Favorites, underdogs, and the four markets

Four markets, four different questions

Liverpool host Bournemouth. You like Liverpool. Fine, but what exactly are you betting on? That they win? That they win by enough? That the game has goals in it? Every matchup on Bet2Invest can be bet through up to four markets, and each one asks a different question:

• Moneyline: who wins the match. Liverpool at 1.55 against Bournemouth at 6.20. You back a team, it wins or it does not. In sports with draws, the draw is a third outcome you can back too.
• Spread: who wins after a handicap is applied. The Lakers at −6.5 points must win by 7 or more for the bet to land; their opponent at +6.5 can lose by up to 6 and still cover. The handicap deliberately erases the gap in class, so both sides trade near even odds.
• Total: the combined score of both teams, over or under a line. Over 2.5 goals in a football match wins once three goals are scored, no matter who scores them. You are betting on the shape of the game, not the winner.
• Team total: the same over/under logic, applied to one team's score alone. Over 1.5 goals for the home side wins if that team scores twice, even in a defeat.

A filter that predicts winners says nothing about totals, and vice versa. A team on a hot defensive streak is an argument for an under, not necessarily for its moneyline. Keep that in mind every time you pair a filter with a bet selection in the strategy builder.

Designations: the literal sides

Within a market, a designation names the side you are backing in fixed, positional terms: home, away, and, where the sport allows it (football being the obvious case), draw. These labels never move with the odds. The home team is the home team whether it is priced at 1.20 or 8.00.

Totals and team totals work the same way with their own positional sides: over or under, plus the points line the market is set at.

Favorite and underdog: sides the platform computes for you

On the moneyline you get two extra sides, and these are semantic rather than positional: favorite and underdog. Nobody declares them in advance. When your strategy is evaluated against a matchup, the platform reads the Pinnacle moneyline at that moment and resolves them: the shorter price is the favorite, the longer one the underdog.

One consequence is worth knowing before you build on it. In a pick'em, a matchup so tight that neither side is clearly shorter, there is no favorite to resolve. When your strategy filters on the favorite or underdog side, a pick'em is simply excluded. The same goes for the favorite_side filter, which checks whether the moneyline favorite sits where you expect it (at home or on the road): no clear favorite, no match.

Why "always back favorites" loses, and "always back dogs" too

Both slogans have loyal followings. Both bleed money over time, for the same two reasons.

First, the vig. Every price you take includes the bookmaker's margin, so even a perfectly informed market charges you a toll on each bet, favorites and underdogs alike. How that margin hides inside the odds is covered in Understanding odds and the vig.

Second, and more fundamental: the market has already priced the difference. Yes, favorites win more often, and they pay less precisely because of it. Underdogs pay handsomely, and lose often enough to cancel it out. A 1.25 favorite that wins four times out of five earns you nothing: you were paid for exactly that frequency, minus the toll. Being on the favorite is not an edge. It is a description.

Where the framing actually earns its keep

So why do the favorite and underdog sides exist at all? Because betting markets are shaped by crowds, and crowds do not behave the same way at every point on the odds spectrum. A widely observed pattern, the favorite-longshot bias, is that recreational money is drawn to long odds. That tends to make extreme longshot prices worse than they should be, while prices on heavier favorites have historically behaved comparatively better. Treat that as a direction to investigate, not a law: the size of the effect varies by sport, by league and by era, and Pinnacle's lines are sharper than most.

The practical point: "underdogs priced between X and Y, on the road, in these leagues" is a testable hypothesis about one asymmetric slice of the market. You can backtest it. "Back dogs" is a slogan. Semantic sides let you carve those slices without hand-picking teams.

How odds_range meets the designations

The workhorse here is odds_range: it passes when the Pinnacle price for a given market and side falls inside your chosen band of decimal odds (anywhere from 1 to 1000). Crucially, you configure it per market, and each variant carries its own parameters:

• On the moneyline, you pick a designation (home, away, draw, favorite or underdog) and the band applies to that side's price.
• On the spread, you set the points line and the side, then the band.
• On the total, you set the points line and choose over or under.
• On the team total, the same, for one team's line.

So "underdog between 2.50 and 3.50" and "over 2.5 goals priced under 2.00" are both odds_range conditions. They just live on different market variants.

A worked mini-example

Suppose you suspect that in a particular league, road underdogs get dismissed too readily once the home crowd inflates the favorite's price. One way to express that in the builder:

1. favorite_side set to home: only keep matchups where the moneyline favorite is the home team.
2. odds_range on the moneyline, away side, between 2.50 and 3.50: the visitor is a genuine outsider, but not a hopeless one.
3. Bet selection: moneyline, away.

Pick'em games drop out automatically (no favorite to resolve), and the odds band keeps you out of extreme longshot territory. Is it profitable? That is exactly what the backtest is for. This is a hypothesis, not a recommendation, and plenty of tidy hypotheses die on contact with the data. Note that favorite_side is a Pro-tier filter; odds_range is available on any plan.

Where to go next

• Understanding odds and the vig: what a decimal price really encodes, and the margin you pay on every bet.
• Odds and market filters: the full toolkit for slicing matchups by price.
• The closing line and market efficiency: why beating the close, not picking winners, is the real scoreboard.