Following up the successful 2016 Summer League Campaign, here is our complete report on the **2016-17 Winter League Campaign**, based on 18 different top flight leagues.

We will try to avoid repeating what was said in the summer league article so that it is all new information for you here.

For the sake of completeness, you should still **read and digest** both reports for a full idea of our strategies and thought processes.

And you will find the current stock of available HDAFU tables **via this link**.

# 2016-17 Campaign Report

## Measures of Risk

Before beginning to plan any portfolio or placing bets, you will need to review your analyses and rank the systems you have found according to risk exposure based on the values of the upper inflection point odds.

This will allow you to compile a portfolio with a healthy balance of risk, which is essential to the success of any investment plan.

Here is our rough guide:

**Low Risk**(Probability 45.00% or more; upper inflection point maximum odds of 2.22)**Low-medium Risk**(Probability 44.99%-35.00%; upper inflection point maximum odds of 2.85)**Medium Risk**(Probability 34.99%-22.50%; upper inflection point maximum odds of 4.44)**Medium-high Risk**(Probability 22.99%-16.00%; upper inflection point maximum odds of 6.25)**High Risk**(Probability 15.99% or less; upper inflection point odds above 6.25)

Discretion is used if a system does not fit these parameters or crosses two or more classifications – In these cases, the **harmonic mean odds** of all the games in the set is used as the benchmark to guage risk. The Excel formula for a range of odds in cells A1 to A100 would be: **=HARMEAN(A1:A100)**

## Measures of Success

You will also need a definitive framework to be able to judge the final results.

For us, the final results of any league fall into four distinct categories:

- Systems that achieve a six-season-high (i.e. profits larger than any of the previous five seasons). (
**Over-Achievers**). - Those that make a profit over and above the size of the initial stake (£100 in our case), but fall short of six-season-high results. (
**Achievers**). - Strategies that break-even or, record a tiny profit or loss up to the size of the initial stake (£100 in our case). (
**Zero-Sum**). - Leagues that make a loss over and above the size of the initial stake. (
**Losers**).

You can already see that two of these outcomes are favourable, one is neutral, and only one is detrimental.

# 2016-17 League-by-League Review

Let’s have a brief look at each league to see how our 22 systems fared. *(Alphabetically according to the tab codes in the workbook)*:

**1. AUS1 – Austria Bundesliga – Whole Season System**

**Medium-high**

Only eight of 28 bets won, but this was enough to see a profit of **£882.00**. Hit rate and yield were both below the calculated averages and the resultant profit figure was lower than any of the five previous seasons’ figures.

Result: **Achiever**

**2. BEL1 – Belgium Jupiler League – Whole Season System**

*Up to, but not including Europa League and Championship Group splits*

**Medium**

Both the estimated hit rate (33 out of 97 bets won) and yield figures were surpassed by wide margins, leading to a six-season-high profit figure of **£3,108.00**.

Result: **Over-Achiever**

**3. CZE1A – Czech Republic 1. Liga – First Half Season System**

*Up to the 04/12/2016 winter break*

**Medium**

Nine out of 22 bets won, and whilst the hit rate and yield both outstripped expectations, the profit figure settled at **£1,247.00**, the fourth largest in the last six seasons.

Result: **Achiever**

**4. CZE1B – Czech Republic 1. Liga – Second Half Season System**

*From 18/02/2017 start of the second half of the season*

**Low**

This one suffered its worst result in the last six seasons, but the resultant loss was minimal at **-£310.00**.

Result: **Loser**

**5. DEN1A – Denmark Superligaen – First Half Season System**

**Medium**

This was the only system employed in this league purely because the format of the second half of the 2016-17 season was to change from previous seasons.

Although hit rate and yield were both below estimates, the system still recorded its third highest total for six seasons at **£1,238.00**.

There were twice as many bets than expected *(largely due to the fact that around 40% more games than usual were played in the first half of the season to accommodate the new second half season format)*.

Result: **Achiever**

**6. ENG1 – England Premier League – Whole Season System**

**High**

This system suffered the longest losing streak we have ever encountered, almost 14% worse than expected, for a very painful 36 straight losses. *(A six-season-low)*.

However, the situation was mostly recovered by three big winners all carrying odds of over 12.00, for a final loss of just **-£32.00.**

The last six bets of the season lost, but had only one of these been a winner, this system would have returned a profit. Small margins.

Result: **Zero-Sum**

**7. FRA1 – France Ligue 1 – Whole Season System**

**Low-medium**

Hit rate and yield were both below par, but the league turned in a steady performance for a profit of **£1,634.00**, ranked fifth largest in the last six seasons.

Result: **Achiever**

**8. FRA2 – France Ligue 2 – Whole Season System**

**Low-medium**

The same story as France Ligue 1, but with a profit of **£2,801.00**, for its third largest profit figure in six seasons.

This one was unusual for a much higher number of bets than expected. (215 vs. 119 estimate – Profit was at £2,523.00 after 119 bets).

