Lidl wain

Lidl wain — CS2 Stats

CD76561199242152816[U:1:1281887088]Steam profile ↗✓ No bans

593Tracked matches43%Win rate2022Tracked since
567Hours in CS1Hrs last 2 wks
CSDB Rating3.9 LearningSupport
FaceitLevel 7 · 1,474 ELOTop 42.3% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 17,053 +1,961 26 Dec – 29 Mar · 33 days played
13,66818,290peak 18,29026 Dec29 Mar
18,290Peak Premier in tracked matches
1,474Highest Faceit ELO seen on CSDB
58Days played since 2025-12-26

Faceit ELO

  • At peak — 1,474
  • Next: Level 8 at 1,531 — 57 to go
  • Reached: Level 7 · Level 6 · Level 5 · Level 4

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

How this compares with the same rank

Median values for Level 7 among CSDB-tracked players (n=14,595), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 7 medianLevel 8 medianvs Level 8
Headshot rate59.3%45.7%46.8%above
Shot accuracy2.5%12.7%13.0%10.4% short
Kill/death ratio0.951.051.060.11 short
Match win rate44.4%45.7%46.3%1.9% short

This profile matches the typical Level 8 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 8 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGLidl wainFACEITLevel 7 · 1,474 ELOSTANDINGTop 42.3% of rankedPEAK ELO1,474csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim46
Positioning43
Utility56

0–100 skill scores via Leetify.

Recent form

COLD55–40–5Last 10055%Win rateWLWLLLLTWL

Last 10 vs previous 10: −20pp win rate · −0.02 avg rating · +2.9pp headshot accuracy · −10ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 611ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 17%
  • Avg reaction 611ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 616ms

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: Support — Utility contribution stands above the rest of this profile (+1.8 against its own average).

Aim4.6
Utility5.6
Positioning4.3
Opening Duels2.1
Clutch3.4

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

Twistzz

Plays most like Twistzz 79% 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

CT openings. Opening success drops from 49% on T to 31% on CT — first contacts on the defending side are being lost.

Reaction time. 639ms 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

Aim4.6
Positioning4.3
Utility5.6
Mechanics4.8
Opening Duels2.6
Win Impact2.6

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time635ms−1ms
first ⅓ avg 635ms → last ⅓ avg 635ms
Headshot accuracy16.5%−4.9%
first ⅓ avg 21.4% → last ⅓ avg 16.5%

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

0.12Best match rating · 13–1 · dust2, 25 Jan →
34%Best headshot accuracy · 13–3 · mirage, 26 Dec →
445msFastest reaction time · 13–8 · dust2, 18 Jan →
13–1Biggest win · ancient, 20 Feb →

Across the last 100 tracked matches.

Highlights

6Longest win streak
4–9In matches decided by ≤2 rounds
13Overtime games

Map breakdown

nukeBest map · 71% over 17anubisWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
mirageB2412–1250%0.01
dust2A1811–761%0.01
ancientB179–853%-0.02
nukeS1712–571%-0.01
infernoB84–450%-0.02
overpassS64–267%0.03
anubisD51–420%-0.00
cache—30–30%-0.01
train—22–0100%0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

15,060Lifetime kills
0.95K/D
784Matches
44.4%Match win rate
59.3%Headshot % · Top 10% of Level 7 players
2.5%Shot accuracy
2,082MVPs
367Hours (in match)
900Bombs planted
150Bombs defused

Most-used weapons

Lifetime map wins

996nuke
944dust2
563vertigo
548inferno
158train
16office
14cbble
5italy

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

Faceit stats

Combat

164Matches
53%Win rate
1.07Avg K/D
83.0ADR
51%Headshot %

Clutches & streaks

37%1v1 clutch win
33%1v2 clutch win
7Longest win streak

Recent Faceit resultsWWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage6152%1.1515.7
Nuke2152%1.1018.2
Ancient1963%1.0316.9
Dust21735%1.0915.9
Anubis1331%0.8814.2
Inferno1145%0.8013.6
Overpass1173%1.0113.8
Vertigo1080%1.1514.6

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.

