Baz

Baz — CS2 Stats

GB76561198206299545[U:1:246033817]Steam profile ↗✓ No bans

550Tracked matches38%Win rate2025Tracked since
594Hours in CS4Hrs last 2 wks
CSDB Rating4.4 DevelopingClutch Specialist
Premier CS Rating16,785Purple band · top ~21.3% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Sep 2026 (36 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 16,785 -99 19 Apr – 30 Sept · 20 days played
16,42017,497peak 17,49719 Apr30 Sept
17,628Peak Premier in tracked matches
34Days played since 2026-04-18

Premier CS Rating

  • 712 below peak (17,497)
  • -44 over 30 days · steady
  • Next: Pink band at 20,000 — 3,215 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-18
  • Blue band first seen 2026-09-18

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 Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate58.3%44.4%46.9%above
Shot accuracy0.3%11.9%13.0%12.7% short
Kill/death ratio0.641.031.080.44 short
Match win rate41.4%45.2%46.7%5.3% short

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

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

Share this profile

CSDB.GGBazPREMIER16,785 · Purple bandcsdb.gg/stats

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Performance scores

Aim58
Positioning52
Utility24

0–100 skill scores via Leetify.

Recent form

COLD48–49–3Last 10048%Win rateLTWLLLLWLW

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +1.4pp headshot accuracy · −9ms 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 17%
  • Avg reaction 577ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 593ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 18%
  • Avg reaction 598ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+2.7 against its own average).

Aim5.8
Utility2.4
Positioning5.2
Opening Duels2.8
Clutch7.0

Limited utility dependenceReliable in 1v1s

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

donk

Plays most like donk 89% playstyle similarity

Most alike: positioning profile, utility contribution.

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

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

Reaction time. 606ms 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

Aim5.8
Positioning5.2
Utility2.4
Mechanics6.0
Opening Duels2.6
Win Impact1.0

Composite 4.4/10 (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-0.01−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time607ms−2ms
first ⅓ avg 609ms → last ⅓ avg 607ms
Headshot accuracy17.8%+3.9%
first ⅓ avg 14.0% → last ⅓ avg 17.8%

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

0.18Best match rating · 13–2 · ancient, 21 Apr →
50%Best headshot accuracy · 3–3 · dust2, 20 Aug →
469msFastest reaction time · 13–11 · anubis, 30 Sept →
13–0Biggest win · mirage, 6 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
11–10In matches decided by ≤2 rounds
12Overtime games

Map breakdown

cacheBest map · 63% over 8infernoWeakest map · 40% over 5
MapGradePlayedRecordWin rateAvg rating
mirageC2611–1542%-0.01
dust2B157–847%-0.01
nukeB147–750%-0.01
anubisB137–654%0.00
ancientA95–456%0.01
cacheA85–363%-0.02
overpassA74–357%-0.01
infernoC52–340%-0.03
vertigo—30–30%-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

21,647Lifetime kills
0.64K/D
1,025Matches
41.4%Match win rate
58.3%Headshot % · Top 10% of Purple band
0.3%Shot accuracy
2,320MVPs
1,697Hours (in match)
751Bombs planted
190Bombs defused

Most-used weapons

Lifetime map wins

1,686nuke
891dust2
619vertigo
544inferno
236train
67office
8cbble

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

Faceit stats

Combat

20Matches
50%Win rate
0.77Avg K/D
63.6ADR
50%Headshot %

Clutches & streaks

55%1v1 clutch win
8%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage933%0.7213.0
Dust2560%0.7812.4
Nuke2100%1.1516.0
Overpass1100%1.1110.0
Inferno1100%0.7414.0
Ancient10%0.6012.0
Cache10%0.315.0

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.

17.2%Headshot accuracy
33.5%Accuracy (enemy spotted)
37.0%Spray accuracy
77.1%Counter-strafing
11.5°Preaim
606msReaction time
42.5%T opening success
38.6%CT opening success
0.37Enemies flashed / flash
2.2%Flash assists
3.71HE damage / grenade
4.94Flashes / 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 0.3671 — 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 38.6361% — 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.