Result: **Achiever**

**9. GER1A – Germany Bundesliga 1 – First Half Season System**

*Up to 21/12/2016 winter break*

**Medium-high**

Another below par system, but one that still achieved a profit of £1,098.00. (Fourth largest in six seasons).

Result: **Achiever**

**10. GER1B – Germany Bundesliga 1 – Second Half Season System**

*From 20/01/2017 start of the second half of the season*

**Medium**

The very rare inclusion of a system with two non-profitable seasons (the oldest two) in the previous five.

It featured one more bet than expected, which won, to total one more winner than expected. Hit rate and yield both exceeded estimates for a profit of **£1,294.00**. (Fourth largest in six seasons).

Result: **Achiever**

**11. GRE1 – Greece Super League – Whole Season System**

**Low-medium**

The hit rate here was almost 8% below estimate and resulted in the worst performance for six seasons, and a loss of **-£819.00**.

Result: **Loser**

First of all,well done!

And I know you are now expecting a but.

But I’m going to be slightly negative.

Isn’t it quite unlikely that most people would be able to bet £100 stakes 1000 times a year without either not getting the price on betfair or getting restricted or even banned by bookies?

I dont know if that’s the case because I dont bet on 90 minute markets but going by what I’ve read online I suspect that it isn’t easy to make £20,000 from betting such markets without problems.

Also,may I ask whether you had Frej to draw or win at Sirius in late October 2016?

Hi again

Just something that occurred to me when placing bets over the weekend, and I wondered if it was something you had ever looked into…

When using a back the draw system, I feel much more comfortable backing the draw when the two teams are relatively well matched than I do when there is a strong favourite at home. Even though both matches might fall into the odds range, it would seem likely that the former would have more chance of actually ending in a draw than the latter – I often wonder if the odds for the draw aren’t just a balancing figure?

Anyway, this led me to wondering whether you had ever given any consideration to HO/AO quotients when considering systems that back the draw? Its something I was thinking about looking into with my current systems to see if there’s anything in it…

Hello Scott,

Bookmakers rely to a huge extent on the psychology of punters who (wrongly) believe that lower priced favourites have a better chance of winning all the time. As a result, favourites are usually under-priced because the majority of punters want to bet on them. People are by very nature risk-averse. Give someone the choice of a 1.20 favourite or an underdog at 8.00, and nine-out-of-ten punters will opt for the favourite.

The weight of money therefore received by the bookmakers on big favourites drives their prices (odds) even further down as they attempt to balance their books. You must therefore appreciate that in order to achieve as much parity as possible, the bookmakers will reduce prices on the favourites to manage/control the extent of risk (liability), and raise prices on the draw and/or the underdog to attract money on these outcomes. Only by performing this juggling act can they achieve as close a balance as possible between the three outcomes. And of course, heavy favourites do not always win. In fact, they win less often than their (often under-priced) odds imply. This is how bookmakers make their margins.

All I can say is don’t fall into the trap of this false-belief system about a shorter price having a better chance than a longer one. Odds prices are purely a measurement of the popularity of the event (

odds are driven by public opinion), and often bear no resemblance to the probabilities of the outcomes.Just about the only time when prices are set according to historical results and statistics, plus some anticipation of what the public will think, is at the very start of the market when bookmakers publish their initial prices.

Stand back and look at the situation from a distance. There are three outcomes: home win, draw, away win. The prize is behind one of these doors. Which door are you going to open? The chance is a basic one-in-three before you begin to take into consideration any extraneous factors affecting the fixture in question.

In answer to your question, both the draw odds and the underdog prices are balancing factors. The economics of the situation in response to human nature says that they have to be. But think again. The home odds are also a balancing factor. Only one of the three outcomes can happen – the money riding on the other two needs to offset the payout on the winning outcome, and hopefully provide a small margin of profit at the same time. The bookmakers can never achieve this on every single match, which is why they employ a huge portfolio of games to bet on each week. An overround of 5% on their entire book of matches per week is enough to create handsome profits during the course of a season, even if they don’t make a profit every week.

The profits to be made from gambling, from either side of the fence (bookie or punter), are a pure numbers game. The larger the portfolio of bets with overround/value on your side, the more exponential the profits are.

Regarding Home Odds/Away Odds quotients, this is something we explain in great detail in our

Odds Calculation Course(using the Over/Under ‘X’ Goals market as the example).There are many ways to skin a cat. Using inflection points and using quotients are just two of them. My advice is to get used to one system and stick with it until you master it. Don’t try and become a ‘Jack of all trades’.

Believe me, the time it takes to try and juggle too many different approaches and get them all finely-tuned at the same time is not worth the effort.

I hope this helps and thanks for the interesting questions!

Hello Soccerwidow!

Firstly, I’d like to thank you sincere for the great job you are making. All the forecasting is really based on fundamental thinking and statistics, and not on enthusiasm, which gives us (the punters) the opportunity to earn money for the long term. I’ve managed to understand the logic base of your system and I would say it’s a quite impressive job.

