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How to analyze odds and win more often
The goal is not to "guess the outcomes," but to buy a price below its fair value. Below is a compact but practical system: how to read coefficients, how to remove margins, where to look for value and how to manage risk so that mathematical expectation works at a distance.
1) Base: conversion of coefficients into probabilities
Decimal (EUR) factors:- Implicit probability: (q = 1/d)
- Break-even point: you need to win more often than (1/d)
Example: (d = 1. 85 \Rightarrow q=54. 05%). In order not to lose over a long distance, your real probability of outcome must be above 54. 05%.
2) How to remove a bookie's margin (around)
In a two-source market, d1 and d2 usually give the sum of the probabilities (q_1+q_2>100%).
Normalization steps (proportional conversion method):1. (q_i = 1/d_i)
2. (R =\sum q_i) (this is> 1 due to margin)
3. "Fair" probabilities: (p_i = q_i/R)
4. "Fair" odds: (d ^ {fair} _ i = 1/p_i)
Mini-example:- d1=1. 85 → q1=0. 5405 d2=2. 05 → q2=0. 4878
- R=1. 0283 (2. 83% margin)
- p1=0. 5257 → (d^{fair}_1≈1. 905)
- p2=0. 4743 → (d^{fair}_2≈2. 108)
If you believe that real (p_1>52. 57%), the rate on the outcome is 1 to 1. 85 may have value.
3) What is value and how to count it
Expected value (EV) per bet S:[
EV = S \cdot (p \cdot d - 1)
]where (p) is your estimate of the true probability.
Эдж (edge): (\text{edge} = p \cdot d - 1).
A positive edge ⇒ rate is mathematically beneficial.
Example: d = 2. 10, yours (p = 52%).
edge = 0. 52×2. 10−1 = +0. 092 (9. 2%), EV per 100 cu = + 9. 2.
4) CLV: main quality marker
Closing Line Value - comparing your price with the closing one (before starting).
Bought 1. 95, closing 1. 85 → you beat the market (got the best price).
At a distance, a positive CLV almost always correlates with a positive result.
How to use: Fix "bid price" and "close." If the CLV is consistently negative, you pay for a "late picture" or overestimate events.
5) Timing and "shopping" lines
Comparison of offices: keep the price list for 3-5 reliable operators - the difference is 0. 02–0. 05 by ten multiples of EV.
When to enter:- Niches/props - more often earlier (your knowledge> of the market).
- Top markets - often later, closer to closing (less noise, more information).
- Movement of lines: sharp shifts ≠ "truth." Check causes (injuries, lineups, weather, motivation).
6) Where to look for an advantage
Niche leagues/pros: less attention - above the price error.
Total models in species with stable "intensity" (basketball, baseball).
Player markets at good sources of stats/minutes.
Live windows: suspension → reopening: brief "skirmishes" of the line; careful with delays.
7) Mini modeling without fanaticism
For outcomes/totals: logistic/poisson model + calibration (Isotonic/Platt).
Feechie: Strength of Teams (Elo/PRI), Pace, xG/eFG%, Schedule (b2b), Weather/Coverage, Injuries, Umpires.
Validation: walk-forward, no data leakage; key metrics are Brier/LogLoss and calibration.
8) Bankroll and the Kelly Stakes
Flat: fixed% of the bank (e.g. 0. 5-1% for singles).
Kelly: (f ^ =\frac {p\cdot d - 1} {d - 1}).
Kelly fraction (¼ - ½) is recommended due to estimation errors (p) and variance.
Never use martingale/dogon - it's a dispersion trap.
9) Dispersion and batch size
Even with a plus EV, there will be minus segments.
The higher the coefficients and express trains, the more volatile the result.
Plan your bank to survive 100-300 bets without stress.
Separately, take into account draws/push/void according to the rules of the sport.
10) Live: Price vs delays
Stream is usually 5-30 seconds behind; model and market - faster.
Buy logic, not a "picture": pace, fouls, rotations, fatigue, economic cycles (in esports).
Overheating windows after mini-events are important (jerks 8-0, early break) - look for overstatement/understatement, but take the re-racing calmly.
11) Betting log: what to fix
Date/league/market, odds at bet, your (p), amount.
Closing factor (CLV), result, why in/out notes.
Weekly: average edge,% value-rates, p-value calibration, error trends.
12) Frequent errors that "eat up" EV
Ignore margin: Compare your probability with "dirty" (uncleaned) from the round.
Buying "brands" and hype: bet on name/news without numbers.
Re-trading: Too many markets without edge.
No timing: entry "by movement" for no reason.
Express trains "for space": margins and correlations multiply.
Emotions and "Dogon": destroy the bank faster than any bad model.
13) Quick cheat sheets by sport
Football: Watch xG, pace and style pairings (pressing vs low block), rotation and calendar. Asian odds and alternative totals are often more honest than 1X2.
Tennis: coverage, freshness,% first/second serve, H2H in style; live - games and pressure points.
Basketball: pace, eFG%, ORB/DRB, fouls/bonus, b2b schedule; player props depend on minutes.
Esports: patches/meta, map pool, ban/peak, LAN fatigue; avoid transferring logic between games.
American football: OL/QB, DVOA, wind; follow the "scripts" of the start of matches.
Baseball: Starting pitchers, bullpen, park factors; the F5 market is often cleaner.
14) Pre-bid checklist
1. Margin removed? I compare my (p) to (p ^ {fair}) rather than the "dirty" probability.
2. Have a value? (p\cdot d - 1\ge X%) (set the minimum threshold in advance).
3. CLV plan: I understand why the price may move and when to enter.
4. Risk: Flat/Kelly share rate, no dogons.
5. Are the calculation rules clear? OT/shootouts, VAR, push/void.
6. Magazine: made a bet and the hypothesis of "why."
15) The bottom line
Winning more often at a distance is not about "flair," but about the price. Translate odds into probabilities, clear margin, only put where value is, keep an eye on CLV, manage the bank with discipline and respect variance. This mechanic is boring - but it is she who turns the chaos of sport into a controlled strategy.