Papa Leo XIV.

Papa Leo XIV. — CS2 Stats

VA76561198168189975[U:1:207924247]Steam profile ↗✓ No bans

895Tracked matches48%Win rate2024Tracked since
1,575Hours in CS8Hrs last 2 wks
CSDB Rating3.8 LearningPositional Player
Premier CS Rating12,547Blue band · top ~41.4% of ranked players (population est.)
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 25 Oct 2026 (6 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: 12,547 -618 21 Jul – 25 Oct · 22 days played
12,02814,535peak 14,53521 Jul25 Oct
14,765Peak Premier in tracked matches
26Days played since 2026-07-09

Premier CS Rating

  • 1,988 below peak (14,535)
  • +519 over 30 days · improving
  • -839 over 90 days
  • Next: Purple band at 15,000 — 2,453 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 rate36.9%42.0%44.4%7.4% short
Shot accuracy0.0%9.6%11.9%11.9% short
Kill/death ratio0.810.981.030.22 short
Match win rate38.2%43.8%45.2%7.0% 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.GGPapa Leo XIV.PREMIER12,547 · Blue bandcsdb.gg/stats

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Performance scores

Aim42
Positioning41
Utility33

0–100 skill scores via Leetify.

Recent form

COLD45–52–3Last 10045%Win rateLLLLLLLWWL

Last 10 vs previous 10: −50pp win rate · −0.02 avg rating · −1.0pp headshot accuracy · −35ms 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 -0.06
  • Avg headshot accuracy 15%
  • Avg reaction 636ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 665ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 683ms

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 (+1.6 against its own average).

Aim4.2
Utility3.3
Positioning4.1
Opening Duels0.2

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

iM

Plays most like iM 83% 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. 674ms 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

Aim4.2
Positioning4.1
Utility3.3
Mechanics6.4
Opening Duels0.3
Win Impact4.4

Composite 3.8/10 (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-0.04−0.01
first ⅓ avg -0.03 → last ⅓ avg -0.04
Reaction time675ms−28ms
first ⅓ avg 704ms → last ⅓ avg 675ms
Headshot accuracy12.9%−2.4%
first ⅓ avg 15.3% → last ⅓ avg 12.9%

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

0.08Best match rating · 13–11 · inferno, 4 Aug →
37%Best headshot accuracy · 5–9 · poseidon, 24 Jul →
484msFastest reaction time · 13–11 · dust2, 1 Sept →
13–2Biggest win · nuke, 10 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L7Current streak
11–9In matches decided by ≤2 rounds
9Overtime games

Map breakdown

anubisBest map · 57% over 7dust2Weakest map · 33% over 15
MapGradePlayedRecordWin rateAvg rating
infernoB209–1145%-0.03
nukeA1810–856%-0.00
dust2D155–1033%-0.04
mirageB136–746%-0.03
ancientA116–555%-0.03
cacheC114–736%-0.04
anubisA74–357%-0.05
vertigo—10–10%-0.07
overpass—11–0100%0.03
shelter—10–10%-0.02
debris—10–10%0.03
poseidon—10–10%-0.07

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

30,249Lifetime kills
0.81K/D
2,121Matches
38.2%Match win rate
36.9%Headshot %
0.0%Shot accuracy
3,213MVPs
723Hours (in match)
2,099Bombs planted
289Bombs defused

Most-used weapons

Lifetime map wins

3,238dust2
2,687inferno
2,347nuke
1,087vertigo
571train
560office
78italy
36ar_shoots

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

Skill profile

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

13.8%Headshot accuracy
31.2%Accuracy (enemy spotted)
31.7%Spray accuracy
78.6%Counter-strafing
10.9°Preaim
674msReaction time
32.3%T opening success
24.2%CT opening success
0.65Enemies flashed / flash
6.4%Flash assists
9.27HE damage / grenade
2.38Flashes / 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 13.7618% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.3834 — below the 4 mark we flag

    Grenade Lineups →
  3. 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 32.2684% — 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.

