Betting on footie using trends is little better than flipping a coin to decide punts, some say. But Nick Pulford shows how some fancy statistical footwork and using your noggin can help you beat the odds.
Nothing polarises opinion about football betting more than trends. Some people swear by them, others swear at them. It pays to be pragmatic, though, because sometimes they genuinely work – and sometimes they don’t.
The real trick with trends is knowing when and how to apply them. The argument against using trends is that such patterns are random and, as such, there’s no guarantee they will be repeated. This point of view often cites the age-old example of the coin-toss, and the random patterns it can generate. If a coin is tossed three times, the argument goes, the chances of getting three heads is 7/1. However, if the coin is tossed 50 times, there’s almost bound to be an occurrence of three heads in a row. This doesn’t prove that three heads in a row is becoming more prevalent, nor that the 7/1 odds have been defied. It merely proves the randomness of such events.
This theory is all well and good, except no outside influences are brought to bear on a coin-toss. That’s why trends are worth following. In football, as in other sports, all manner of forces are at work – chiefly, the football skills and other human characteristics that influence the outcome of games. These produce patterns of results and, while many of them are random, some have enough logic to make them worthy of consideration.
Two types of trends we’ll look at here are statistical trends and patterns of results, and over the next few pages I’ll explain why no serious football bettor should place bets without taking them into consideration.
No one would dispute that there are strong statistical trends in football results – home wins account for around 45% of all matches, away wins make up 25-30%, and 25-30% of matches are draws, for example. These stats are drawn from hundreds of matches over the course of a season (and thousands over several seasons), yet they show little variation. The bookmakers are aware of them – and tailor their odds accordingly – and punters need to be aware of them, too.
However, there are a few less obvious trends that can provide a serious edge for punters. In-depth analysis before Euro 2004 identified several trends that might produce a profit over the course of the tournament. These were based on study of the previous six European Championships (1980-2000), which were the only ones to feature a single tournament with a group format.
Consider the following three trends (right), and the logic behind them, and decide whether you would have made a profit if you had followed them. It’s like one of those magazine questionnaires: do you prefer trend 1, 2 or 3? Answers at the end.
Trend 1: The high number of draws in the opening set of group games In previous tournaments, from 1980-2000, the draw rates in these games were 50% (1980), 50% (1984), 25% (1988), 75% (1992), 50% (1996) and 25% (2000). There were eight such games at Euro 2004, and three draws out of eight (37.5%) were needed for a profit. The downside looked negligible, with two draws out of eight the least that could be expected on past evidence and on the usual distribution of draws across all types of top-level football.
The logic behind the stats is that teams play more cautiously at the start of the tournament, knowing that defeat is usually fatal to their chances, and are happy to settle for a point.
Trend 2 The high number of goals in the final set of group games In previous tournaments, the numbers of these games that featured three goals or more were 25% (1980), 50% (1984), 25% (1988), 100% (1992), 75% (1996) and 63% (2000). There were eight such games at Euro 2004, with a profit depending on at least four (50%) being high-scoring (more than 2.5 goals). Again, that would be in line with the expected distribution.
The logic behind the stats is that this is the last-chance saloon for some teams, who must throw caution to the wind, while others (either already qualified or eliminated) can play with more freedom. The rising figures from 1992 could be due to more liberal rules, which give more advantage to attacking players.
Trend 3 The high number of draws at the semi-final stage Semi-finals were introduced in 1984, when both ended all-square. Since then, the figures were 0% (1988), 50% (1992), 100% (1996) and 100% (2000). One drawn semi-final at Euro 2004 would ensure a profit, although a 50% draw distribution is double the usual average. The draw-draw double result (that is, draw at half-time, draw at fulltime), which had occurred in four of the seven previous drawn semi-finals, could also increase the returns. The logic behind the stats is that semi-finals are cagey affairs, with neither side prepared to take risks. The finals of 1996 and 2000 were also draws, suggesting the cautious approach was becoming dominant.
Three of the eight games were drawn, giving a profit of £16.50 to a £10 level stake.
Seven of the eight games featured at least three goals, giving a profit of £48 to a £10 level stake.
One of the semi-finals was a draw (with a draw-draw double result), giving a profit of £14 to a £10 level stake on the draw, or £40 profit to a £10 level stake on the draw-draw double result.
The overall profit was £78.50 to a £10 level stake (or £104.50 profit including the draw-draw double result).
None of these trends carried a guarantee, but they did fulfil some of the key elements necessary for a trend to have some currency. First, the figures could be tested over several years and compared like with like; second, they were backed up by sound football logic; and third, there was little downside to the bets – fewer than two draws with trend 1, for example, would have been highly unusual.
Several bookmakers were alive to such trends – Coral and William Hill were both short of the draw in all eight of the opening group games – but there was only so much evasive action they could take.
PATTERNS OF RESULTS
Results patterns are more controversial. Many people argue that we can read nothing at all into the fact that two teams produce more than the average number of draws, or that one team is dominant over the other. Opponents of trends will say that any successes are a matter of luck and that there are at least as many times when trends will let you down. They will also point out that ten-year trends are meaningless in football because of the high turnover of playing and coaching staff.
However, a punter who bets without any appreciation of such trends is missing a vital piece of the jigsaw. True, trends aren’t the whole answer, but they’re part of the answer. I never back a team based simply on past result trends against certain opponents, nor do I ever make a selection without looking at the trends. In fact, one of my first ports of call when assessing a match is to look at the head-to-head record between the two teams (www.soccerbase.com is a good research tool).
