Crypto Casino
Torrent Gear
How to tell strategy from superstition
1) Short answer
Strategy is a set of rules based on testable assumptions, data and mathematics, with an understandable source of expectation and risk control.
Superstition is a belief in "patterns" without causation: "after black it will be red," "the slot has warmed up," "happy time/number."
2) Three strategy criteria
1. Falsifiability. The thesis has a way of making sure it is incorrect (test/experiment).
2. Cause → effect. It is clear why it should work (probability/payout/cost changes).
3. Success metric and risk. There are measurable goals (EV, ROI, Kelly share, drawdown) and limits (SL/TP,% of bankroll).
If at least one point is not there, this is 90% superstition.
3) Source of expectation: where + EV is taken (if at all)
Casino games: house edge is built into the rules; betting strategy does not change RTP. This means that + EV has nowhere to go - you can only control the trajectory and risk.
Exceptions with potential + EV:- Blackjack with basic strategy + card count (offline with suitable rules).
- Video poker on the "right" pay tables with the perfect game.
- Promo/overlays with arithmetically favorable terms.
- Sport/exchange with correct probability model.
- If your "plan" does not change the probabilities/payments/costs - this is not about + EV.
4) Red flags of superstition
Appeal to seriality: "after 7 minuses, definitely a plus" (gambler's fallacy).
After-the-fact patterns: explanations of "why worked" without prediction in advance.
Time magic: "slots are more generous at night," "roulette gives on Tuesdays."
Opaque signals: "secret indicators," graphs without technique.
Ignores mathematics: no edge/RTP calculation, ROI, risks, only "sensations."
Promise of assurance: "risk-free" systems, "100% strategy."
5) Green strategy flags
Hypothesis with a test plan: how you collect data, what sample, what success criterion.
Net source of effect: increased probability (p), improved payments (k), reduced costs (commission, tax), market filter.
Risk accounting: rate in% of BR, SL/TP, duration, correlation of positions.
Repeatability: the result is stable on new data (out-of-sample).
Transparent metrics: EV = k· p − 1 (sports), total ≈ − edge × turnover (casino), Sharpe/quartiles of drawdown (portfolio).
6) Tampering test (do before the game)
1. Formalize the statement. For example: "If k ≥ 1. 95 and my model gives p ≥ 0. 54, then EV = 1. 95×0. 54 − 1 = +0. 053».
2. Assign thresholds and horizon. How many attempts, what is the minimum sample.
3. Define "stop by hypothesis." In what result do you recognize the idea as incorrect (p-value, confidence interval, ROI drop).
4. Protect from retraining. Divide the data by in-sample/validation/out-of-sample.
If steps 1-4 cannot be performed, this is not a strategy.
7) Mathematical mini-set
Casino (EV <0):[
\ text {Expected Total }\approach -\text {edge }\times\text {Turnover} ,\quad\text {edge} = 1-\text {RTP}.
]Consequence: progressions/alternations change only variance and turnover/hour, not average.
Sports (single bet):[
EV = k\cdot p ^ - 1 ;\quad\text {Kelly's fraction} =\frac {k p ^ -1} {k-1 }\(\text {use }\tfrac14\text {- }\tfrac12).
][
Loss_{hour}\approx\text {edge }\times\text {bid }\times (\text {attempts/min} )\times 60.
]8) Examples: strategy or superstition?
A. "After ten blacks I put on red - the chance has grown."
Superstition. Events are independent; p was unchanged.
B. "Playing European roulette, not American roulette."
Game price management strategy: edge 2. 70% vs. 5. 26%. The average will not be a plus, but the cost is lower.
C. "I raise the bet after winning, lower it after losing - the slot "feels.""
Superstition. Turnover and volatility change, not RTP.
D. "Full Paytable Jacks or Better Video Poker + Optimal Strategy"
Strategy with potential + EV (rarely, depends on the table and error-free game).
E. "I bet only on rinks with a margin of <2%, where my p gives EV> 0; size - ¼ Kelly"
Strategy: there is a p model, quality thresholds, risk management.
9) Practical filter 5 questions
1. What exactly is changing in probabilities/payouts/costs?
2. How to measure and check it in advance?
3. What is the risk management plan? (% BR, SL/TP, duration)
4. What will be considered a refutation of the hypothesis?
5. Is there a conflict of interest/manual sampling/fitting to the past?
10) Data and discipline checklist
Keep a journal: turnover, total,% rate, speed, game/market, RTP version, promotional conditions.
Consider alpha: the difference between fact and benchmark (for a casino - '− edge × turnover').
Test resilience: repeatability on new data; exclude "better days" from the report.
Control speed (less auto-attempts/min → less than an hour).
Keep short sessions with timer and SL/TP; no dogons.
11) Frequent cognitive traps
Gambler's fallacy: Belief in "debts of chance."
Survival bias: we see survivors, we do not see hundreds of failed "strategies."
Confirmation bias: we collect facts "for," ignore "against."
Control illusion: bet control ≠ probability control.
Post hoc: "after that means because of this."
12) What to do instead of superstition
Define the goal: playtime/wagering/+ EV.
Choose cheap products (below edge), use the rate in% of BR:- high-vol: 0. 25–0. 75% BR, medium: ~ 1% BR, low/1: 1: 1-2% BR.
- Play in series (30-90 min) with SL/TP (e.g. − 20... − 40 %/+ 30... + 150%).
- For sports/plus - build model p, test out-of-sample, use fractional Kelly.
- Count bonus arithmetic: Bonus × Wager × edge (allowed games).
A strategy is a testable hypothesis with an understandable source of expectation and risk control; superstition - everything that relies on "feel," "saw the series," "the system always works." In casinos, "betting strategies" do not make the game positive, but help manage the price of an hour, playtime and stress. And where + EV is fundamentally possible (sports, rare payment tables, overlays), it is given by data and discipline, not signs.