bi-lard

bi-lard — CS2 Stats

76561199104334363[U:1:1144068635]Steam profile ↗✓ No bans

1,009Tracked matches34%Win rate2021Tracked since
3,224Hours in CS63Hrs last 2 wks
CSDB Rating5.3 DevelopingPositional Player
FaceitLevel 8Top 31.2% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 16,813 +16 4 Jun – 29 Jun · 5 days played
16,68917,059peak 17,0594 Jun29 Jun
17,161Peak Premier in tracked matches
44Days played since 2026-06-04

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches86——
Win rate45%——
K/D0.64——
Headshot %50%——

Measured 5 Sep 2026 → 3 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 8 among CSDB-tracked players (n=14,773), 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 8 medianLevel 9 medianvs Level 9
Headshot rate43.4%46.8%48.2%4.8% short
Shot accuracy16.1%13.0%13.3%above
Kill/death ratio1.051.061.070.02 short
Match win rate47.0%46.3%46.9%meets

This profile matches the typical Level 9 player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGbi-lardFACEITLevel 8STANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim79
Positioning56
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY45–54–1Last 10045%Win rateWLLLWWLWWL

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating · −1.7pp headshot accuracy · −32ms reaction

Win rate up 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 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 574ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 543ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 15%
  • Avg reaction 559ms

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 (+2.1 against its own average).

Aim7.9
Utility3.8
Positioning5.6
Opening Duels1.0
Clutch3.6

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

sh1ro

Plays most like sh1ro 89% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; lower opening-duel success.

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. 586ms 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

Aim7.9
Positioning5.6
Utility3.8
Mechanics6.7
Opening Duels2.8
Win Impact0.0

Composite 5.3/10 (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-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time572ms−73ms
first ⅓ avg 645ms → last ⅓ avg 572ms
Headshot accuracy16.5%−1.4%
first ⅓ avg 17.8% → 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

0.15Best match rating · 13–6 · anubis, 29 Jun →
41%Best headshot accuracy · 2–13 · ancient, 21 Sept →
422msFastest reaction time · 2–13 · inferno, 26 Jun →
13–1Biggest win · mirage, 26 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
8–10In matches decided by ≤2 rounds
11Overtime games

Map breakdown

cacheBest map · 71% over 7infernoWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
mirageA3017–1357%-0.00
dust2D217–1433%-0.02
ancientC177–1041%-0.01
anubisB147–750%0.00
cacheS75–271%0.01
infernoD50–50%-0.07
nukeC52–340%-0.03
overpass—10–10%0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

79,049Lifetime kills
1.05K/D
3,890Matches
47.0%Match win rate · Top 50% of Level 8 players
43.4%Headshot %
16.1%Shot accuracy · Top 25% of Level 8 players
9,820MVPs
1,672Hours (in match)
4,670Bombs planted
1,122Bombs defused

Most-used weapons

AK-4721,143
AWP7,399
FAMAS3,737
MP91,209
MP71,185

Lifetime map wins

3,687dust2
2,447inferno
1,403nuke
1,065train
935vertigo
276cbble
55lake
31office

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

Faceit stats

Combat

329Matches
52%Win rate
1.07Avg K/D
79.7ADR
43%Headshot %

Clutches & streaks

38%1v1 clutch win
22%1v2 clutch win
7Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage9257%1.1816.4
Dust28442%1.0715.0
Anubis4240%1.0015.3
Ancient4060%1.0016.2
Nuke2572%1.0415.9
Inferno2143%0.9715.1
Cache1377%1.0514.4
Overpass450%1.0013.3

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.

16.6%Headshot accuracy
38.1%Accuracy (enemy spotted)
41.0%Spray accuracy
80.0%Counter-strafing
8.7°Preaim
586msReaction time
47.0%T opening success
35.6%CT opening success
0.46Enemies flashed / flash
6.4%Flash assists
13.06HE damage / grenade
5.94Flashes / 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 0.4558 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

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

    CT opening duels 35.5984% — 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.

