Baggemus

Baggemus — CS2 Stats

76561198088804618[U:1:128538890]Steam profile ↗✓ No bans

723Tracked matches48%Win rate2023Tracked since
869Hours in CS15Hrs last 2 wks
CSDB Rating5.0 DevelopingPositional Player
Premier CS Rating14,402Blue band · top ~31.6% of ranked players (population est.)
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (4 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: 14,402 +881 17 Apr – 30 Oct · 14 days played
12,67414,720peak 14,72017 Apr30 Oct
14,720Peak Premier in tracked matches
48Days played since 2026-04-17

Premier CS Rating

  • 318 below peak (14,720)
  • Next: Purple band at 15,000 — 598 to go
  • Reached: Blue band · Light Blue band

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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate42.7%42.0%44.4%1.7% short
Shot accuracy8.4%9.6%11.9%3.4% short
Kill/death ratio0.800.981.030.23 short
Match win rate35.7%43.8%45.2%9.5% short

This profile sits below the typical Purple band player on every metric we can compare.

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

Share this profile

CSDB.GGBaggemusPREMIER14,402 · Blue bandcsdb.gg/stats

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Performance scores

Aim73
Positioning59
Utility18

0–100 skill scores via Leetify.

Recent form

STEADY43–49–8Last 10043%Win rateWWLWWLLLLT

Last 10 vs previous 10: +10pp win rate · −0.06 avg rating · −6.0pp headshot accuracy · −58ms reaction

Win rate +10pp 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

  • 4–1 · 80% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 545ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 10%
  • Avg reaction 484ms

Last 20

  • 7–9–4 · 35% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 513ms

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 (+2.7 against its own average).

Aim7.3
Utility1.8
Positioning5.9
Opening Duels1.9

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

sh1ro

Plays most like sh1ro 79% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower opening-duel success; 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.

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

Aim7.3
Positioning5.9
Utility1.8
Mechanics6.7
Opening Duels2.3
Win Impact4.4

Composite 5.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time538ms−59ms
first ⅓ avg 597ms → last ⅓ avg 538ms
Headshot accuracy13.9%−4.2%
first ⅓ avg 18.0% → last ⅓ avg 13.9%

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

0.26Best match rating · 9–1 · inferno, 21 Oct →
39%Best headshot accuracy · 9–4 · inferno, 16 Oct →
352msFastest reaction time · 2–9 · inferno, 29 Sept →
13–2Biggest win · anubis, 25 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
11–3In matches decided by ≤2 rounds
5Overtime games

Map breakdown

anubisBest map · 75% over 8dust2Weakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
infernoC4917–3235%-0.04
ancientB158–753%-0.00
nukeS96–367%0.02
cacheA95–456%0.00
anubisS86–275%-0.01
dust2D50–50%-0.06
mirage—40–40%-0.04
vertigo—11–0100%0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

21,219Lifetime kills
0.80K/D
1,487Matches
35.7%Match win rate
42.7%Headshot % · Top 50% of Blue band
8.4%Shot accuracy
2,095MVPs
418Hours (in match)
1,031Bombs planted
127Bombs defused

Most-used weapons

Lifetime map wins

1,833inferno
1,530nuke
708vertigo
546dust2
96train
70lake
68safehouse
33cbble

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

Faceit stats

Combat

5Matches
60%Win rate
0.39Avg K/D
—ADR
62%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
2Longest win streak

Recent Faceit resultsLWLWW

MapMatchesWin rateAvg K/DAvg kills
Anubis2100%0.406.5
Ancient10%0.385.0
Nuke1100%0.385.0
Mirage10%0.417.0

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.

14.7%Headshot accuracy
34.1%Accuracy (enemy spotted)
36.8%Spray accuracy
80.0%Counter-strafing
8.3°Preaim
546msReaction time
43.2%T opening success
35.1%CT opening success
0.31Enemies flashed / flash
1.9%Flash assists
5.90HE damage / grenade
1.68Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.7081% — below the 15% mark we flag

    Aim Training →
  2. 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 0.3099 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

