓ avg 14.1% → last ⅓ avg 21.3%

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

0.15Best match rating · 13–6 · dust2, 9 Jun →
33%Best headshot accuracy · 13–7 · dust2, 29 Jul →
422msFastest reaction time · 13–10 · nuke, 15 Aug →
13–0Biggest win · train, 11 Jun →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
6–2In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 64% over 42cacheWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
nukeA4227–1564%-0.02
dust2A169–756%0.00
mirageB105–550%0.01
cacheC83–538%0.01
infernoC73–443%0.00
trainB63–350%0.00
vertigo—43–175%-0.02
overpass—21–150%-0.01
office—20–20%-0.03
ancient—20–20%-0.06
anubis—10–10%-0.08

Across the last 100 tracked matches.

Skill profile

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

21.2%Headshot accuracy
32.2%Accuracy (enemy spotted)
30.0%Spray accuracy
79.9%Counter-strafing
10.3°Preaim
654msReaction time
29.0%T opening success
37.1%CT opening success
0.38Enemies flashed / flash
1.7%Flash assists
1.63HE damage / grenade
0.48Flashes / 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. 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 0.3847 — below the 0.5 mark we flag

    Grenade Lineups →
  2. 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 29.0358% — below the 40% mark we flag

Spend your practice time on Cache

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 8 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
nuke6–130.0012%1 Oct →
nuke1–13-0.0017%1 Oct →
vertigo13–11-0.0814%29 Aug →
nuke13–80.0233%29 Aug →
nuke12–12-0.0320%29 Aug →
dust210–13-0.0230%29 Aug →
mirage8–3-0.0827%29 Aug →
nuke13–10-0.0323%21 Aug →
cache3–10-0.0427%17 Aug →
vertigo7–9-0.1214%17 Aug →
inferno8–80.0228%17 Aug →
overpass6–7-0.0717%17 Aug →
nuke13–10-0.0513%15 Aug →
nuke13–6-0.039%15 Aug →
nuke9–13-0.098%15 Aug →
dust213–10-0.1125%15 Aug →
nuke13–10-0.0412%8 Aug →
nuke13–8-0.0118%8 Aug →
inferno13–9-0.093%7 Aug →
nuke13–4-0.0525%5 Aug →
nuke13–11-0.1231%5 Aug →
dust26–13-0.0421%4 Aug →
nuke13–100.0225%4 Aug →
nuke12–120.0125%3 Aug →
nuke13–5-0.0219%3 Aug →
nuke13–3-0.0114%3 Aug →
nuke13–110.0131%31 Jul →
office9–13-0.0924%29 Jul →
dust213–7-0.0333%29 Jul →
mirage10–130.0132%29 Jul →
nuke6–13-0.0423%27 Jul →
nuke13–4-0.0727%27 Jul →
nuke13–20.0224%27 Jul →
mirage9–130.0027%21 Jul →
nuke12–120.0028%21 Jul →
nuke13–9-0.0218%21 Jul →
nuke13–8-0.049%21 Jul →
dust213–9-0.0324%16 Jul →
nuke13–4-0.0221%16 Jul →
mirage8–30.0329%16 Jul →
inferno13–90.0220%16 Jul →
mirage10–13-0.0510%16 Jul →
mirage8–130.0125%15 Jul →
vertigo13–90.0513%15 Jul →
dust213–11-0.0319%15 Jul →
nuke13–50.0224%15 Jul →
dust213–10-0.0125%13 Jul →
vertigo13–50.0519%13 Jul →
mirage13–100.0827%13 Jul →
inferno5–130.0823%9 Jul →
nuke8–13-0.0612%9 Jul →
nuke13–4-0.0418%9 Jul →
train11–13-0.0710%6 Jul →
nuke13–10.0323%2 Jul →
office8–130.0213%2 Jul →
mirage13–40.0919%2 Jul →
nuke13–3-0.0312%2 Jul →
nuke10–13-0.0610%30 Jun →
dust27–13-0.078%30 Jun →
nuke12–120.0415%29 Jun →
cache8–13-0.0210%24 Jun →
train1–13-0.0514%23 Jun →
train13–40.0311%23 Jun →
inferno9–7-0.0121%23 Jun →
nuke1–9-0.298%23 Jun →
dust28–13-0.0814%19 Jun →
cache13–70.069%19 Jun →
inferno6–130.0220%19 Jun →
train13–90.1010%19 Jun →
nuke13–60.0712%19 Jun →
cache4–130.0515%18 Jun →
ancient5–13-0.029%18 Jun →
nuke13–80.0310%18 Jun →
overpass10–130.0414%18 Jun →
dust25–130.1312%18 Jun →
nuke13–70.1110%18 Jun →
dust213–50.0711%18 Jun →
nuke13–50.0418%18 Jun →
cache13–4-0.0116%18 Jun →
dust28–130.0013%18 Jun →
mirage13–50.0814%18 Jun →
cache12–60.017%17 Jun →
dust213–20.0520%17 Jun →
nuke13–40.0813%15 Jun →
mirage7–13-0.0911%14 Jun →
cache12–120.0117%14 Jun →
anubis2–13-0.080%11 Jun →
dust24–130.0114%11 Jun →
nuke12–12-0.0627%11 Jun →
train13–00.0123%11 Jun →
nuke13–4-0.0116%11 Jun →
nuke9–13-0.0514%9 Jun →
dust213–10.0215%9 Jun →
ancient10–13-0.0912%9 Jun →
train12–12-0.0115%9 Jun →
inferno12–12-0.0116%9 Jun →
cache9–130.0317%9 Jun →
nuke9–13-0.0418%9 Jun →
nuke7–130.0112%9 Jun →
dust213–60.1513%9 Jun →

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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