17.9%Headshot accuracy
31.5%Accuracy (enemy spotted)
31.4%Spray accuracy
71.6%Counter-strafing
10.7°Preaim
639msReaction time
49.4%T opening success
31.5%CT opening success
0.59Enemies flashed / flash
7.6%Flash assists
6.18HE damage / grenade
12.55Flashes / 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

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 31.4618% — below the 40% mark we flag

Spend your practice time on Anubis

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–10-0.0019%24 Oct →
ancient6–13-0.0728%19 Oct →
inferno13–30.0213%10 Oct →
anubis14–16-0.0416%25 Sept →
nuke7–13-0.0414%21 Aug →
cache11–130.0518%16 May →
cache2–13-0.0918%16 May →
cache12–120.0124%1 May →
mirage10–10.1110%3 Apr →
mirage7–13-0.0713%29 Mar →
dust213–16-0.0317%28 Mar →
mirage13–50.0814%27 Mar →
mirage8–13-0.0930%25 Mar →
mirage13–80.0412%24 Mar →
overpass13–160.0219%23 Mar →
nuke13–8-0.0318%19 Mar →
ancient13–30.027%16 Mar →
mirage4–40.000%12 Mar →
dust26–130.0110%12 Mar →
overpass13–90.0616%11 Mar →
dust26–130.0328%9 Mar →
inferno12–16-0.0323%5 Mar →
dust212–12-0.0527%5 Mar →
dust213–16-0.0423%25 Feb →
mirage8–130.0226%24 Feb →
ancient13–6-0.0413%22 Feb →
anubis8–13-0.0310%22 Feb →
ancient13–10.068%20 Feb →
nuke13–9-0.049%20 Feb →
mirage13–20.0521%17 Feb →
ancient3–13-0.069%16 Feb →
inferno9–13-0.0211%16 Feb →
overpass13–10-0.0023%15 Feb →
dust213–9-0.0025%15 Feb →
nuke1–13-0.0011%14 Feb →
nuke13–70.0428%14 Feb →
nuke13–80.0224%13 Feb →
ancient13–7-0.0515%13 Feb →
mirage13–80.0111%8 Feb →
dust29–0-0.0213%8 Feb →
anubis13–60.0815%7 Feb →
anubis4–13-0.0526%6 Feb →
mirage13–4-0.0019%6 Feb →
mirage9–13-0.0020%4 Feb →
nuke4–13-0.0621%3 Feb →
overpass13–30.1032%3 Feb →
ancient15–15-0.0615%2 Feb →
dust213–80.0225%2 Feb →
mirage13–50.0313%1 Feb →
overpass11–13-0.0115%1 Feb →
mirage13–60.0429%1 Feb →
ancient13–50.0219%31 Jan →
nuke13–8-0.0316%31 Jan →
mirage11–13-0.0111%30 Jan →
nuke13–4-0.0115%30 Jan →
ancient16–12-0.0215%30 Jan →
dust213–11-0.0119%26 Jan →
mirage5–13-0.089%25 Jan →
dust213–10.1222%25 Jan →
ancient10–13-0.0321%24 Jan →
nuke13–80.0022%24 Jan →
dust213–80.0729%24 Jan →
ancient6–130.0117%24 Jan →
anubis15–150.0226%24 Jan →
ancient13–80.0127%19 Jan →
dust213–8-0.0221%18 Jan →
inferno16–140.0121%16 Jan →
mirage2–13-0.0723%16 Jan →
dust25–13-0.0425%16 Jan →
nuke13–5-0.0316%14 Jan →
mirage4–13-0.0625%13 Jan →
nuke13–6-0.028%13 Jan →
mirage13–80.018%11 Jan →
dust213–30.0526%9 Jan →
mirage5–13-0.0220%9 Jan →
inferno13–8-0.0610%6 Jan →
nuke3–13-0.1017%5 Jan →
nuke13–40.0011%5 Jan →
mirage11–130.0321%4 Jan →
ancient13–8-0.0116%4 Jan →
dust210–13-0.0519%3 Jan →
train13–90.0123%3 Jan →
train13–110.0130%3 Jan →
ancient15–15-0.1218%2 Jan →
inferno7–13-0.0425%1 Jan →
nuke13–70.0523%1 Jan →
overpass13–90.0128%1 Jan →
ancient14–16-0.0218%29 Dec →
dust213–10.0725%29 Dec →
nuke7–13-0.0332%29 Dec →
mirage16–120.0320%28 Dec →
mirage14–160.0323%28 Dec →
dust213–110.0631%27 Dec →
dust213–50.1028%27 Dec →
ancient11–130.0123%26 Dec →
nuke13–10.0222%26 Dec →
mirage13–100.0931%26 Dec →
inferno5–13-0.058%26 Dec →
mirage13–3-0.0034%26 Dec →
ancient13–60.0523%26 Dec →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.