Why Do Sports Odds Change?

Many sports trading strategies hinge on odds changing over time. For instance, a strategy might involve laying a market at lower odds, anticipating the opportunity to back it at higher odds later on. Conversely, one might back a market at higher odds, hoping to lay it at lower odds in the future. Some strategies work with short term odds fluctuations, while others depend on longer term odds variations.

In this post I’ll take a look at some examples of odds dynamics and unpack why the odds change.

Pre-Match and In-Play Odds Changes

Example: Draw

Let’s start with the Nordsjælland — Hvidovre (29 September 2023) match. Nordsjælland had pre-match odds of around 1.3, while Hvidovre was at 13, and a draw was 7. Nordsjælland was the clear favourite.

In-match odds: Nordsjælland (red), Hvidovre (green), and draw (blue).
In-match odds: Nordsjælland (red), Hvidovre (green), and draw (blue).
Pre-match odds.
Pre-match odds.

The match ended in a 0:0 draw. The in-match odds plotted below show how things evolved during the course of the game. As a draw became progressively more likely the odds on the draw (blue) shortened, while those on Nordsjælland (red) lengthened. Less obviously, the odds on Hvidovre (green) drifted too.

Example: Underdog Wins

Next let’s look at the Wolverhampton — Manchester City (30 September 2023) match. The odds on Manchester City before the match around 1.4, while Wolverhampton was at 9.4, and a draw was 5.5. Manchester City was the clear favourite.

In-match odds: Wolverhampton (red), Manchester City (green), and draw (blue).
In-match odds: Wolverhampton (red), Manchester City (green), and draw (blue).
Pre-match odds.
Pre-match odds.

Wolverhampton scored in the first half, causing their odds to shorten, while those of Manchester City got longer. At the start of the second half Wolverhampton were 1:0 up, with their odds being similar to those for a draw. Manchester City, whose odds had been gradually drifting during the first half, was still favoured to win the game. Not far into the second half the odds on Wolverhampton dropped below those on Manchester City. However, a goal from Manchester City caused a reversal and their odds dropped dramatically, while those of Wolverhampton lengthened. Not long after that that, Wolverhampton scored a second goal, causing their odds to decline, while those of Manchester City increased. There were no further events in the game. The odds on Wolverhampton continued to decrease for the rest of the game, ending around 1.04, while those for Manchester City drifted to 170 at the final whistle. The odds of a draw were still significant for most of the second half, although these too drifted towards the end, with a final value of 50. Wolverhampton, the underdog, won 2:1.

Example: Favourite Wins

A third example is the Dalian Yifang — Shandong Luneng Taishan (26 September 2023) match. Luneng had pre-match odds of around 1.1, while Dalian was at 36, and a draw was 18. Dalian was the clear favourite.

In-match odds: Shandong Luneng Taishan (red), Dalian Yifang (green), and draw (blue).
In-match odds: Shandong Luneng Taishan (red), Dalian Yifang (green), and draw (blue).
Pre-match odds.
Pre-match odds.

Luneng, the favourite, won the game 2:0. Jadson (Luneng) received a red card in the first half. The odds plotted below reflect the effect of the two goals and the red card. After the red card, the odds for Luneng (red) jumped from 1.12 to 1.76, reflecting the fact that with one less player on the field their chances of winning had decreased. However, not too long afterwards a goal reduced their odds to 1.3 and a second goal brought them to 1.03. Somewhat surprisingly, the red card did not have much effect on the odds of a draw (blue), nor did either of the goals. Yet the draw odds did change during the game. Why?

Also noteworthy is that there was no systematic change in the odds during the match. Compared with the previous two plots, the odds in this game remained constant for long periods. Why?

My hypothesis is that there was no systematic trend in the odds on this game because the favourite was consistently in the lead. The other two games either ended in a draw (Nordsjælland — Hvidovre) or the underdog won (Wolverhampton — Manchester City). A sample of size of 3 is not much to go on though!

Some other games with interesting odds dynamics:

Reasons that Odds Change

Before we consider the reasons for odds changing with time it would be helpful to consider where the initial odds come from. Bookmakers set initial odds based on several factors, including team performance, player injuries, and head-to-head statistics. These initial odds are a reflection of how bookmakers see the game’s probable outcome.

There are various factors that influence whether, when and to what degree those odds will change.

  • Wagers & Market Sentiment — One of the primary reasons odds change is the number and size of wagers placed on a particular outcome. If a large amount of money is placed on the home team to win, the odds for the home team will shorten, meaning they become less profitable to bet on. Conversely, the odds for the away team will lengthen, becoming more appealing to punters. If a majority of bettors believe that the underdog has a fighting chance, even if statistics say otherwise, the sheer volume of wagers can move the odds.
  • News — Football is a team sport, and the availability or absence of key players can dramatically affect a team’s chances. If a star player is announced injured or unavailable, the odds can shift in favor of the opposing team. Other information (like tactics, morale, or any other sudden or significant change) can come to light, impacting the potential result of the game and hence the odds. The timing of the news relative to the start of the game can influence the size of its influence on the odds.
  • External Events — Events unrelated to the sport can also influence odds. For instance, weather conditions can affect a team’s performance, especially if one team isn’t used to playing in certain conditions. Political events, financial downturns, or even unexpected global events can indirectly influence the odds.
  • Bookmaker Strategy — Sometimes, bookmakers adjust odds to balance their books. If they stand to lose a significant amount should a particular result occur, they might adjust the odds to encourage betting on the other side.