In the same manner, I would like to ask you some questions regarding the odds that you use for statistics and betting:

1. What odds do you use for historical statistics? Example: football-data.co.uk there is a paragraph that offers statistical information for several leagues. They have odds as: averages of the bookmakers, for different bookmakers apart and closing odds of Pinnacle. What are the best odds to use for identifying the inflection points? Personally I chose the average odds, as I intend to make the bet 1 day before the matches (Please correct me if I’m wrong 🙂 ).

2. When is the best time to place the bets? As I said, for me is optimal to place bets one day before the match starts. But as you know, the odds are moving and sometimes some matches that has been picked up (the odds are in the established range) can go out of the range till the start of the match. In result what is the best time to place the bet and what historical odds should be the base for identifying the inflection points?

As I understand these to elements should have some correlation between them.

Thank you for your support and the great job you are making!!! It really is something interesting and totally different from the information existing on the web.

Hi Andrei,

We do not use football-data.co.uk for odds in connection with the HDAFU system betting tables.

The odds they use are taken at different points in time and do not provide a reliable benchmark (Joseph at Football-data.co.uk has advised me that odds are collected around 6pm on a Friday in advance of weekend/Monday games, and around the same time on a Tuesday for midweek games).

To state

what is actually said on their site: “Fixtures and betting odds for upcoming games are made available, collected Friday afternoons for weekend fixtures, and on Tuesday afternoons for midweek games”.We use the highest odds as near to the close of the ante post market as we can find, and Oddsportal is the only site currently providing this.

Many people have asked the same question on the best time to place bets. To save myself from repeating anything, please read the comments above, and also the comments on the

Summer League summary. You should find all the answers you are looking for.Thank you for your kind words and best wishes.

Hi Right Winger,

regarding Ratchet & Stop-loss Simulation I don’t completely understand how ratchet system works. The first trigger +5% is when profits are 1947.00 (cell K1850). The second trigger is +15%, from 105% to 120% at cell I1854 although the profit increase from the last trigger is just 2631.3 units (4578.3-1947). And the next increase at cell I1855 is 15% although profit increase from the last trigger is just 2619 units. As far as I understand in these both cases increase should’ve been 10%, so why it’s 15%?

Hello Jo,

Sorry for the delay in replying – we are currently on holiday for the first time in over four years 🙂

As per the article, the 5% increments are based on whole 000’s profit. There are four whole 000’s in 4,578.30, hence why it is 4 x 5% = 20% increment.

The ratchet triggers are when the profit figure exceeds by at least 1,000 the previous highest profit point.

The first trigger was at 1,947 (containing one whole thousand = +5% increment on original stake). The next trigger was activated at 4,578, the first time 1,947 was exceeded by 1,000 or more. (4,578 contains four whole thousands = +20% increment on original stake).

I hope this is now clear!

What can you say about my new portfolio, I have 28 strategies left, numbers and percentages are:

5 or 17% low, 5 or 17% low-medium, 5 or 17% medium risk, 8 or 28% medium-high risk and 5 or 17% high risk strategies.

Hi Jo,

Looks like a much better balance than your initial effort.

On face value, I would be happy with these numbers.

Happy hunting!

Hi Jo,

Personally, I don’t think it matters a great deal.

The only important thing with the new format in Denmark is not to include any Relegation or Europa League play-off games in your strategy.

Also, expect fewer numbers of games entering your inflection points in the second half of the season as there are fewer ‘league’ games after the winter break now.

Check out our

Summer & Winter League Calendarfor a full summary of what to include and what not to bet on in each league.Hi Michael,

I think I have answered this one before to some degree. (Page 2 of this article I believe?).

We were aware that the Danish league format was changing in the second half of the season, hence why we chose to include just a first half season system.

The new first half up to the winter break included straight-forward league matches, just as any other season before. The only difference likely was that there would be more matches encapsulated by our inflection points.

Therefore, for all intents and purposes, the league was no different up to the break than before – just league games during the same part of the year in accordance with the analysis.

Thanks for sharing your Summer League success story – keep in touch and let us know where you end up!

All the best.

Hi Right Winger,

since Danish league had only 1 season in new format, would it be better to skip the 2nd/whole season strategies from betting in the upcoming season?

Hi Soccerwidow

Please could you explain why you went with a system in Denmark despite the 2016/2017 season being the first season after major structural changes?

I would have thought that that was risky in the sense that historical data is now not directly comparable to the new format.

Asking because there’s other leagues with the same problem for the upcoming season, eg Bulgaria / Ukraine.

Been having some good success with a summer leagues system thanks to your work, with roughly £1,200 profit since March.

Thanks

Hi RW – sorry, but I’ve got a question you’ve probably been asked a million times about placement of bets.

I’m currently sorting out getting some money onto Vodds in preparation for the winter season starting, and obviously anticipate being able to access the upper end of the odds range as a result.

My questions are:

1. In terms of bet selection, should I only be placing the bet if the max odds on oddsportal are within my strategy range? I’ve got a summer league campaign running at the minute and I tend to use the upper range as a guide but I always check if the top price looks anomalous – if it does, and if I can access odds within my range, I’ll place the bet. However, I’m never sure if I’m “breaking protocol” here and should be using the top price as the decision point, anomalous or not….I’m conscious there might not be a right answer to this but could you please expand a bit on how you weight your decision on selection.

