Expected points refer to the value of any given situation regarding potential points. For example, a team starting a drive at their 20-yard line is in a situation that has an expected point value. On average, drives starting from this field position may result in 1.5 points. This value is based on historical data and the probability of specific outcomes from that field position. EP models get pretty complex, considering factors such as down and distance, field position, time remaining, the offence’s strength and defence’s strength, and even the weather. The output of these models is a value, often represented as a decimal, that indicates the expected points for that specific situation.
EP models in betting
Expected points models are a natural fit for football betting as they provide a quantitative way of evaluating performance independent of the final score. Here are some key ways bettors use EP models to their advantage:
Identifying over/undervalued teams
Expected points help identify teams that consistently outperform or underperform their expectations. For example, a team may have a solid won-loss record. Still, its expected points differential suggests it benefits from luck or unsustainable factors like an abnormally high number of forced turnovers. A team with a poor record may consistently put itself in high-value situations only to be let down by a few key players. These teams may be worth considering as underdogs in certain matchups, especially if their expected points differential is positive despite their losing record.
Evaluating offense and defense
Expected points models provide separate values for offensive and defensive performance, allowing bettors to identify teams with solid offences but weak defences or vice versa. This is crucial when assessing the likelihood of specific outcomes, such as a high-scoring game or a particular team covering the spread. For example, if a team has a potent offence but a porous defence, they may be a good bet to go over the total points line, even if their overall won-loss record doesn’t reflect it. A team with a stout defence but a sputtering offence may be a good bet to keep the game close, making them attractive underdogs against a higher-ranked opponent.
Sample size and variability
Football has a relatively small sample size compared to other sports, with only 17 regular-season games in the NFL and typically 12 or so games in a college football season. This means a few outlier games or unusual performances can influence expected point differentials. Bettors should be cautious when dealing with small sample sizes, especially early in the season. Monitoring trends and looking for consistent patterns is essential rather than overreacting to a single game or short-term fluctuation.
Line movement and market efficiency
Expected points models are widely used by sportsbooks and professional bettors, which means much of the value identified by these models may already be reflected in the betting lines. While EP models provide an edge, it’s important to remember that sportsbooks also employ analysts and models to set their lines, and the market is often efficient at incorporating new information. Bettors should consider expected points as one tool in their arsenal, used with other factors like line movement, public betting trends, and qualitative analysis. If you are looking for a trusted platform, consider sbobet88, which offers an extensive selection of football betting markets and competitive odds.