jaegermeister

jaegermeister — CS2 Stats

76561197990900991[U:1:30635263]Steam profile ↗✓ No bans

1,622Tracked matches55%Win rate2020Tracked since
8,203Hours in CS
CSDB Rating6.7 SolidPositional Player
FaceitLevel 9 · 2,211 ELOTop 20.7% of ranked FACEIT players
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 9 among CSDB-tracked players (n=15,132), 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 9 medianLevel 10 medianvs Level 10
Headshot rate53.0%48.2%50.9%above
Shot accuracy22.1%13.2%13.7%above
Kill/death ratio0.991.071.090.10 short
Match win rate45.4%46.9%48.4%3.0% short

This profile matches the typical Level 10 player on 2 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGjaegermeisterFACEITLevel 9 · 2,211 ELOSTANDINGTop 20.7% of rankedcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim84
Positioning68
Utility54

0–100 skill scores via Leetify.

Recent form

COLD55–40–5Last 10055%Win rateLLLLLTWWLW

Last 10 vs previous 10: −50pp win rate · −0.02 avg rating · +1.9pp headshot accuracy · +68ms reaction

Win rate down 50pp 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

  • 0–5 · 0% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 28%
  • Avg reaction 603ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 29%
  • Avg reaction 596ms

Last 20

  • 11–8–1 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 28%
  • Avg reaction 562ms

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 (+1.9 against its own average).

Aim8.4
Utility5.4
Positioning6.8
Opening Duels3.7
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

jL

Plays most like jL 95% playstyle similarity

Most alike: utility contribution, positioning 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

Preaim. Mechanical aim is strong but the crosshair sits 10.8° off target when enemies appear — placement, not flicking, is the bigger win available.

Reaction time. 567ms 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

Aim8.4
Positioning6.8
Utility5.4
Mechanics6.9
Opening Duels3.5
Win Impact6.7

Composite 6.7/10 (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 rating0.01+0.01
first ⅓ avg 0.00 → last ⅓ avg 0.01
Reaction time572ms−20ms
first ⅓ avg 592ms → last ⅓ avg 572ms
Headshot accuracy27.0%+7.9%
first ⅓ avg 19.1% → last ⅓ avg 27.0%

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

0.13Best match rating · 3–13 · dust2, 30 Sept →
50%Best headshot accuracy · 13–9 · dust2, 18 Dec →
375msFastest reaction time · 13–8 · dust2, 5 Sept →
13–1Biggest win · nuke, 18 Nov →

Across the last 100 tracked matches.

Highlights

8Longest win streak
L5Current streak
10–10In matches decided by ≤2 rounds
14Overtime games

Map breakdown

nukeBest map · 68% over 19trainWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
dust2C3113–1842%0.00
infernoA2113–862%0.01
nukeS1913–668%0.03
ancientA95–456%0.02
anubisA85–363%0.01
trainD62–433%-0.03
mirage—42–250%-0.01
overpass—11–0100%-0.03
golden—11–0100%0.08

Across the last 100 tracked matches.

Lifetime stats

488,495Lifetime kills
0.99K/D
7,964Matches
45.4%Match win rate
53.0%Headshot % · Top 50% of Level 9 players
22.1%Shot accuracy · Top 1% of Level 9 players
16,537MVPs
8,203Hours (in match)
6,336Bombs planted
1,534Bombs defused

Most-used weapons

AK-47215,067
AWP153,894
P25012,932
FAMAS5,545
SSG 084,092

Lifetime map wins

16,655inferno
15,771dust2
8,399nuke
3,232train
1,371vertigo
812cbble
33dust
24assault

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

Faceit stats

Combat

1,777Matches
51%Win rate
1.16Avg K/D
77.4ADR
48%Headshot %

Clutches & streaks

38%1v1 clutch win
27%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Inferno10052%1.1516.0
Dust28956%1.3117.2
Anubis6338%1.0216.4
Nuke5564%1.2717.3
Ancient4549%1.1717.7
Train743%1.4217.1
Vertigo617%0.8415.5
Mirage425%1.1918.0

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.