2. TIming is the other question. I’ve tended to look at the odds an hour or so before K-O and made my decision at that point. However, on occasion I’ll have a cheeky look just before K-O and can sometimes see that the odds have shifted markedly and I’m now in a position where I should be placing a bet. Should I ignore this and not place the bet, or is this now deemed an appropriate selection based on the late odds movement?

Thanks again!

Hello Scott,

To answer your questions seriatim:

1) Yes, place the bet in accordance with the highest odds shown in Oddsportal, and yes, it is always a good thing to check for and preclude anomalous odds that haven’t updated for a while.

As previously mentioned, we try and iron out the anomalous odds when putting together the analyses, and for the sake of good order, you should try and do the same when judging whether to place the bet if it is close to the outliers of your odds range.

2) The HDAFU analyses are based on odds as close to the end of the ante post market as we can get them. If towards kick-off you realise that the odds have shifted a bet to within your inflection points then, yes, it is a valid bet to place.

I hope this clarifies.

Hi – thanks for your reply, and apologies for my delayed response to it. All makes perfect sense, thanks again for taking the time and for your excellent website.

Hi Daniel,

As mentioned in the article, the odds splits for the risk analysis are a ‘rough guide’ to get readers thinking about the composition of their portfolios, and to encourage people to balance their portfolios with an even spread of risk.

The classifications stated for our 2016-17 portfolio are based to some degree on discretion (also mentioned as an adjustment factor above), and you will see from the 2016-17 Campaign workbook that some of our systems did indeed cross the thresholds of several odds’ bands.

When this happens, we can never be truly exact but we can say from the start that the majority of the bets will fall into one or another of the odds brackets.

Using the example you mentioned, in a system covering a range as wide as Greece between odds of 2.13-7.40, we know from the outset that there will be more bets at the lower end because it is a home win system. Indeed, the analysis showed the harmonic mean odds for the matches between these inflection points as 2.97, which further validated our decision to classify this system with low-medium status.

The harmonic mean for the 110 bets placed was just over 3.00.

As a reminder, the harmonic mean formula in Excel is

=harmean(a1:a10), if the range of odds you are looking at encompasses cells A1 to A10.Perhaps our readers will come up with better ways of gauging the risk content of their portfolios, but the overarching message we are putting across in this article is that

a healthy balance should always be sought.It’s not an exact science, maths never is, but hopefully we have guided you in the right direction.

Another great question – thanks again!

RW,

I think you did a great job with explaining how you gauge the risk of the system within the context of a portfolio of systems.

When getting the balance in mine as even as I could I relied to an extent on the workbook of your previous campaign to see how you yourself classified a system, taking into account things like the odds range, hit rates, yield, number of bets e.t.c. So it was interesting to see based on these things how you rated your own systems. I then looked at my own systems to see how they looked in terms of risk.

I found the low risk and low-medium risk the easy ones to classify. I look for those systems to have a good length of winning streaks, low length of losing streaks, 50-60%+ hit rates, and of course meeting the 4 of 5 seasons in profit and 10%+ yield. Most of these systems have relatively small odds ranges.

The ones I found a little more difficult to classify were those that had odds range more spread out, like the Greek example you gave. So applying the harmonic mean to it, gives that extra view point that I found helpful to see how risky a system is based on odds the majority of bets placed will be at.

What I had done was analyse each league to identify the systems and then make a spreadsheet that listed each system for whole, 1st half, 2nd half, and show each of the systems features i.e hit rate, zero odds, yield e.t.c

From that I selected those that I felt gave a balance and listed them in order from low risk to high. Applying the harmonic mean odds to each system then showed that the odds increased from low to high, which I think validated that I have my systems in the right sections of the risk profile and have a decent balance.

That’s something I found useful in getting something I was finally happy with.

Now, very much looking forward to the weekend to take things “live”.

Good luck everyone and I wish you all the best for the upcoming season!

Hello Right Winger,

i am in the final stages of the analysis and i wanted to ask you for an opinion about the spread of risk of my portfolio. I have just selected the best systems (as far as i can tell) from each Championship, 39 systems in total. I have selected 4 low risk, 8 low-medium, 11 medium, 3 medium-high and 13 high risk systems. The ratio in % is: low 10%, low-medium 21%, medium 28%, medium-high 8% and high 33%. Looking at the spread on your campaigns i notice that i have slightly more systems at the upper and lower end and less in the medium range. So i want an opinion from you.. what do you think about my spread? Do you find it balanced or should i fine tune it to balance it more?

Thanks, i’m really looking forward to the beginning of this season (in a week or so for the early championships)!

Hello Daniele,

I would be happier with a more even spread across the board.

With fewer bets at the lower odds range, your portfolio will find it difficult to make-up for the losing streaks at the higher odds range.

Whilst Jo’s portfolio (see 6th July above), has a chance of making money (as it is biased towards lower risk), I think your current arrangement will struggle more.

Increase the low risk and medium-high risk bets and reduce the high risk bets for a better balance.

Good luck!

