Steppa Pig

Steppa Pig — CS2 Stats

76561198055371001[U:1:95105273]Steam profile ↗✓ No bans

889Tracked matches52%Win rate2020Tracked since
537Hours in CS
CSDB Rating3.6 LearningSupport
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Sep 2026 (58 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 889 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 19,049 +1,090 23 Aug – 26 Sept · 6 days played
17,95919,326peak 19,32623 Aug26 Sept
19,326Peak Premier in tracked matches
36Days played since 2025-03-22

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 4 among CSDB-tracked players (n=14,630), 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 4 medianLevel 5 medianvs Level 5
Headshot rate36.7%42.7%43.8%7.1% short
Shot accuracy11.4%11.2%12.0%0.6% short
Kill/death ratio0.740.991.020.28 short
Match win rate46.7%43.9%44.7%above

This profile matches the typical Level 5 player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGSteppa PigFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim30
Positioning39
Utility43

0–100 skill scores via Leetify.

Recent form

COLD56–37–7Last 10056%Win rateWTLLLLLTTL

Last 10 vs previous 10: −70pp win rate · −0.04 avg rating · −2.4pp headshot accuracy · −39ms reaction

Win rate down 70pp 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 658ms

Last 10

  • 1–6–3 · 10% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 14%
  • Avg reaction 698ms

Last 20

  • 9–8–3 · 45% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 717ms

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 (+1.6 against its own average).

Aim3.0
Utility4.3
Positioning3.9
Opening Duels0.0

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

NiKo

Plays most like NiKo 66% 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. 679ms 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

Aim3.0
Positioning3.9
Utility4.3
Mechanics4.6
Opening Duels0.5
Win Impact5.6

Composite 3.6/10 (Learning), 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-0.04+0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time681ms−33ms
first ⅓ avg 715ms → last ⅓ avg 681ms
Headshot accuracy14.2%−2.5%
first ⅓ avg 16.7% → last ⅓ avg 14.2%

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 · 16–13 · ancient, 27 Aug →
33%Best headshot accuracy · 7–2 · inferno, 24 Apr →
406msFastest reaction time · 13–5 · inferno, 26 Sept →
13–1Biggest win · nuke, 7 Apr →

Across the last 100 tracked matches.

Highlights

8Longest win streak
14–3In matches decided by ≤2 rounds
3Overtime games

Map breakdown

trainBest map · 75% over 8cacheWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
infernoA138–562%-0.02
nukeB137–654%-0.03
ancientC125–742%-0.05
overpassA117–464%-0.02
trainS86–275%-0.02
vertigoA74–357%-0.04
dust2S75–271%-0.02
cacheD62–433%-0.06
anubisC52–340%-0.04
mirageA53–260%-0.04
palacio—22–0100%-0.04
jura—21–150%-0.04
basalt—21–150%-0.05
poseidon—11–0100%-0.00
sanctum—10–10%-0.01
alpine—10–10%-0.04
golden—11–0100%-0.02
italy—10–10%-0.02
grail—11–0100%-0.02
edin—10–10%0.02

Across the last 100 tracked matches.

Lifetime stats

15,939Lifetime kills
0.74K/D
1,181Matches
46.7%Match win rate · Top 50% of Level 4 players
36.7%Headshot %
11.4%Shot accuracy · Top 50% of Level 4 players
1,706MVPs
537Hours (in match)
996Bombs planted
318Bombs defused

Most-used weapons

Lifetime map wins

2,415inferno
1,301nuke
893dust2
602train
338vertigo
88cbble
39lake
38bank

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

Faceit stats

Combat

289Matches
49%Win rate
0.71Avg K/D
—ADR
32%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
9Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Ancient1968%0.7211.5
Inferno1833%0.7811.4
Overpass1656%0.589.1
Anubis1567%0.8211.4
Nuke650%0.609.3
Dust210%0.7311.0
Mirage10%0.569.0

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.

13.0%Headshot accuracy
30.3%Accuracy (enemy spotted)
32.1%Spray accuracy
70.7%Counter-strafing
12.0°Preaim
679msReaction time
22.8%T opening success
34.1%CT opening success
0.67Enemies flashed / flash
6.7%Flash assists
9.38HE damage / grenade
8.26Flashes / 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 13.0059% — below the 15% mark we flag

    Aim Training →
  2. 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 22.7714% — below the 40% mark we flag

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.

