Baggis

Baggis — CS2 Stats

SE76561197961481770[U:1:1216042]Steam profile ↗✓ No bans

4,527Tracked matches57%Win rate2022Tracked since
CSDB Rating3.2 LearningSupport
Premier CS Rating14,142Blue band · top ~32.9% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Oct 2026 (yesterday). 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: 14,142 +2,547 11 Sept – 16 Oct · 19 days played
10,00014,999peak 14,99911 Sept16 Oct
14,999Peak Premier in tracked matches
18Days played since 2026-09-11

Premier CS Rating

  • 857 below peak (14,999)
  • +2,547 over 30 days · improving
  • Next: Purple band at 15,000 — 858 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-11
  • Light Blue band first seen 2026-09-11

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

Share this profile

CSDB.GGBaggisPREMIER14,142 · Blue bandcsdb.gg/stats

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Performance scores

Aim21
Positioning39
Utility58

0–100 skill scores via Leetify.

Recent form

HOT49–49–2Last 10049%Win rateLWLWWWLWWW

Last 10 vs previous 10: +20pp win rate · +0.05 avg rating · +2.3pp headshot accuracy · +16ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 10%
  • Avg reaction 658ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 10%
  • Avg reaction 656ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 9%
  • Avg reaction 649ms

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 (+2.4 against its own average).

Aim2.1
Utility5.8
Positioning3.9
Opening Duels0.5

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

ZywOo

Plays most like ZywOo 57% 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

Reaction time. 647ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 58% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim2.1
Positioning3.9
Utility5.8
Mechanics1.9
Opening Duels1.1
Win Impact7.2

Composite 3.2/10 (Learning), 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-0.01+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.01
Reaction time649ms−6ms
first ⅓ avg 655ms → last ⅓ avg 649ms
Headshot accuracy9.1%−2.4%
first ⅓ avg 11.5% → last ⅓ avg 9.1%

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

0.16Best match rating · 13–0 · mirage, 16 Oct →
25%Best headshot accuracy · 4–0 · inferno, 29 Sept →
398msFastest reaction time · 8–0 · inferno, 29 Sept →
13–0Biggest win · mirage, 16 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
4–10In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 67% over 12dust2Weakest map · 31% over 13
MapGradePlayedRecordWin rateAvg rating
infernoB2512–1348%-0.01
cacheB179–853%-0.03
dust2D134–931%-0.02
anubisS128–467%0.01
nukeB126–650%-0.02
mirageB105–550%-0.01
ancientB105–550%-0.01
tuscan_d—10–10%0.00

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

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

9.2%Headshot accuracy
33.1%Accuracy (enemy spotted)
35.1%Spray accuracy
58.4%Counter-strafing
14.0°Preaim
647msReaction time
30.7%T opening success
38.4%CT opening success
0.46Enemies flashed / flash
5.0%Flash assists
7.60HE damage / grenade
10.58Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.9768° — above the 12° mark we flag

    Aim Training →
  2. 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 9.1848% — below the 15% mark we flag

    Aim Training →
  3. 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 0.4621 — below the 0.5 mark we flag

    Grenade Lineups →
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.

31% win rate across 13 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
inferno14–160.0111%16 Oct →
anubis13–7-0.0214%16 Oct →
dust214–16-0.0016%16 Oct →
mirage13–00.165%16 Oct →
ancient13–80.025%16 Oct →
nuke13–70.025%16 Oct →
dust28–130.0112%16 Oct →
anubis13–40.0612%15 Oct →
cache13–6-0.088%15 Oct →
nuke13–10.0912%15 Oct →
inferno13–16-0.014%15 Oct →
nuke13–9-0.029%15 Oct →
inferno11–130.0111%14 Oct →
mirage13–8-0.016%14 Oct →
nuke13–10.015%14 Oct →
inferno13–60.048%13 Oct →
cache6–13-0.0313%13 Oct →
dust23–13-0.0413%13 Oct →
cache6–13-0.065%13 Oct →
inferno13–3-0.065%13 Oct →
anubis2–13-0.066%13 Oct →
dust216–14-0.066%11 Oct →
inferno13–1-0.043%11 Oct →
mirage8–13-0.064%11 Oct →
inferno11–13-0.0517%11 Oct →
nuke9–13-0.0416%11 Oct →
cache13–6-0.0610%11 Oct →
ancient10–13-0.057%11 Oct →
inferno13–4-0.0210%10 Oct →
cache13–10.0012%10 Oct →
inferno15–150.0119%10 Oct →
cache13–11-0.017%10 Oct →
anubis13–20.114%10 Oct →
cache16–120.019%10 Oct →
anubis13–3-0.039%10 Oct →
mirage13–40.0113%10 Oct →
cache4–13-0.117%9 Oct →
cache13–60.029%9 Oct →
inferno11–13-0.049%9 Oct →
dust210–13-0.038%9 Oct →
anubis13–20.116%9 Oct →
cache11–13-0.015%9 Oct →
ancient13–100.119%9 Oct →
inferno13–70.016%8 Oct →
ancient13–10-0.034%8 Oct →
anubis16–13-0.035%8 Oct →
cache4–13-0.056%8 Oct →
nuke13–9-0.066%8 Oct →
nuke13–6-0.069%5 Oct →
ancient9–13-0.059%5 Oct →
inferno13–6-0.0114%5 Oct →
ancient13–60.0111%5 Oct →
tuscan_d2–130.002%4 Oct →
nuke10–13-0.0810%4 Oct →
cache9–13-0.0511%4 Oct →
inferno10–13-0.019%4 Oct →
inferno3–13-0.065%3 Oct →
inferno9–13-0.0317%3 Oct →
nuke4–13-0.019%3 Oct →
cache11–13-0.0313%3 Oct →
ancient4–13-0.0224%3 Oct →
anubis8–13-0.057%3 Oct →
dust27–13-0.0810%3 Oct →
inferno7–13-0.009%3 Oct →
cache13–90.067%2 Oct →
nuke3–13-0.0311%2 Oct →
mirage12–160.0622%2 Oct →
dust216–12-0.0211%2 Oct →
cache13–9-0.049%2 Oct →
dust210–13-0.034%1 Oct →
nuke5–13-0.0218%30 Sept →
ancient13–30.0011%30 Sept →
dust211–13-0.0516%30 Sept →
ancient5–13-0.077%29 Sept →
nuke9–13-0.0713%29 Sept →
anubis8–130.0110%29 Sept →
anubis13–9-0.018%29 Sept →
mirage15–15-0.068%29 Sept →
inferno8–0-0.0113%29 Sept →
anubis13–40.0314%29 Sept →
inferno4–0-0.0525%29 Sept →
dust211–130.0413%27 Sept →
inferno13–90.0213%27 Sept →
inferno10–13-0.0114%27 Sept →
cache6–13-0.0212%27 Sept →
mirage8–13-0.064%27 Sept →
inferno9–13-0.0719%27 Sept →
anubis11–130.058%27 Sept →
ancient8–13-0.0415%27 Sept →
mirage16–12-0.0311%26 Sept →
dust213–40.017%26 Sept →
inferno3–13-0.077%26 Sept →
mirage16–14-0.0514%26 Sept →
inferno13–10-0.0121%26 Sept →
mirage7–13-0.0515%26 Sept →
inferno13–40.092%25 Sept →
dust213–10-0.029%25 Sept →
dust27–130.0116%25 Sept →
cache13–100.035%25 Sept →
inferno13–110.029%25 Sept →

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 →

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