Thanks for your answer.

I noticed though that in this article you stated that you chose a spread of 4 low, 6 low-medium, 6 medium and 6 high-medium/high, for a total of 22 systems. Looking at the spreadsheet of the campaign I see that the inflection points guidance as per Page 1 of this article does not exactly match what is stated above, and if we analyze the maximum inflection points of each system we count 3 low (max inflection point of 2.22), 2 low-medium (max inflection point of 2.85), 8 medium (max inflection point of 4.44), and 9 medium-high/high systems. Could you please clarify on this matter?

For example, a system in your campaign have odds from 2.13 to 7.40. Don’t you classify it as high risk system? Or another system has odds from 4.25 to 5.25. Don’t you classify this as a medium-high system?

I understand that the first system spread across all 5 categories, and the second have a spread between medium and medium-high. So how do we decide in which category they should fit in?

Thanks!

Hi Right Winger,

can you explain more in detail how do you compile Inflection Points graph? Odds are ranked from 1 to 200 in both summer and winter leagues campaigns. In Summer league campaign every number is repeated 4 times 7 times in a row, and every 8th number is repeated 5 times in a row (8, 16, 24 and so on). As I understand it’s because you get round cluster size number for odds rank no. 8 – 33.000, then for 16 – 66.000 and so on. Or, whenever you get closest to round number, for instance in winter league it’s odds rank 7 and cluster size of 63.980. Regarding my own portfolio, to make my own inflection points graph with data taken from HDAFU tables of the 2016-2017 winter leagues season, there are 1452 bets. 1452 divided by 200 equals 7.26. I tried to calculate the right sequence how to spread and repeat odds rank numbers evenly across those 200 and it didn’t work out. I finally finished with 202. But numbers of odds rank in some cases are repeated for 7 times and every 8th number for 8 times and then I have intervals where same odds rank numbers are repeated for 7 times 15 times in a row. A bit chaotic, but just to finish “ranking” around 200 because I struggle to calculate the right sequence. It was not the easiest thing to explain, but I hope you understand what I mean.

Hello Jo,

Yes, I know exactly what you mean and I think you have described it rather eloquently.

And I’m afraid my answer is going to disappoint you.

I’m sorry but this is one of our ‘trade secrets’, and we are not prepared to divulge or give away for free this part of our intellectual property.

The clustering sequence is just a small part of the HDAFU table compilation process. There are other bits of the jigsaw you haven’t mentioned, which are also essential to know and get right when putting the tables together.

And some of the formulas needed to calculate vital areas of the tables will not be found in the actual tables themselves.Of course, from a personal perspective, I am 100% proficient in putting the tables together. I’m very fast as I know exactly what I’m doing, and even have the raw data set-out in an optimum design to copy and paste nicely into the template.

But even at a lightning pace, it still takes me at least 20 minutes to put a single table together (more than an hour for one league), and then more time to review that everything is okay and cross-checking nicely.

Today’s product is the culmination of several years of work. We allow people to buy the tables but I’m afraid we will never reveal the recipe for making them.

And I would strongly advise against anyone trying to copy them as, if you don’t have the various formulas for certain parts of the table, you will not even know if the information you receive from your end product is correct or not.The probable knock-on effect would then be reliance on a totally false picture, which will only lead to disappointment (at the very least) when it comes to investing money on it.

This is therefore our health warning – put together your own tables at your own peril!There are over 100 steps involved, many of them requiring to be performed in a certain order – cracking the exact code and sequence is probably akin to the old statistical theory of countless monkeys on countless typewriters. (

The Infinite Monkey Theorem). Good luck to anyone who can do it!Sorry again Jo!

No problem Right Winger, I understand.

Regarding my portfolio, after your previous comment I made a lot of changes and now instead of low risk strategies, medium risk strategies makes it unbalanced: 19% low risk, 25% low-medium risk, 51% medium risk and 3% medium-high risk strategies. 31 strategy in total. I checked everything thoroughly and making any better balance would mean to exclude some strategies or leagues from betting. What can you say about portfolio when higher risk strategies, in this case medium risk, are dominant over the others? Is it a good idea to exclude some of them to make the portfolio more evenly balanced? Just two of all strategies have zero odds higher than first inflection point, but no more than 0.04.

Hi Jo,

I think I would be a little uncomfortable with a portfolio biased towards medium risk strategies.

You have a fair enough representation of low/low-medium risk systems, but the higher end, in other words, medium-high and high risk strategies is hardly represented at all.

With the portfolio you have suggested I imagine that you may see a profit, but it won’t come close to the type of figures we achieved in the 2016-17 Winter League Campaign.

You need the higher odds bets to make the money. The smaller odds bets create the safety net to allow you to speculate on the higher risk bets. This is a key element of the portfolio approach.

The old adage ‘speculate to accumulate’ applies to any form of investment – life is one big gamble in general. If you don’t include room to speculate in your portfolio, then I imagine you will perform a lot of work placing many bets, with perhaps a less than satisfactory outcome at the end.

You could be looking at a yield far less than 10%. Too many small odds bets will make it harder to recover losses. See also my answer to Simon from yesterday at 1.51pm.

