SUCK PIG SHAWN

SUCK PIG SHAWN — CS2 Stats

CA76561198151829806[U:1:191564078]Steam profile ↗✓ No bans

655Tracked matches44%Win rate2023Tracked since
CSDB Rating4.2 Developing
Premier CS Rating5,412Light Blue band · top ~76.8% of ranked players (population est.)
CSDB Leaderboard#20331 of 26500 tracked
WingmanSilver III
Ladder ranks via Leetify

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CSDB.GGSUCK PIG SHAWNPREMIER5,412 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim46
Positioning48
Utility48

0–100 skill scores via Leetify.

Recent form

COLD38539Last 10038%Win rateLWLLLWLTLW

Last 10 vs previous 10: -20pp win rate · +0.00 avg rating

Player DNA

Aim4.6
Aggression7.3
Utility4.8
Positioning4.8
Opening Duels3.7

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

ropz

Plays most like ropz 84% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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. 684ms 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

Aim4.6
Positioning4.8
Utility4.8
Mechanics6.5
Opening Duels3.7
Win Impact3.1

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.03
first ⅓ avg -0.00 → last ⅓ avg 0.03
Reaction time698ms+7ms
first ⅓ avg 691ms → last ⅓ avg 698ms
Headshot accuracy15.2%+2.9%
first ⅓ avg 12.4% → last ⅓ avg 15.2%

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.

Highlights

0.16Best rating — train 13–4
131Biggest win — mirage
5Longest win streak
99In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 50% over 10infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
dust2D33112233%0.04
ancientC135838%-0.03
mirageC125742%0.02
nukeB105550%0.00
cacheB84450%0.02
infernoD72529%0.01
train42250%0.06
overpass41325%-0.02
vertigo31233%0.02
office2020%0.00
anubis21150%-0.01
alpine21150%-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno 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.

15.7%Headshot accuracy
31.5%Accuracy (enemy spotted)
33.3%Spray accuracy
79.1%Counter-strafing
10.9°Preaim
684msReaction time
39.1%T opening success
50.4%CT opening success
0.55Enemies flashed / flash
6.2%Flash assists
8.46HE damage / grenade
6.59Flashes / 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 39.0763% — below the 40% mark we flag

Spend your practice time on Inferno

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
train10–130.0218%14 Aug
nuke13–80.0410%7 Aug
mirage4–130.0817%27 Jul
dust27–130.0013%21 Jul
inferno1–13-0.0311%21 Jul
train12–10.0317%21 Jul
mirage2–100.026%20 Jul
dust212–120.0621%20 Jul
dust29–13-0.0225%9 Jul
dust213–70.047%8 Jul
dust213–100.0919%6 Jul
mirage5–50.089%5 Jul
mirage12–120.0316%5 Jul
cache13–11-0.0011%5 Jul
cache5–130.0020%4 Jul
dust216–120.0422%30 Jun
ancient2–13-0.0513%30 Jun
mirage16–14-0.0113%29 Jun
dust25–13-0.0217%29 Jun
dust210–130.0815%27 Jun
nuke13–80.0315%27 Jun
dust28–130.0324%26 Jun
overpass3–13-0.050%26 Jun
dust213–110.0719%26 Jun
vertigo9–130.0315%26 Jun
dust212–120.1128%26 Jun
mirage4–13-0.0321%26 Jun
nuke13–70.066%26 Jun
dust213–110.1216%25 Jun
inferno9–13-0.0113%24 Jun
nuke4–13-0.0819%24 Jun
nuke13–100.0717%23 Jun
dust26–130.0612%23 Jun
ancient8–130.0118%23 Jun
dust213–80.0916%22 Jun
dust213–60.1211%22 Jun
ancient11–130.0112%22 Jun
mirage5–13-0.048%21 Jun
mirage13–10.0810%21 Jun
dust213–9-0.0310%21 Jun
ancient13–80.067%21 Jun
ancient13–6-0.039%21 Jun
train13–40.1615%20 Jun
train12–120.0420%19 Jun
mirage3–13-0.004%19 Jun
dust211–130.0922%19 Jun
dust23–130.0228%19 Jun
inferno7–90.0319%18 Jun
office9–130.0410%18 Jun
dust29–7-0.003%18 Jun
nuke11–13-0.0113%15 Jun
dust26–130.0014%15 Jun
office6–13-0.0310%14 Jun
dust210–130.0615%14 Jun
vertigo11–13-0.0110%14 Jun
dust25–130.0213%14 Jun
inferno13–9-0.017%13 Jun
ancient8–13-0.044%9 Jun
dust211–13-0.0117%9 Jun
overpass9–5-0.057%8 Jun
vertigo13–110.029%8 Jun
anubis13–70.0121%31 May
dust211–130.1020%25 May
cache13–100.0915%25 May
nuke2–13-0.0816%24 May
nuke0–13-0.0514%24 May
cache5–13-0.0411%24 May
cache13–40.0821%24 May
dust212–120.0717%16 May
alpine4–13-0.1014%16 May
nuke13–20.108%15 May
dust213–110.0121%15 May
dust29–130.0214%15 May
cache12–120.055%14 May
dust213–100.056%13 May
dust23–13-0.068%11 May
mirage12–12-0.0312%11 May
ancient13–10-0.0212%11 May
inferno13–30.113%11 May
ancient3–13-0.0319%10 May
mirage13–50.0512%10 May
cache10–13-0.0223%9 May
dust27–13-0.038%9 May
inferno11–13-0.0114%9 May
ancient9–13-0.0913%8 May
ancient9–4-0.067%8 May
dust22–70.1121%8 May
overpass8–130.0514%8 May
ancient6–13-0.0911%8 May
ancient6–13-0.078%8 May
dust23–13-0.075%8 May
dust212–120.0615%8 May
anubis11–13-0.0321%7 May
nuke0–6-0.0311%7 May
overpass4–13-0.0317%7 May
cache13–40.0312%7 May
alpine2–3-0.069%7 May
ancient13–90.018%7 May
mirage13–4-0.0115%7 May
inferno12–12-0.038%7 May

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 →