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

    CT opening duels 35.1177% — below the 40% mark we flag

Spend your practice time on Dust 2

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.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–11-0.007%30 Oct →
inferno9–6-0.035%30 Oct →
inferno5–9-0.0619%30 Oct →
ancient13–9-0.0312%29 Oct →
cache13–110.0110%29 Oct →
inferno0–2-0.100%29 Oct →
nuke10–13-0.0616%29 Oct →
inferno2–9-0.2214%29 Oct →
inferno1–9-0.270%29 Oct →
inferno8–8-0.0316%28 Oct →
inferno8–8-0.0216%28 Oct →
cache13–90.0118%28 Oct →
inferno9–5-0.0913%28 Oct →
ancient13–11-0.0015%27 Oct →
inferno6–90.1314%27 Oct →
inferno5–9-0.0720%27 Oct →
dust21–13-0.0526%27 Oct →
anubis2–13-0.0314%27 Oct →
dust215–15-0.0610%27 Oct →
inferno8–8-0.0015%27 Oct →
inferno5–90.0527%26 Oct →
inferno3–9-0.125%24 Oct →
ancient13–5-0.0513%22 Oct →
dust25–13-0.077%22 Oct →
dust21–13-0.0838%22 Oct →
nuke16–120.0919%21 Oct →
ancient13–7-0.019%21 Oct →
inferno9–10.268%21 Oct →
anubis10–13-0.0312%20 Oct →
ancient10–13-0.0121%20 Oct →
inferno5–9-0.1413%20 Oct →
inferno9–00.2215%19 Oct →
inferno9–70.059%19 Oct →
inferno9–50.0115%19 Oct →
inferno9–4-0.0539%16 Oct →
dust27–13-0.0510%14 Oct →
inferno5–9-0.047%12 Oct →
inferno2–9-0.1518%29 Sept →
inferno4–9-0.1510%26 Sept →
mirage2–13-0.0721%25 Sept →
anubis13–2-0.0227%25 Sept →
cache16–130.0013%25 Sept →
cache11–130.0114%25 Sept →
nuke4–50.0219%25 Sept →
ancient6–13-0.0513%25 Sept →
inferno5–9-0.1621%25 Sept →
ancient13–110.0013%17 Sept →
nuke8–2-0.013%17 Sept →
inferno9–6-0.2230%17 Sept →
nuke10–130.0314%14 Sept →
ancient5–130.0116%14 Sept →
inferno5–9-0.1113%14 Sept →
ancient7–13-0.0014%8 Sept →
inferno6–9-0.0611%6 Sept →
anubis13–100.0316%1 Sept →
inferno4–9-0.0816%27 Aug →
inferno13–80.025%27 Aug →
inferno1–9-0.2025%26 Aug →
inferno1–9-0.2131%26 Aug →
mirage4–13-0.0417%25 Aug →
inferno5–90.0119%25 Aug →
nuke8–13-0.0121%22 Aug →
inferno8–80.019%22 Aug →
cache13–7-0.0211%22 Aug →
inferno5–9-0.130%21 Aug →
ancient15–15-0.0114%20 Aug →
inferno9–40.0816%19 Aug →
inferno9–20.1129%19 Aug →
ancient5–13-0.038%18 Aug →
inferno2–9-0.0525%14 Aug →
inferno9–7-0.0925%6 Aug →
cache9–13-0.0034%8 Jul →
cache4–00.105%8 Jul →
vertigo13–100.0313%8 Jul →
inferno6–130.0219%8 Jul →
inferno9–40.0932%7 Jul →
nuke13–70.0814%5 Jul →
ancient13–30.1110%5 Jul →
anubis13–9-0.0122%5 Jul →
mirage4–13-0.0522%30 Jun →
nuke13–110.0228%30 Jun →
inferno3–9-0.0928%30 Jun →
inferno4–9-0.226%30 Jun →
ancient15–15-0.0015%10 Jun →
mirage10–130.0114%10 Jun →
ancient13–110.0215%3 Jun →
inferno9–7-0.0224%1 Jun →
inferno9–30.1311%24 May →
inferno7–9-0.1024%19 May →
inferno8–80.0824%18 May →
inferno3–9-0.0915%18 May →
inferno9–50.0221%17 May →
inferno9–70.0111%15 May →
anubis13–70.045%6 May →
inferno2–13-0.1114%5 May →
cache10–13-0.0328%3 May →
cache6–13-0.0613%3 May →
anubis13–3-0.0214%18 Apr →
ancient13–4-0.0113%18 Apr →
anubis13–8-0.0815%17 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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