40% 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
mirage9–13-0.0714%4 Nov →
overpass12–12-0.0016%3 Nov →
anubis13–110.0317%30 Sept →
mirage3–13-0.0016%30 Sept →
mirage8–13-0.0222%23 Sept →
anubis11–13-0.0312%23 Sept →
nuke7–13-0.0640%22 Sept →
dust213–100.0413%22 Sept →
nuke13–160.0117%19 Sept →
anubis13–110.0015%4 Sept →
mirage13–40.0316%3 Sept →
dust24–13-0.079%3 Sept →
mirage2–130.0617%3 Sept →
nuke7–130.0218%2 Sept →
ancient6–13-0.0320%2 Sept →
dust213–70.0423%2 Sept →
mirage13–1-0.0018%2 Sept →
anubis10–13-0.0118%1 Sept →
ancient13–110.0210%1 Sept →
dust213–6-0.0220%1 Sept →
mirage5–13-0.0419%1 Sept →
dust22–130.0010%31 Aug →
anubis14–16-0.0217%31 Aug →
mirage2–13-0.0522%31 Aug →
cache13–16-0.068%31 Aug →
dust216–14-0.0421%30 Aug →
nuke13–9-0.0223%30 Aug →
mirage8–13-0.036%30 Aug →
mirage3–13-0.0124%30 Aug →
mirage13–10-0.0019%27 Aug →
mirage14–160.0231%27 Aug →
nuke15–150.0113%27 Aug →
ancient13–110.0423%27 Aug →
dust212–16-0.0224%27 Aug →
vertigo7–13-0.0616%27 Aug →
anubis16–13-0.0524%27 Aug →
nuke16–13-0.0515%26 Aug →
ancient6–13-0.0727%26 Aug →
cache13–8-0.036%26 Aug →
nuke13–9-0.0324%26 Aug →
inferno11–13-0.0010%26 Aug →
mirage7–13-0.0414%20 Aug →
dust23–3-0.0350%20 Aug →
anubis13–9-0.0731%20 Aug →
ancient6–13-0.0316%20 Aug →
dust213–60.0124%20 Aug →
dust29–130.0225%20 Aug →
mirage13–5-0.0117%20 Aug →
mirage13–11-0.0122%16 Aug →
nuke8–13-0.0531%16 Aug →
dust29–13-0.0213%16 Aug →
mirage13–40.0821%16 Aug →
mirage13–00.0918%6 Aug →
anubis9–13-0.0012%5 Aug →
mirage9–13-0.0416%5 Aug →
mirage13–9-0.0317%17 Jul →
dust211–13-0.0116%3 Jul →
mirage16–14-0.0718%2 Jul →
overpass13–10.0023%2 Jul →
dust213–7-0.0112%2 Jul →
mirage13–60.0119%2 Jul →
nuke13–70.0415%1 Jul →
cache3–13-0.0522%1 Jul →
dust26–13-0.0411%13 May →
dust213–90.0233%13 May →
overpass13–90.0124%4 May →
cache13–11-0.0434%3 May →
nuke12–16-0.0516%3 May →
overpass7–13-0.037%3 May →
overpass13–11-0.0019%2 May →
mirage11–13-0.0415%2 May →
nuke13–60.0421%2 May →
anubis11–130.0414%2 May →
anubis13–40.0118%2 May →
nuke13–40.0115%2 May →
mirage16–14-0.058%1 May →
mirage11–13-0.0213%30 Apr →
cache13–4-0.049%30 Apr →
cache13–8-0.0213%30 Apr →
cache8–130.0613%29 Apr →
cache13–90.0414%29 Apr →
ancient13–9-0.0611%23 Apr →
overpass13–60.0113%23 Apr →
anubis13–10.1420%23 Apr →
anubis7–130.0019%23 Apr →
ancient13–80.0112%21 Apr →
ancient13–20.1816%21 Apr →
mirage9–13-0.0214%21 Apr →
inferno3–13-0.1013%21 Apr →
mirage11–13-0.0319%20 Apr →
anubis13–11-0.016%20 Apr →
inferno13–80.0025%20 Apr →
ancient12–120.0314%19 Apr →
nuke6–13-0.047%19 Apr →
overpass6–13-0.098%19 Apr →
vertigo5–130.029%18 Apr →
inferno13–50.0125%18 Apr →
inferno5–13-0.0514%18 Apr →
vertigo8–13-0.065%18 Apr →
nuke13–60.0017%18 Apr →

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 →

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