In summary, I think your suggestion has the potential to make money, but you’ll have to have an exceptional season to see a profit size that will make all the work worthwhile. If your season is as bad as the reality check on page 5 of this article, you may even lose money.

But if you’re looking for an introduction to gain a little experience running a multi-risk portfolio, then go with it. If it is going to lose, I think it will lose slowly, giving you the option to cut and run if you get fed up with it.

I hope this is useful.

Thanks for the reply, that makes sense. Focus on the best only.

At present the 3.22 – 3.68 odds cluster is the one I had chosen for that league for the 1st half, and would be one of the medium risk systems. Then for the 2nd half in that league there is a solid favourite system that I had chosen as a low risk.

I think I’m almost there really when it comes to the portfolio – but am just tinkering to see where I can make things better, if that’s possible.

There are 20 systems I have assembled in total; 4 low risk, 5 low-medium risk, 6 medium risk and 5 medium-high/High risks. In fairness I have modelled it in large part on the successful one you illustrated, to get a similar balance.

I’m not a high risk type of person though, preferring moderate risk with a tinge of something higher risk included. Some of the underdog systems I have analysed with big profits but come with between 20-30 game losing streaks are something I’d rather stear clear of! With what I have now, 6 of the systems have double figure losing streaks, but all under 20. That’s palatable for me especially as the lower risk systems balance that out with the longer winning streaks.

I know I won’t make the portfolio perfect (doubt that is possible anyway) since this is my first attempt, but overall I’m happy with the way it looks so far. All that remains is to see how it fares in a couple of weeks when the first games start.

Hello again Simon,

Don’t worry, there is no such thing as the ‘perfect portfolio’ but I’m afraid you will need to get used to the ‘high risk’ element as it is a vital constituent of the whole mix, especially if you are going to achieve profits worthy of the time you’ll need to run the operation.

Bookmakers rely to a certain extent on the psychology of the majority of punters to make their profits. People tend to back lower priced favourites (usually under-priced) because they think they are more likely to win, and also because they are scared of backing a rank outsider.

Running a mixed risk portfolio allows you to gamble on the higher prices (and reap the higher rewards), because the lower priced bets provide a safety net.

It sounds like you have a good understanding of the concepts we have outlined, so, good luck – hope it all goes well for you!

I won’t mention the particular league this question relates to so as not to give away any specific content, but was wondering if I could get an opinion on something please.

It’s a first half workbook, and of particular interest to me is the draw bet type, which gives a reasonably profitable medium risk (I think) system. The profit curve increases smoothly from odds of 3.22 up until 3.38 and then levels off briefly before dropping off and then increasing again smoothly.

So it seems there is sweet spot in the lower odds range, followed by a brief period of statistical noise and then another decent profit increase. So I looked at 3 things in detail here; the first rising portion of the curve, the second rising portion, and then the entire curve.

I found the following:

Odds 3.22 – 3.38: Profit 5072, zero odds 2.43, hit rate 41.13%, yield 35.97, 28 total bets, losing streak 8.

Odds 3.5 – 3.68: Profit 4659, zero odds 2.73, hit rate 36.6%, yield 30.45, 31 total bets, losing streak 9

Both of those sets of odds ranges were in profit 4 out of 5 seasons. The gap between the 2 systems is the statistical noise you mentioned in the article.

Then I looked at Odds 3.22 – 3.68 to see what effect the statistical noise had on the outcome, and found this….Profit 7536, zero odds 2.93, hit rate 34.17, yield 17.28, 87 total bets, losing streak 9. Interestingly it was in profit 5 out of 5 seasons.

My first option would be simply to go with the system with inflection points 3.22 -3.68, which to me looks good. I could also go with the entire odds range of 3.22 – 3.68 to access the higher profit at the expense of hit rate, yield, and having to place more bets.

Then I thought to myself, well why not just run both systems for the first half? They don’t conflict with each other, they are the same bet type in the same league, all I’m doing is cutting out an unprofitable section between 2 very steady portions of the curve. And by doing so I would increase the 5 season profit by 4659 and only need to place 30 extra bets, taking the total estimated bets for this first half system to 59.

Does this sound feasible to you given the figures I have found? Or would I be better served here by just going with the 3.22 – 3.38 system?

Thanks.

Hi Simon,

For us, the decision is not to run split systems in the same league.

As mentioned in

Page 1 of the User Guide, we have found that the synergy effect gained of running only the best single system from a league is detrimentally affected if you begin running competing systems in the same league.Therefore, we would suggest choosing just one of the three options you have outlined. Either go with the longer 3.22-3.68 cluster (more bets but higher potential profit), or choose one of the two segments within this cluster, i.e. the 3.22-3.38 or 3.50-3.68.

Of the two smaller segments, the first is better (higher profit, fewer bets).

Ultimately, the choice is yours and is probably easier to make once you have a rough idea what the risk profile of your portfolio is after you have highlighted the best systems in each league.

Remember, try to keep the portfolio as a whole as balanced as you can. Choose whichever system adds or maintains balance to the portfolio as a whole.