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

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
poseidon9–7-0.0027%14 May →
sanctum8–8-0.0116%14 May →
ancient6–13-0.0518%14 May →
inferno6–13-0.0517%14 May →
cache5–13-0.077%12 May →
nuke3–13-0.0713%7 May →
ancient8–13-0.0614%7 May →
anubis15–15-0.0610%3 May →
cache12–12-0.099%3 May →
cache9–13-0.119%3 May →
alpine4–13-0.0424%29 Apr →
cache4–13-0.067%29 Apr →
cache13–50.019%29 Apr →
cache13–8-0.0311%29 Apr →
inferno7–20.0533%24 Apr →
anubis13–80.0218%24 Apr →
palacio13–11-0.047%3 Oct →
golden13–10-0.0215%3 Oct →
palacio13–8-0.0413%3 Oct →
nuke13–3-0.0122%29 Sept →
overpass12–12-0.0414%29 Sept →
ancient5–13-0.095%29 Sept →
nuke4–13-0.0315%26 Sept →
inferno13–5-0.0424%26 Sept →
overpass13–8-0.0418%26 Sept →
jura4–13-0.0916%14 Sept →
nuke13–11-0.0812%9 Sept →
ancient2–13-0.104%9 Sept →
vertigo6–90.0021%31 Aug →
train13–8-0.038%31 Aug →
ancient16–130.0811%27 Aug →
ancient11–13-0.0313%25 Aug →
overpass13–100.0211%25 Aug →
inferno13–11-0.0120%23 Aug →
nuke6–13-0.0417%23 Aug →
italy12–12-0.029%23 Aug →
mirage13–80.016%23 Aug →
overpass13–8-0.0210%23 Aug →
ancient10–13-0.1016%21 Aug →
inferno13–60.0312%21 Aug →
train13–7-0.048%21 Aug →
ancient13–40.027%21 Aug →
dust213–80.0213%19 Aug →
inferno12–16-0.0015%13 Aug →
nuke13–7-0.0116%13 Aug →
nuke13–9-0.0212%13 Aug →
inferno13–11-0.029%10 Aug →
overpass13–30.0020%3 Aug →
dust27–130.0214%3 Aug →
overpass5–13-0.0821%26 Jul →
ancient13–6-0.0210%26 Jul →
nuke5–13-0.0523%17 Jul →
jura13–5-0.0021%9 May →
grail13–10-0.0217%9 May →
nuke7–13-0.085%26 Apr →
dust213–6-0.0218%26 Apr →
inferno10–13-0.0411%21 Apr →
train13–11-0.0112%21 Apr →
overpass13–110.0316%21 Apr →
mirage4–13-0.0614%21 Apr →
vertigo13–6-0.0110%21 Apr →
vertigo13–60.0117%20 Apr →
inferno13–50.058%20 Apr →
inferno11–13-0.0916%19 Apr →
overpass13–20.0213%19 Apr →
train13–11-0.089%19 Apr →
nuke13–11-0.0210%9 Apr →
ancient4–13-0.0614%9 Apr →
nuke13–10.0217%7 Apr →
dust213–11-0.0616%7 Apr →
train9–13-0.0521%7 Apr →
dust21–13-0.0529%3 Apr →
basalt13–60.008%3 Apr →
vertigo4–13-0.0612%3 Apr →
overpass6–13-0.0825%3 Apr →
anubis5–13-0.118%3 Apr →
train13–60.0529%3 Apr →
overpass13–11-0.0216%31 Mar →
ancient13–11-0.0521%31 Mar →
vertigo13–2-0.0514%31 Mar →
train6–13-0.027%29 Mar →
mirage9–13-0.0820%29 Mar →
vertigo4–13-0.150%29 Mar →
inferno12–12-0.0823%29 Mar →
anubis9–13-0.0116%25 Mar →
nuke11–13-0.0218%25 Mar →
dust213–5-0.079%25 Mar →
mirage13–5-0.0219%25 Mar →
anubis13–11-0.0718%24 Mar →
mirage13–3-0.0731%24 Mar →
basalt10–13-0.1029%24 Mar →
edin5–130.029%24 Mar →
inferno13–50.0412%23 Mar →
ancient13–10-0.0715%23 Mar →
dust213–110.0122%23 Mar →
overpass12–12-0.0311%23 Mar →
vertigo13–9-0.0312%23 Mar →
train13–5-0.0018%23 Mar →
nuke13–90.0316%23 Mar →
inferno13–8-0.0417%22 Mar →

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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