It’s a constant source of amazement that tipsters apparently place such importance on team line-ups, while ignoring past result trends. One injured or suspended player – no matter how important he is deemed to be – is unlikely to have much impact on a team’s performance in a single match. To argue otherwise usually relies on evidence less well tested than supposedly unimportant result trends.
The key point is that football is a team game. The team is more important than individuals, and this is the best reason to concentrate on what a team achieves in the long term. Form is the most important factor to assess, but result trends can also be significant.
I don’t stick to any rigid cut-off point when looking at past results. If two teams have played at the same level for most of the past ten years, then I will probably take into account all those results, but give most relevance to the recent results.
Fulham are an example of a team with a short Premiership history (they’re now in their fourth season in the top flight), but their past results can still be a good guide. Against Arsenal, for instance, going into this season they had a record of five defeats and one draw even though, on paper, they have a team capable of posing the Gunners some problems. This pattern of results supported Arsenal’s form chance before their visit to Craven Cottage on 11 September, when they won 3-0.
Arsenal, admittedly, were expected to win that game, so let’s look at another Fulham example. Their first home game this season was against Bolton Wanderers, who had failed to beat the Londoners in six previous Premiership meetings (home and away) and had lost on all three visits to Fulham, but arrived this time on the back of a 4-1 opening-day home win over Charlton Athletic and were soon to go unbeaten against Liverpool, Manchester United and Arsenal. The result? 2-0 to Fulham. Despite Bolton’s form, Fulham emerged as winners. Past results between the sides couldn’t be the sole reason for selecting Fulham, but it was difficult to dispute that it had some relevance.
It’s all in the past
Past results, after all, are just another source of form, and they can reveal quite a lot about a team’s characteristics. Most fans would agree there are bogey teams that always seem to cause their own team problems year in, year out. Such observations can’t be wrong across the board, and part of the reason is that a team’s playing style is apt to change more slowly than its personnel.
Ask a football fan to characterise Spurs, for example, and he would probably use words such as flashy or attacking. The same words might also have been used 30 years ago. If this characterisation is correct, it may explain why Spurs fare so poorly away to the best teams, who over the years have been able to match them for attacking ability but are superior in defence.
Top teams have a good balance between attack and defence, and most football watchers would agree Spurs have failed consistently to bring their defence up to the level required to compete at the highest level. It remains to be seen whether new boss Jacques Santini can effect a lasting change in this department, but Spurs’ past defensive weaknesses probably explain why their Premiership record is so poor at Manchester United (played 12, won none, drawn one, lost 11), Arsenal (P12, W1, D5, L6), Chelsea (P13, W0, D5, L8) and Liverpool (P12, W1, D3, L8).
Ah, you might say, but shouldn’t we expect such results from Spurs? Well, three other middle-ranking teams have been full-time members of the Premiership since its launch in 1992 – Aston Villa, Everton and Southampton – and all three have gained more points than Spurs in away games against Manchester United, Arsenal, Chelsea and Liverpool. And that’s despite Spurs being a better team overall than both Southampton and Everton for most of that period. This is just one example of how logic and analysis can be applied to trends.
Of course, it isn’t necessary to go to such lengths to validate every trend, and not every trend will have real significance, but it’s clear that patterns of results, just like statistical trends, do merit a second glance.
USE THE TRENDS TO AVOID BAD BETS
There are certain types of bet where punters are at a serious disadvantage unless they possess a thorough understanding of the statistical trends.
One such example is goals trends, where the bookmakers are very much on the ball, making it hard for the punter to find an edge. The statistics show that there’s little overall variance in the average number of goals scored per game. In the Premiership last season, for example, the average was 2.7 goals a game, and in the three lower divisions, it varied only a little, at 2.5 or 2.6 goals a game.
This average is repeated season after season, and not only in England, either: Italy’s Serie A, which is supposedly less attacking than English football, had an identical goals-per-game ratio as the Premiership in 2003-04. As such, the bookmakers set their goals line at 2.5 goals – asking the punter to bet above or below the average.
As there’s a fairly even split between the number of games above and below the average – in the Premiership last season, the split was 189 games/191 games – and the bookmakers build in a margin to their prices (often making both eventualities odds-on), the odds are against the punter over the long term.
For this reason, it makes no sense whatsoever to bet on goals scored based on factors such as a team being on a good scoring run or the fact that a match features two attacking sides – this approach must lose in the long term.
The upshot is that the only way to beat the odds is to identify a statistical glitch in the overall trend, and these are few and far between. In short, this type of betting is best avoided unless you do find a statistical edge.
TOP 4 DOS AND DON’TS OF TRENDS
Trends, ideally, should satisfy certain key criteria:
1.) The figures need to be tested and cross-checked as far as possible, comparing like with like.
The examples from Euro 2004 used in this article drew on research from previous European Championships going back to 1980 – it would have been pointless and misleading to look at earlier European Championships because they didn’t use a group format.
2.) More recent results tend to be a better guide.
If the stats show a decline in a particular trend, it’s best to be wary of applying that trend in future. With the Euro results, for example, you would want to see that any trend had worked well at the 1996 and 2000 tournaments before accepting its relevance for 2004.
3.) Trends should also be backed up by sound football logic.
This is a subjective exercise, but it’s no use watching a lot of football and then not applying the knowledge gained when it comes to placing your bets. In fact, many trends can be unearthed by asking questions based on conventional football wisdom – the answers may support or contradict the widely held view, but either way could give the clued-up punter an edge.
4.) It’s an advantage if there isn’t much downside to bets based on trends.
This is one reason why trends based on a group of matches, rather than individual games, are a safer bet, as they spread the risk and put the percentages more in the punter’s favour. Beware, though: trends based on a small sample of matches may still work, but they carry a higher risk.