Those factors are most important pre-match. However, the odds are usually more dynamic during the match. During the game the most important events which influence the odds are:

  • a goal being scored or
  • a red card.

Bookmaker

The most consistent (and IMHO most interesting) cause for changing odds is wager volume. Bookmakers need to change their odds in order to balance their books. Balancing their books will ensure that they should pay out roughly the same amount regardless of the outcome of the game. As a result the bookmaker can guarantee a profit on the game.

Balanced books: (odds) × (total wagered) approximately the same for all outcomes.

It’s a risk management strategy. An illustrative example should help understand how and why it works.

Consider football match between The Bumbling Buccaneers (Bumblers) and The Hopping Hooligans (Hooligans). Suppose that the bookmaker sets the following initial odds:

Initial Odds: Fair Book

  • Bumblers — 2.0
  • Draw — 4.0 and
  • Hooligans — 4.0.

Inverting the odds we get the implied probabilities (50%, 25% and 25% respectively), which sum to 100%. This means that the bookmaker has a fair book.

Overround

The bookmaker quickly realises their error. After taking another look at the form of the teams and crunching the numbers they adjust the odds to

  • Bumblers — 2.0
  • Draw — 2.5 and
  • Hooligans — 5.0.

Now the implied probabilities sum to 110%. A reasonable overround.

Initial Wagers

After a while some punters have placed wagers:

  • Bumblers — £200
  • Draw — £100 and
  • Hooligans — £100.

The total amount wagered is £400. What would the bookmaker make on each of the outcomes?

  • If Bumblers won then the payout would be £400 (2.0 × £200) including the initial stake. Since the total amount wagered was £400 they would break even. ☑️
  • In the case of a Draw the payout would be £250 (2.5 × £100). This time there’s an excess of £150 profit! ✅
  • If Hooligans won then the payout be £500 (5.0 × £100). Since the total amount wagered was only £400, this implies a £100 loss. 🚨

One of three possible outcomes results in break even, another in profit and the third in a loss. Normally a bookmaker would want to make a profit (or at least break even) on all outcomes. They need to balance the books!

Shorter Odds on Underdog

The current odds on a Hooligans win land the bookmaker with a potential liability. They need to shorten those odds so that the payout on future Hooligans wagers is reduced. This would discourage punters from wagering on the Hooligans. The revised odds are

  • Bumblers — 2.0
  • Draw — 2.5 and
  • Hooligans — 4.0.

More wagers are placed at these odds:

  • Bumblers — £600
  • Draw — £400 and
  • Hooligans — £250.

The total of these wagers is £1250. What would the bookmaker stand to make or lose on each outcome?

  • The payout on a Bumblers win would be £1200 (2.0 × £600) including the initial stake. Since the total wagered was £1250 there would be a small profit of £50. ✅
  • The payout on a draw would be £1000 (2.5 × £400), yielding an excess of £250! ✅ ✅
  • A Hooligans win would also payout £1000 (4.0 × £250), also yielding £250 profit! ✅ ✅

This is a great improvement. All three options are now profitable. One small problem: a Bumblers win is less profitable than the other two outcomes.

Longer Odds on Favourite

Although all outcomes now yield a profit, a Bumblers win is much less profitable. The bookmaker needs to increase the odds on the Bumblers. This may seem counter-intuitive, but it works. Longer odds on the Bumblers signals to punters that they are less likely to win, and this should reduce the relative proportion of wagers on the Bumblers. The new (and final!) odds are

  • Bumblers — 2.2
  • Draw — 2.5 and
  • Hooligans — 4.0.

Since the game is imminent the wager volume is picking up, however, now there’s relatively less money being placed on the Bumblers.

  • Bumblers — £900
  • Draw — £800 and
  • Hooligans — £500.

The total of these wagers is £2200. How does the bookmaker fair now?

  • A Bumblers win would payout £1980 (2.2 × £900) for a profit of £220. ✅ ✅ ✅
  • A draw would payout £2000 (2.5 × £800) with a profit of £200. ✅ ✅ ✅
  • A Hooligans win would also payout £2000 (4.0 × £500) for a £200 profit. ✅ ✅ ✅

All three outcomes now result in a similar profit. The bookmaker has found his sweet spot and can start counting his profits with confidence.

Betting Exchange

The odds on a betting exchange like Betfair or Smarkets are much more dynamic than those offered by a bookmaker. The underlying reason for the changes are essentially the same. However, there are some subtle differences. I’ll dig into exchange dynamics in another post.

Conclusion

Odds are influenced by a variety of factors. Some of these factors are hard to predict (like news and external events). However, others are fairly deterministic, being determined by market sentiment and wager volume. If wager volume is not in keeping with the prevailing odds then a bookmaker will need to balance their books by adjusting the odds to ensure they are profitable irrespective of the match outcome. Understanding this strategy can help punters find value bets and potentially take advantage of skewed odds.