₿Money Montana Papud₿

₿Money Montana Papud₿ — CS2 Stats

EE76561199199792781[U:1:1239527053]Steam profile ↗✓ No bans

1,664Tracked matches44%Win rate2021Tracked since
4,570Hours in CS21Hrs last 2 wks
CSDB Rating6.3 SolidPositional Player
Premier CS Rating19,875Top 50% of 209,427 CSDB-tracked playersPurple band · top ~9% of ranked players (population est.)
CSDB Leaderboard#87383 of 256935 tracked
FaceitLevel 6Top 54.0% of ranked FACEIT players
WingmanMaster Guardian Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Oct 2026 (5 days ago). Ranks are recorded once per day this page is viewed.

+366Premier CS Rating · 19,509 → 19,875

Rating over time

Premier CS Rating: 19,875 +1,621 25 Aug – 23 Oct · 30 days played
17,97421,000peak 21,00025 Aug23 Oct
21,000Peak Premier in tracked matches
41Days played since 2026-08-25

Premier CS Rating

  • 1,125 below peak (21,000)
  • +899 over 30 days · improving
  • Next: Pink band at 20,000 — 125 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-09
  • Purple band first seen 2026-09-09

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 Level 6 among CSDB-tracked players (n=13,185), 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 6 medianLevel 7 medianvs Level 7
Headshot rate52.9%44.8%45.7%above
Shot accuracy5.3%12.4%12.7%7.4% short
Kill/death ratio0.941.031.050.11 short
Match win rate45.8%45.2%45.7%meets

This profile matches the typical Level 7 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 7 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GG₿Money Montana Papud₿FACEITLevel 6STANDINGTop 54.0% of rankedPREMIER19,875 · Purple bandcsdb.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
Positioning60
Utility40

0–100 skill scores via Leetify.

Recent form

STEADY48–46–6Last 10048%Win rateWLTLWWWWLL

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating · +0.4pp headshot accuracy · −52ms 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 30%
  • Avg reaction 552ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 33%
  • Avg reaction 538ms

Last 20

  • 8–9–3 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 33%
  • Avg reaction 564ms

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 (+1.7 against its own average).

Aim8.4
Utility4.0
Positioning6.0
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

ropz

Plays most like ropz 91% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: 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

Strengths

T openings. 68% T opening-duel success — entries that actually open the round.

Areas to improve

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

CT openings. Opening success drops from 68% on T to 45% on CT — first contacts on the defending side are being lost.

Reaction time. 595ms 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
Positioning6.0
Utility4.0
Mechanics6.8
Opening Duels6.6
Win Impact3.1

Composite 6.3/10 (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 rating-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time599ms+5ms
first ⅓ avg 594ms → last ⅓ avg 599ms
Headshot accuracy31.1%−1.8%
first ⅓ avg 32.9% → last ⅓ avg 31.1%

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

0.12Best match rating · 13–6 · dust2, 4 Oct →
75%Best headshot accuracy · 13–11 · dust2, 8 Oct →
352msFastest reaction time · 0–13 · vertigo, 29 Sept →
13–1Biggest win · nuke, 31 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
7–6In matches decided by ≤2 rounds
7Overtime games

Map breakdown

vertigoBest map · 60% over 5cacheWeakest map · 18% over 11
MapGradePlayedRecordWin rateAvg rating
mirageA2514–1156%-0.02
dust2B1910–953%0.01
infernoC125–742%0.01
cacheD112–918%-0.02
ancientA95–456%-0.03
nukeC94–544%0.02
anubisC52–340%-0.01
vertigoA53–260%-0.03
office—31–233%-0.00
train—11–0100%0.04
italy—11–0100%0.04

Across the last 100 tracked matches.

Lifetime stats

91,282Lifetime kills
0.94K/D
5,671Matches
45.8%Match win rate · Top 50% of Level 6 players
52.9%Headshot % · Top 25% of Level 6 players
5.3%Shot accuracy
13,176MVPs
3,051Hours (in match)
3,950Bombs planted
1,038Bombs defused

Most-used weapons

AK-4727,683
AWP14,150
SSG 082,413
FAMAS1,609
SG 5531,135

Lifetime map wins

7,594dust2
6,628inferno
6,414nuke
3,417vertigo
1,141train
759office
216cbble
200lake

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

Faceit stats

Combat

167Matches
51%Win rate
0.91Avg K/D
78.7ADR
54%Headshot %

Clutches & streaks

38%1v1 clutch win
14%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage5046%0.9215.3
Dust22658%0.9415.8
Inferno2458%0.8214.7
Anubis1844%0.9214.0
Nuke1856%1.0316.9
Ancient1747%0.9516.8
Overpass683%0.7913.5
Cache50%0.7513.4

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.

