Big Poppa

Big Poppa — CS2 Stats

US76561199825036371[U:1:1864770643]Steam profile ↗✓ No bans

283Tracked matches64%Win rate2025Tracked since
CSDB Rating6.0 SolidAll-Rounder
Premier CS Rating18,874Top 50% of 215,386 CSDB-tracked playersPurple band · top ~13% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Sep 2026 (72 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 283 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 18,874 +4,480 6 Dec – 3 Sept · 19 days played
10,81818,874peak 18,8746 Dec3 Sept
18,874Peak Premier in tracked matches
26Days played since 2025-11-30

Premier CS Rating

  • At peak — 18,874
  • 0 over 30 days · steady
  • +4,502 over 90 days
  • Next: Pink band at 20,000 — 1,126 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-03
  • Blue band first seen 2026-09-03

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

Share this profile

CSDB.GGBig PoppaPREMIER18,874 · Purple bandcsdb.gg/stats

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Performance scores

Aim62
Positioning61
Utility56

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateWTWWLLWLWW

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · −3.7pp headshot accuracy · −8ms 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

  • 3–1–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 569ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 13%
  • Avg reaction 590ms

Last 20

  • 11–7–2 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 594ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim6.2
Utility5.6
Positioning6.1
Opening Duels4.8

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

jL

Plays most like jL 86% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; 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

Reaction time. 585ms 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

Aim6.2
Positioning6.1
Utility5.6
Mechanics4.9
Opening Duels4.1
Win Impact9.8

Composite 6.0/10 (Solid), 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 rating0.02+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.02
Reaction time587ms−40ms
first ⅓ avg 627ms → last ⅓ avg 587ms
Headshot accuracy16.3%+3.8%
first ⅓ avg 12.5% → last ⅓ avg 16.3%

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 · 13–8 · inferno, 20 Dec →
41%Best headshot accuracy · 13–3 · ancient, 18 Jun →
438msFastest reaction time · 8–13 · anubis, 30 May →
13–1Biggest win · inferno, 30 May →

Across the last 100 tracked matches.

Highlights

10Longest win streak
8–7In matches decided by ≤2 rounds
9Overtime games

Map breakdown

anubisBest map · 75% over 8dust2Weakest map · 20% over 15
MapGradePlayedRecordWin rateAvg rating
infernoA2314–961%0.02
nukeA1811–761%0.02
dust2D153–1220%-0.01
ancientA127–558%-0.01
cacheB84–450%0.03
anubisS86–275%0.01
overpassD72–529%-0.04
mirage—44–0100%-0.00
train—20–20%-0.03
boulder—10–10%-0.08
eldorado—11–0100%0.09
rooftop—10–10%-0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 15). 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.

16.7%Headshot accuracy
35.4%Accuracy (enemy spotted)
38.2%Spray accuracy
72.0%Counter-strafing
10.6°Preaim
585msReaction time
45.4%T opening success
47.8%CT opening success
0.52Enemies flashed / flash
4.6%Flash assists
9.12HE damage / grenade
9.00Flashes / match

Recommended for you

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.

20% win rate across 15 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
cache13–100.0115%1 Aug →
inferno15–15-0.0119%25 Jul →
nuke13–110.034%25 Jul →
nuke13–6-0.0012%25 Jul →
cache10–130.0225%25 Jul →
boulder4–13-0.0813%24 Jul →
anubis13–80.0612%24 Jul →
dust23–13-0.019%24 Jul →
nuke13–80.0915%24 Jul →
eldorado9–30.096%24 Jul →
inferno3–9-0.210%24 Jul →
dust27–130.0417%24 Jul →
inferno11–13-0.0523%19 Jul →
nuke13–8-0.0026%18 Jul →
cache13–50.1419%18 Jul →
nuke2–13-0.0831%18 Jul →
cache13–90.0113%18 Jul →
inferno13–100.0212%18 Jul →
cache15–15-0.0312%18 Jul →
nuke13–60.1314%17 Jul →
anubis13–30.1218%17 Jul →
inferno13–80.0222%17 Jul →
inferno8–130.0410%17 Jul →
cache11–13-0.0223%17 Jul →
cache13–30.1211%17 Jul →
dust29–13-0.0213%17 Jul →
inferno13–4-0.0215%17 Jul →
anubis13–4-0.0111%17 Jul →
inferno13–60.146%19 Jun →
dust210–130.0214%18 Jun →
anubis13–11-0.0229%18 Jun →
ancient13–3-0.0141%18 Jun →
inferno13–100.0127%18 Jun →
ancient13–3-0.0114%18 Jun →
dust216–130.0315%15 Jun →
ancient13–90.0114%15 Jun →
ancient16–140.0310%15 Jun →
nuke13–11-0.0117%15 Jun →
inferno13–40.0419%15 Jun →
nuke13–100.027%15 Jun →
dust26–13-0.0513%14 Jun →
anubis15–15-0.0018%11 Jun →
mirage13–50.0115%11 Jun →
inferno9–130.0424%11 Jun →
dust211–13-0.0119%11 Jun →
ancient9–13-0.047%11 Jun →
nuke10–130.0619%11 Jun →
dust213–70.0212%11 Jun →
mirage13–70.0517%4 Jun →
dust211–13-0.0612%4 Jun →
inferno1–80.0925%4 Jun →
inferno13–90.0819%4 Jun →
dust29–13-0.0611%4 Jun →
dust211–13-0.0511%4 Jun →
cache10–13-0.017%30 May →
mirage13–11-0.0216%30 May →
anubis13–11-0.0312%30 May →
anubis8–13-0.0511%30 May →
inferno13–10.1314%30 May →
ancient9–130.0614%3 Apr →
anubis13–4-0.0211%3 Apr →
mirage13–8-0.0617%13 Jan →
ancient16–14-0.097%13 Jan →
inferno13–20.0214%13 Jan →
overpass13–60.044%13 Jan →
dust28–13-0.0318%11 Jan →
train4–13-0.0511%11 Jan →
train15–15-0.0119%11 Jan →
inferno11–13-0.0124%10 Jan →
overpass3–13-0.0811%10 Jan →
ancient13–9-0.0313%10 Jan →
overpass13–6-0.0414%10 Jan →
ancient0–13-0.0317%9 Jan →
overpass6–13-0.0421%9 Jan →
dust214–16-0.0112%28 Dec →
inferno8–13-0.0516%28 Dec →
ancient4–13-0.0013%28 Dec →
nuke6–130.0119%28 Dec →
overpass2–13-0.0921%28 Dec →
nuke13–10.107%21 Dec →
inferno13–10-0.0313%20 Dec →
overpass6–13-0.079%20 Dec →
nuke13–40.0515%20 Dec →
inferno13–30.0713%20 Dec →
nuke3–13-0.0312%20 Dec →
ancient1–13-0.049%20 Dec →
nuke4–13-0.0213%20 Dec →
inferno13–80.168%20 Dec →
nuke13–80.006%19 Dec →
dust210–13-0.0314%14 Dec →
inferno8–130.036%14 Dec →
nuke5–13-0.098%14 Dec →
dust213–50.0116%14 Dec →
overpass10–130.007%7 Dec →
nuke12–16-0.034%6 Dec →
nuke13–20.066%6 Dec →
ancient13–70.009%6 Dec →
inferno13–50.048%6 Dec →
rooftop5–9-0.0415%30 Nov →
inferno9–70.0217%30 Nov →

Match data via Leetify.

Recent teammates

Milestones

100 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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