I hope this is clear!

Hi again, RW. I am very excited to the upcoming season in applying all the knowledge learned here in the last few months.

A couple more questions:

1) I found very healthy inflection points in 2nd divison leagues of England, Italy, France and Germany. You held to France only. Is there a specific reason? Also, these other 3 have very good liquidity. Why not them? Aren’t they better and more liquid than Croatian, for example?

2) About odds movement: would it be correct to collect data from footballdata (friday 18h) and oddsportal (closing odds) to compares odds movement per league and per bet type (HDAFU) to try to antecipate betting movements? That would help, in my point of view, to place bets before the one hour ante post. Does that make any sense or it is impossible to antecipate those movements due to news about the teams at the last hour or so? Does this enormous effort compensate? Also, oddsportal collects opening odds x closing odds. Now, that would be enormous work because one cant copy paste these data. Please, some kind words about this topic.

Best regards!

Hi Gabriel,

Your question is worthy of a series of articles, so I will try and be brief!

We tend to look at only the top-tier leagues in each country because they are far more stable in their composition than any of the leagues below (and therefore give more reliable results).

For example, in France Ligue 1, 65% of teams have been ‘ever-present’ in the five seasons from 2012-17 (and also in the five seasons from 2011-16). Compare this with Ligue 2, and you will see that the latter has only a 35% rate of ever-present teams during those same periods.

The fact that the composition of lower leagues is so greatly affected by teams leaving/joining as a result of relegation/promotion creates a good deal of statistical noise. Results just aren’t as reliable because there are fewer games involving the same ‘established’ teams each season.

Ligue 2 is the only second tier we look at purely because of the prevalance of one particular bet type, which is almost unique to this league.

In reply to point 2, unfortunately, Football-data.co.uk collects its data at two separate times during a week. Fridays for weekend games and Mondays (I believe) for midweek games, which is why we need a more reliable benchmark for odds.

Oddsportal includes time stamps for when the odds were recorded and also red/green arrows indicating which way the odds have moved (from the opening odds of each bookmaker to the odds currently displayed).

If you study Oddsportal from the opening of the market in any particular round of games not yet played and watch/record the odds as they change during the ante post period, then you will have a good idea of how the market moves. I can say that with a lot of experience watching odds movements, the trends are fairly predictable, and help us judge when we can place bets at optimum prices.

This also helps us avoid congestion on days where we can see there may be a glut of bets all needing to be placed within a short space of time – we can place them further in advance and still get prices within the inflection points, sometimes a lot better than the closing odds.

Therefore, there is no need to collect data from more than one point during the ante post period for the inflection points analysis.

I hope this helps.

hi Right Winger,

my current portfolio with 30 strategies has uneven balance of risk. 40% low risk, 16% low-medium risk, 33% medium risk and 10% medium-hight risk strategies. Majority, 67% of them, have no losing season out of 5 and substituting them to balance the risk more evenly would mean to incorporate strategies that have 1 losing season out of 5 instead of none and (or) less balanced hit rate and (or) less balanced number of matches and (or) lower profits over 5 seasons. Of course, you won’t see exact numbers to judge, but in order to balance the risk more evenly, would it be a better trade in your eyes?

And what is better to you: a strategy that has zero odds below first infection point, but 1 losing season over 5 years, or zero odds above first inflection point, but profit in all 5 previous seasons?

Hi Jo,

The portfolio you have suggested is a little bottom heavy. In other words, you are going to see a larger percentage of games at lower odds, which will tend to produce a more jagged profit curve (you may not see your portfolio constantly in profit from the start).

The main purpose of the lower odds games is to fill-in the gaps between the losing bets at higher odds. If you remember the inflection point graph in the 2016 Summer League Campaign spreadsheet, it was a zero-sum game up to odds of around 2.28. Because you have a higher proportion of lower risk strategies, you may see this figure pushed upwards (e.g. a zero sum game up to odds of 2.50?).

Your profit curve will look more like the Summer League Campaign than the more efficient Winter League strategy. Your profits will be lower because you are playing a lower risk strategy. It will also be harder to recover losses if your wins are relatively small at that end of the spectrum. You might find it frustrating as the going will be slow – three steps forwards and two back. If it were me, I would find a better balance.

It is always better to have the zero odds below the lower inflection point as every bet you make will be a value bet, which is a strategy that will guarantee long-term profits. If you start surrendering value, you will hamstring yourself. I would rather have value on my side than an analysis with all five seasons in profit.

I hope this assists!

An additional question: Isn’t the number of (possible) games in each league also important for the risk strategy? I would assume that for judging the portfolio’s risk you have to weight the risk in each league.

A simple example:

Two leagues, one with a low risk strategy (e.g. home wins between 1.8 – 2.2 and 200 games), combined with a medium-high to high risk strategy in another league (e.g. underdog wins between 4.5 and 7.5 and 30 games).

Hello again Acepoint,

Your example is a good one, dealing with two opposite strategies in two different leagues.

With a lower risk strategy, you will always be faced with a higher number of bets than with a higher risk strategy, and vice versa.