29.4%Headshot accuracy
33.6%Accuracy (enemy spotted)
37.6%Spray accuracy
80.4%Counter-strafing
8.4°Preaim
595msReaction time
67.8%T opening success
45.0%CT opening success
0.55Enemies flashed / flash
7.1%Flash assists
6.12HE damage / grenade
5.53Flashes / match

Recommended for you

Spend your practice time on Cache

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

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
cache13–60.0838%23 Oct →
ancient5–13-0.0827%21 Oct →
cache15–150.0418%18 Oct →
ancient3–13-0.0335%17 Oct →
dust213–10-0.0034%17 Oct →
ancient13–11-0.0443%17 Oct →
dust213–80.0840%17 Oct →
dust213–4-0.0037%15 Oct →
dust210–13-0.0425%13 Oct →
office7–13-0.0638%13 Oct →
dust215–15-0.0324%11 Oct →
anubis5–13-0.0126%11 Oct →
cache9–13-0.0640%11 Oct →
office12–12-0.0135%11 Oct →
dust27–13-0.0822%11 Oct →
cache2–13-0.1319%11 Oct →
inferno11–130.0523%10 Oct →
vertigo13–90.0332%10 Oct →
dust213–11-0.0575%8 Oct →
ancient13–8-0.0035%7 Oct →
nuke4–13-0.0236%4 Oct →
ancient5–13-0.0715%4 Oct →
mirage13–9-0.0721%4 Oct →
mirage13–10-0.0319%4 Oct →
dust213–60.1230%4 Oct →
dust27–130.0024%3 Oct →
vertigo9–13-0.0135%3 Oct →
dust26–13-0.0421%3 Oct →
mirage14–16-0.0516%3 Oct →
inferno13–50.0427%3 Oct →
dust25–130.0828%2 Oct →
anubis13–70.0348%2 Oct →
mirage13–20.0339%1 Oct →
mirage13–80.0029%30 Sept →
nuke13–6-0.0432%30 Sept →
cache10–130.0439%30 Sept →
dust213–70.0027%29 Sept →
mirage13–90.0156%29 Sept →
vertigo0–13-0.050%29 Sept →
mirage11–13-0.0328%29 Sept →
office13–40.0644%29 Sept →
cache10–13-0.0142%27 Sept →
mirage13–100.0543%27 Sept →
dust27–130.0153%27 Sept →
dust28–130.0142%27 Sept →
anubis5–130.0640%26 Sept →
dust213–90.0622%26 Sept →
cache13–4-0.0021%26 Sept →
mirage5–13-0.0820%26 Sept →
train13–100.0441%26 Sept →
ancient6–1-0.0460%26 Sept →
mirage13–4-0.0745%26 Sept →
mirage13–80.0341%25 Sept →
cache6–13-0.0330%25 Sept →
nuke6–130.0117%25 Sept →
mirage13–10-0.0324%24 Sept →
mirage13–8-0.0133%23 Sept →
inferno16–140.0526%23 Sept →
ancient3–13-0.0532%22 Sept →
mirage2–80.0240%22 Sept →
cache2–13-0.1126%22 Sept →
nuke13–70.1230%18 Sept →
mirage13–8-0.0114%17 Sept →
inferno12–120.1221%17 Sept →
cache10–130.0024%17 Sept →
nuke13–110.0232%16 Sept →
inferno15–150.0121%15 Sept →
mirage6–13-0.0442%15 Sept →
ancient13–9-0.0139%13 Sept →
inferno3–13-0.0830%12 Sept →
dust211–130.0338%12 Sept →
italy13–70.0448%12 Sept →
vertigo13–11-0.1347%11 Sept →
cache7–13-0.0419%10 Sept →
anubis9–13-0.0521%9 Sept →
ancient13–100.0349%8 Sept →
inferno13–6-0.0342%8 Sept →
mirage4–13-0.0430%6 Sept →
dust213–8-0.0026%6 Sept →
inferno13–9-0.0243%5 Sept →
mirage13–10-0.0541%5 Sept →
vertigo6–4-0.0050%2 Sept →
dust213–110.0343%2 Sept →
nuke13–10.0941%31 Aug →
nuke6–90.0433%31 Aug →
nuke10–13-0.0118%31 Aug →
inferno9–50.0814%30 Aug →
inferno7–90.0338%30 Aug →
mirage13–90.0239%29 Aug →
inferno15–15-0.0028%29 Aug →
mirage0–13-0.0338%27 Aug →
mirage5–13-0.0315%26 Aug →
mirage9–13-0.0227%26 Aug →
mirage13–4-0.0142%26 Aug →
nuke14–16-0.0214%25 Aug →
inferno7–13-0.0722%25 Aug →
mirage5–13-0.0227%25 Aug →
dust213–80.0422%25 Aug →
mirage10–13-0.0530%25 Aug →
anubis13–10-0.0833%25 Aug →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.