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–110.0411%30 Sept →
inferno11–13-0.0610%30 Sept →
ancient6–130.0113%27 Sept →
dust27–13-0.0517%27 Sept →
dust213–60.1024%27 Sept →
ancient13–7-0.0316%27 Sept →
dust210–130.0117%26 Sept →
cache13–100.0013%26 Sept →
mirage13–10.0311%26 Sept →
cache11–130.048%25 Sept →
nuke22–19-0.0512%25 Sept →
mirage3–13-0.0213%25 Sept →
mirage13–110.0011%23 Sept →
dust211–13-0.0521%23 Sept →
ancient7–130.0221%23 Sept →
mirage7–13-0.0523%23 Sept →
nuke1–13-0.078%23 Sept →
dust215–19-0.0220%22 Sept →
anubis4–13-0.0510%22 Sept →
dust213–110.0117%21 Sept →
ancient2–13-0.0241%21 Sept →
cache16–120.0126%20 Sept →
dust23–130.0519%20 Sept →
mirage13–70.0322%20 Sept →
nuke6–13-0.0123%19 Sept →
anubis12–12-0.0616%19 Sept →
inferno4–9-0.1111%19 Sept →
mirage7–130.0218%19 Sept →
anubis11–13-0.0217%19 Sept →
ancient5–13-0.0221%19 Sept →
mirage9–13-0.047%19 Sept →
dust26–13-0.0613%15 Sept →
mirage13–90.0814%15 Sept →
cache13–50.0521%15 Sept →
dust29–13-0.038%15 Sept →
mirage5–13-0.0320%15 Sept →
nuke16–140.0123%13 Sept →
mirage13–8-0.019%13 Sept →
ancient13–2-0.063%13 Sept →
anubis14–16-0.029%11 Sept →
dust23–13-0.0415%9 Sept →
mirage17–19-0.0313%8 Sept →
anubis13–4-0.056%2 Sept →
mirage13–80.0113%1 Sept →
anubis13–90.012%30 Aug →
cache9–13-0.0215%29 Aug →
ancient13–70.0415%29 Aug →
anubis6–130.029%28 Aug →
cache13–10-0.0416%28 Aug →
mirage7–13-0.0110%27 Aug →
mirage13–60.0514%27 Aug →
nuke15–19-0.0313%26 Aug →
mirage7–13-0.0611%24 Aug →
cache7–30.045%24 Aug →
anubis11–13-0.0016%24 Aug →
dust25–13-0.0613%24 Aug →
ancient8–130.039%24 Aug →
ancient13–100.0314%24 Aug →
dust213–11-0.0114%24 Aug →
mirage13–90.0220%23 Aug →
dust27–130.0315%23 Aug →
anubis13–40.0324%20 Aug →
mirage13–40.0312%18 Aug →
mirage13–90.0115%16 Aug →
dust210–13-0.0314%16 Aug →
dust26–13-0.0121%15 Aug →
ancient10–130.0014%15 Aug →
anubis13–4-0.0421%14 Aug →
dust23–13-0.0617%14 Aug →
dust28–13-0.134%12 Aug →
mirage13–11-0.1017%9 Aug →
mirage6–13-0.0712%9 Aug →
dust213–4-0.0314%9 Aug →
mirage13–10.0311%9 Aug →
mirage13–5-0.1020%9 Aug →
inferno8–13-0.1022%8 Aug →
ancient14–16-0.0216%8 Aug →
ancient13–11-0.0312%7 Aug →
mirage13–10-0.0022%7 Aug →
dust213–90.0138%25 Jul →
mirage13–80.0719%25 Jul →
mirage14–16-0.054%24 Jul →
mirage6–13-0.0321%19 Jul →
ancient11–130.0121%16 Jul →
mirage8–130.0313%5 Jul →
anubis13–60.1519%29 Jun →
mirage13–80.0029%29 Jun →
anubis10–130.0218%29 Jun →
dust213–50.0021%29 Jun →
ancient13–16-0.0113%26 Jun →
inferno2–130.0111%26 Jun →
mirage13–30.0917%26 Jun →
dust213–80.0416%26 Jun →
ancient13–8-0.038%15 Jun →
mirage9–13-0.0116%15 Jun →
ancient16–14-0.0335%8 Jun →
inferno6–9-0.0928%7 Jun →
anubis13–100.0018%7 Jun →
overpass10–130.0019%6 Jun →
ancient10–130.0116%4 Jun →

Match data via Leetify.

Recent teammates

Milestones

1,000 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.