Dr. Mantis Toboggan MD

Dr. Mantis Toboggan MD — CS2 Stats

US76561198175274842[U:1:215009114]Steam profile ↗VAC banned

466Tracked matches48%Win rate2023Tracked since
336Hours in CS
CSDB Rating4.9 DevelopingPositional Player
Premier CS Rating11,268Blue band · top ~48.2% of ranked players (population est.)
WingmanSilver Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Aug 2026 (64 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: 11,268 -216 6 Aug – 16 Aug · 2 days played
11,26811,484peak 11,4846 Aug16 Aug
11,959Peak Premier in tracked matches
21Days played since 2026-08-06

Premier CS Rating

  • 216 below peak (11,484)
  • Next: Purple band at 15,000 — 3,732 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 rate45.6%42.0%44.3%above
Shot accuracy6.2%9.6%11.9%5.6% short
Kill/death ratio1.060.981.03above
Match win rate45.2%43.8%45.2%meets

This profile matches the typical Purple band player on 3 of 4 comparable metrics.

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.GGDr. Mantis Toboggan MDPREMIER11,268 · Blue bandcsdb.gg/stats

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Performance scores

Aim73
Positioning47
Utility43

0–100 skill scores via Leetify.

Recent form

COLD55–37–8Last 10055%Win rateLLLWLLLWLW

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · −5.4pp headshot accuracy · −93ms reaction

Win rate down 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

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 533ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 12%
  • Avg reaction 537ms

Last 20

  • 8–9–3 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 583ms

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 (+2.5 against its own average).

Aim7.3
Utility4.3
Positioning4.7
Opening Duels0.0
Clutch0.0

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

b1t

Plays most like b1t 90% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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. 614ms 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

Aim7.3
Positioning4.7
Utility4.3
Mechanics6.5
Opening Duels0.0
Win Impact4.4

Composite 4.9/10 (Developing), 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 rating0.01+0.02
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time618ms−71ms
first ⅓ avg 689ms → last ⅓ avg 618ms
Headshot accuracy13.9%−0.5%
first ⅓ avg 14.4% → last ⅓ avg 13.9%

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

0.12Best match rating · 13–4 · mirage, 14 Aug →
39%Best headshot accuracy · 13–1 · mirage, 14 Aug →
453msFastest reaction time · 1–13 · ancient, 12 Sept →
13–1Biggest win · dust2, 20 Aug →

Across the last 100 tracked matches.

Highlights

8Longest win streak
L3Current streak
6–1In matches decided by ≤2 rounds
1Overtime games

Map breakdown

cacheBest map · 80% over 5infernoWeakest map · 42% over 19
MapGradePlayedRecordWin rateAvg rating
dust2A3620–1656%0.00
mirageA2212–1055%-0.00
infernoC198–1142%0.00
anubisA106–460%-0.01
cacheS54–180%0.01
ancient—41–325%-0.01
nuke—33–0100%0.02
train—11–0100%0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

14,763Lifetime kills
1.06K/D · Top 50% of Blue band
909Matches
45.2%Match win rate · Top 50% of Blue band
45.6%Headshot % · Top 50% of Blue band
6.2%Shot accuracy
1,520MVPs
336Hours (in match)
491Bombs planted
154Bombs defused

Most-used weapons

Lifetime map wins

1,853dust2
1,167inferno
291nuke
210vertigo
154train
134office
87cbble
47lake

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

Faceit stats

Combat

2Matches
0%Win rate
0.78Avg K/D
65.5ADR
53%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

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.

14.3%Headshot accuracy
41.6%Accuracy (enemy spotted)
39.3%Spray accuracy
79.1%Counter-strafing
10.3°Preaim
614msReaction time
24.6%T opening success
30.2%CT opening success
0.42Enemies flashed / flash
4.9%Flash assists
4.59HE damage / grenade
16.08Flashes / 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 14.3143% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4168 — below the 0.5 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 24.6366% — 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.

42% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient6–13-0.094%18 Sept →
ancient1–130.0119%12 Sept →
inferno3–100.022%11 Sept →
anubis9–20.029%11 Sept →
anubis3–13-0.1117%10 Sept →
inferno9–130.0818%7 Sept →
inferno0–13-0.075%6 Sept →
anubis13–50.0215%6 Sept →
inferno9–130.0413%6 Sept →
ancient13–30.1118%6 Sept →
anubis3–13-0.1125%4 Sept →
dust213–11-0.0513%4 Sept →
inferno13–90.0324%4 Sept →
dust213–30.0819%4 Sept →
dust212–120.048%4 Sept →
mirage7–13-0.009%4 Sept →
inferno13–30.0413%3 Sept →
inferno12–120.0217%3 Sept →
dust213–100.0618%3 Sept →
dust212–12-0.0231%3 Sept →
dust213–8-0.0324%28 Aug →
mirage13–7-0.046%28 Aug →
dust210–130.0316%28 Aug →
dust29–130.028%27 Aug →
dust213–50.018%27 Aug →
dust22–10-0.0329%27 Aug →
inferno13–60.0011%27 Aug →
inferno13–90.1013%27 Aug →
dust21–4-0.110%24 Aug →
mirage7–130.0516%24 Aug →
dust213–20.0110%24 Aug →
mirage9–130.0212%24 Aug →
mirage13–20.0212%24 Aug →
mirage10–130.0112%24 Aug →
inferno8–13-0.0323%21 Aug →
dust212–120.0422%20 Aug →
dust213–100.0212%20 Aug →
anubis4–70.0629%20 Aug →
mirage3–00.0525%20 Aug →
mirage13–11-0.0513%20 Aug →
dust213–10.0315%20 Aug →
inferno13–11-0.059%16 Aug →
nuke13–10-0.038%16 Aug →
mirage4–13-0.086%16 Aug →
train13–50.0323%16 Aug →
inferno2–13-0.0330%15 Aug →
inferno9–13-0.0414%15 Aug →
cache13–20.046%15 Aug →
nuke13–110.0112%15 Aug →
dust213–50.1016%15 Aug →
nuke13–80.0814%15 Aug →
anubis13–10.0114%14 Aug →
mirage13–10.0039%14 Aug →
mirage13–40.129%14 Aug →
inferno4–13-0.0115%14 Aug →
mirage13–90.008%14 Aug →
dust213–50.0433%14 Aug →
mirage10–13-0.0817%13 Aug →
cache6–13-0.0310%9 Aug →
dust213–7-0.0410%9 Aug →
dust28–0-0.026%9 Aug →
dust213–80.0214%9 Aug →
mirage13–50.0921%9 Aug →
inferno13–70.0211%9 Aug →
cache13–70.0924%9 Aug →
mirage13–10-0.0610%9 Aug →
anubis13–4-0.0112%9 Aug →
dust27–13-0.0224%9 Aug →
dust213–30.0713%9 Aug →
dust213–60.0319%9 Aug →
mirage12–120.0025%9 Aug →
mirage13–80.0122%9 Aug →
inferno3–13-0.110%9 Aug →
dust25–13-0.093%9 Aug →
mirage13–10-0.0410%8 Aug →
dust212–12-0.0216%8 Aug →
dust213–20.1019%8 Aug →
mirage7–13-0.019%8 Aug →
ancient1–6-0.0814%8 Aug →
dust29–13-0.0310%8 Aug →
dust211–13-0.0412%8 Aug →
mirage13–50.0122%8 Aug →
dust212–120.0320%8 Aug →
dust213–10-0.0421%8 Aug →
inferno13–60.0215%8 Aug →
dust25–120.0110%7 Aug →
dust25–13-0.0317%7 Aug →
inferno13–40.0218%7 Aug →
dust210–13-0.0120%6 Aug →
cache13–11-0.0113%6 Aug →
anubis7–13-0.0521%6 Aug →
anubis13–50.000%6 Aug →
mirage3–13-0.0729%6 Aug →
cache13–10-0.035%6 Aug →
inferno15–15-0.0411%6 Aug →
dust213–11-0.0212%6 Aug →
anubis11–20.0510%6 Aug →
dust213–7-0.0613%6 Aug →
dust213–5-0.107%6 Aug →
mirage10–130.0017%6 Aug →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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