26.6%Headshot accuracy
39.1%Accuracy (enemy spotted)
37.3%Spray accuracy
81.1%Counter-strafing
10.8°Preaim
567msReaction time
38.0%T opening success
49.9%CT opening success
0.56Enemies flashed / flash
12.5%Flash assists
7.50HE damage / grenade
12.04Flashes / 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

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 38.0039% — below the 40% mark we flag

Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust27–13-0.0435%3 Oct →
inferno11–130.0326%30 Sept →
dust23–130.1332%30 Sept →
dust27–13-0.0424%13 Sept →
ancient5–13-0.0325%11 Sept →
dust212–12-0.0224%9 Sept →
nuke13–110.0024%8 Sept →
inferno13–40.0335%8 Sept →
dust26–13-0.0333%8 Sept →
nuke16–130.0129%8 Sept →
mirage10–13-0.0127%7 Sept →
inferno16–120.0226%7 Sept →
inferno13–100.0322%7 Sept →
dust213–80.0620%5 Sept →
nuke13–110.0333%5 Sept →
inferno11–100.0839%5 Sept →
dust210–20.0633%5 Sept →
dust213–5-0.0015%19 Dec →
overpass13–11-0.0329%19 Dec →
dust212–160.0222%19 Dec →
nuke13–80.0717%19 Dec →
inferno8–130.0324%19 Dec →
inferno5–130.0023%18 Dec →
dust213–9-0.0050%18 Dec →
ancient13–50.0213%18 Dec →
nuke13–110.0328%18 Dec →
train4–13-0.0919%18 Nov →
nuke13–10.0621%18 Nov →
dust211–130.0222%18 Nov →
dust23–13-0.0424%18 Nov →
anubis13–11-0.0244%14 Nov →
nuke9–13-0.0123%10 Nov →
mirage8–13-0.0328%10 Nov →
nuke13–100.0211%9 Nov →
train13–3-0.0032%9 Nov →
nuke13–100.0541%9 Nov →
ancient13–9-0.0322%3 Nov →
nuke13–100.0425%3 Nov →
inferno13–80.0129%3 Nov →
dust23–13-0.0625%2 Nov →
train12–12-0.0233%1 Nov →
golden13–30.0815%1 Nov →
mirage13–50.0135%1 Nov →
inferno13–7-0.0622%1 Nov →
nuke13–70.0924%1 Nov →
dust213–60.0120%1 Nov →
nuke7–13-0.0236%29 Oct →
inferno3–13-0.0212%29 Oct →
dust213–50.0427%29 Oct →
dust213–100.0228%27 Oct →
nuke13–50.0224%27 Oct →
inferno13–9-0.0533%27 Oct →
train4–13-0.069%27 Mar →
nuke13–80.0623%25 Mar →
nuke16–130.0325%25 Mar →
dust211–130.0714%25 Mar →
ancient13–60.1020%25 Mar →
anubis19–160.0121%25 Mar →
inferno13–60.0618%22 Mar →
inferno16–140.0319%22 Mar →
inferno11–13-0.0027%21 Mar →
inferno15–190.0117%21 Mar →
dust211–130.0424%21 Mar →
ancient15–15-0.0017%17 Mar →
anubis13–90.0324%15 Mar →
train9–130.0018%15 Mar →
ancient13–100.0818%14 Mar →
ancient13–100.0316%14 Mar →
dust29–13-0.0120%14 Mar →
ancient9–130.0220%14 Mar →
anubis9–13-0.0127%14 Mar →
dust213–11-0.0516%13 Mar →
dust215–150.0421%13 Mar →
dust219–160.0019%20 Feb →
dust213–50.0319%20 Feb →
inferno13–50.0816%20 Feb →
anubis7–13-0.037%16 Feb →
nuke11–130.0616%14 Feb →
dust213–80.0739%14 Feb →
dust28–13-0.0425%14 Feb →
inferno13–4-0.0115%14 Feb →
mirage13–9-0.0317%14 Feb →
inferno13–7-0.026%13 Feb →
anubis13–70.0021%10 Feb →
inferno15–150.0321%10 Feb →
train13–10-0.0025%10 Feb →
dust213–10-0.0614%31 Dec →
dust25–13-0.0517%31 Dec →
dust213–110.0126%30 Dec →
inferno13–11-0.0325%30 Dec →
anubis7–130.0927%30 Dec →
inferno11–130.0220%30 Dec →
nuke12–160.0124%30 Dec →
dust28–13-0.0414%30 Dec →
anubis13–70.0013%28 Dec →
dust214–16-0.0117%28 Dec →
ancient2–13-0.0322%28 Dec →
dust25–13-0.067%22 Dec →
nuke14–160.0216%22 Dec →
nuke11–13-0.0425%20 Dec →

Match data via Leetify.

Recent teammates

Milestones

2K ELO1,000 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.