33% 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
nuke8–13-0.0615%25 Oct →
anubis5–13-0.0711%25 Oct →
inferno10–13-0.0826%25 Oct →
inferno11–13-0.0515%25 Oct →
dust25–13-0.039%19 Oct →
nuke7–13-0.0213%19 Oct →
ancient6–13-0.109%15 Oct →
dust213–11-0.0310%15 Oct →
cache13–10-0.0410%15 Oct →
mirage10–13-0.0616%15 Oct →
dust213–10-0.0515%15 Oct →
nuke13–10-0.0111%15 Oct →
inferno5–13-0.0121%15 Oct →
anubis4–13-0.026%15 Oct →
nuke13–10-0.0116%15 Oct →
anubis9–6-0.0414%15 Oct →
ancient13–10-0.0613%9 Oct →
mirage3–13-0.0714%9 Oct →
cache13–7-0.0321%9 Oct →
mirage13–9-0.0111%9 Oct →
nuke5–13-0.0313%9 Oct →
nuke15–150.0115%4 Oct →
inferno16–13-0.0720%4 Oct →
nuke13–11-0.0118%4 Oct →
mirage8–13-0.0713%2 Oct →
ancient13–110.059%2 Oct →
ancient13–10-0.0414%30 Sept →
cache1–13-0.078%30 Sept →
inferno13–10-0.019%25 Sept →
cache0–13-0.046%25 Sept →
inferno7–13-0.105%15 Sept →
vertigo2–13-0.076%15 Sept →
overpass13–90.0313%15 Sept →
nuke13–20.0411%10 Sept →
mirage14–16-0.0314%10 Sept →
ancient15–15-0.038%10 Sept →
nuke11–130.0525%1 Sept →
nuke13–80.0829%1 Sept →
ancient8–13-0.0210%1 Sept →
cache10–13-0.0413%1 Sept →
dust213–11-0.087%1 Sept →
shelter7–13-0.0228%23 Aug →
mirage8–13-0.0013%23 Aug →
inferno13–80.0315%23 Aug →
mirage13–11-0.0613%16 Aug →
ancient13–6-0.0617%16 Aug →
dust25–13-0.0126%16 Aug →
mirage13–10-0.089%11 Aug →
inferno13–11-0.0222%11 Aug →
nuke12–6-0.018%11 Aug →
inferno2–13-0.0121%11 Aug →
inferno7–130.0228%11 Aug →
inferno9–13-0.0212%11 Aug →
cache13–2-0.0016%10 Aug →
dust29–13-0.0419%9 Aug →
cache5–10-0.065%9 Aug →
dust213–7-0.0427%8 Aug →
mirage7–130.0111%8 Aug →
nuke10–130.0112%8 Aug →
dust27–13-0.0624%8 Aug →
inferno6–13-0.007%4 Aug →
ancient13–20.0419%4 Aug →
inferno13–110.0822%4 Aug →
inferno13–7-0.088%4 Aug →
ancient16–120.0016%4 Aug →
nuke10–13-0.0424%2 Aug →
dust211–13-0.0223%2 Aug →
dust213–60.0223%2 Aug →
anubis5–13-0.0417%2 Aug →
nuke13–70.0013%2 Aug →
nuke13–11-0.0121%2 Aug →
inferno4–13-0.068%31 Jul →
ancient11–13-0.0035%31 Jul →
cache8–13-0.079%31 Jul →
inferno10–13-0.0223%31 Jul →
anubis13–5-0.069%31 Jul →
cache10–13-0.073%24 Jul →
nuke14–16-0.0616%24 Jul →
inferno11–13-0.0311%24 Jul →
anubis13–8-0.059%24 Jul →
mirage13–110.0219%24 Jul →
inferno13–80.0219%24 Jul →
debris8–80.0323%24 Jul →
poseidon5–9-0.0737%24 Jul →
mirage11–130.0013%21 Jul →
dust210–13-0.0410%21 Jul →
dust25–13-0.0019%21 Jul →
cache13–11-0.0111%21 Jul →
nuke13–110.0110%19 Jul →
anubis16–13-0.0522%19 Jul →
mirage13–70.0017%19 Jul →
dust25–13-0.048%19 Jul →
inferno16–13-0.0422%15 Jul →
ancient6–13-0.0714%15 Jul →
dust25–13-0.070%12 Jul →
nuke13–50.0317%12 Jul →
inferno13–8-0.0712%12 Jul →
dust210–13-0.0513%12 Jul →
cache14–16-0.0618%9 Jul →
mirage13–30.016%9 Jul →

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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