In other words, with lower odds, you need a higher number of winning bets to create the profit, and vice versa with higher odds.

The risk of each strategy never changes – every bet within the inflection points chosen carries the implied probabilities of those odds. It is not affected by what happens in a different strategy bearing different implied probabilities.

Combining the strategies or weighting them in accordance with each other to obtain some sort of overall measure of risk is therefore going to distort the picture.

Therefore, what we don’t want to do is dilute the extremes of our risk spectrum (i.e. the lowest and highest ends). We therefore take each system in each league on its own merits and line them up alongside each other.

I hope I have understood your question correctly.

Hi, about splitting system into 1st and 2nd half, what would you do if a smooth rising line would show up in a whole season analysis but by splitting them it would show more profit?

For example: analysing a whole season, the inflection points I decided to use were from 3.1 to 3.9. But, if I split it in 2 half seasons, I would have better results by using 2.9 to 3.4 in 1st half and 3.2 to 3.9 in 2nd half.

Resuming: what is the main variable to be analysed in cases (there are many) like this? The stability? The bigger profit? The clear half cut in the season during winter, for example?

Thanks!

Hello again Gabriel,

The main decision-making factor has to be a combination of personal choice and risk acceptance.

Although I was pressed for time in making the analyses for the article above, I made sure, from the results I had at my disposal, to compile a portfolio containing an even balance of low, medium and high risk.

So, yes, find the systems with the highest profit and incorporate them into a team of systems.

Once you have your best team of systems planned out on paper, you may have to do some rearranging (i.e. substituting a split analysis in one league, for the whole season analysis instead, or vice versa), to ensure the portfolio is balanced from a risk perspective.

It’s stability in the whole portfolio you are looking for, not necessarily within individual leagues, but if your inflection points show odds clusters above the zero odds in each system (remember

page 3 of the User Guide), you will certainly make money in the long run.Thanks again for your question!

Hi Right Winger,

As always, excellent job, and congratulations on the results achieved!

I noticed two systems in the portfolio with high expected losing streak, England Premier League (31), and Netherlands Eredivisie (29). Both surpasses your previous recommendations of trying to stay below 20, by far. I know in the end it’s all a matter of personal preference and attitude toward risk, i’m just curious to know your thought process that led to the selection of this two particular systems. What made you close an eye on the losing streak figure?

Thanks!

Hello again Daniel,

I’m afraid to say that the decisions made on those two leagues were not scientific.

You will see in a couple of my replies above (see 25/06/17 to Acepoint), that we were simply rushed for time and I was faced with a “take it or leave it” decision.

But with the EPL and Eredivisie being two of the top six most popular leagues, I couldn’t really leave them out of the campaign, even with their 31 and 29 estimated streaks respectively.

This time last year was such a hectic period that I couldn’t finish the analyses in time – some of the leagues did receive the benefit of all three analyses (whole season basis, 1st half season, 2nd half season), whilst with others, I was only able to carry out one analysis (the whole season).

Ordinarily I would say to everyone to stick with the maximum of 20 losing streak as a rule of thumb, with perhaps a little leeway.

At the time, and with my experience of running these campaigns, I didn’t think it would make a huge difference to the results. Perhaps things could have been improved in the EPL, but I was more than happy with the Eredivisie outcome.

Again, I think it shows the power of a portfolio approach based on inflection points that a healthy profit can be made, even if the most optimal systems are not chosen, although I would always recommend taking the time to perform the job properly.

If I had had time to do a perfect job on the analysis, results may have been even better, but ultimately, there was no spilt milk to cry over.

Thanks for your question – it was a good point to bring up.

Hi again, RW!

Are HDAFU tables and methods to build a system also appliable to group stage competitions, such as Libertadores, Champions League and Europa League? Or even to Europe or South América World Cup Qualifiers?

I understand that playoffs are off the table, but I see these competitions mentioned above as a middle ground between the regular legues and the playoffs.

What do you think about this?

Hello again Gabriel,

The competitions you mention do have group stages (i.e. a mini league format), but there are simply not enough of those games to form any level of statistical significance over a relevant period of time (say five seasons).

All qualifying-round and knock-out-stage games in those competitions would effectively be cup games, and therefore off the agenda as being too volatile to predict.

In the Champions League, for example, I think there are only 96 group-stage games per season. The smallest league we analyse for the HDAFU tables is Iceland with 132 games per season.

Also, league-games-only is a far more predictable science as each season contains a similar number of the same teams. In other words, over five seasons, the turnover of different teams is likely to be a lot lower in a league than it is in the Champions League.

A lower turnover of teams means a lot more games between the same teams in five seasons and therefore a more standardised data set. You might have some of the same teams represented in the Champions League, such as Real Madrid, Man Utd, Juventus, etc., but they might not ever play each other in five seasons of group games (more statistical noise created).

Keep it simple – stick to top-flight leagues – there are plenty of matches to bet on there!

I hope this helps your thinking and thanks again for writing!

Hello again Jo,

I did mention at the end of the ratchet and stop-loss section on page 4 of this article that the staking plan example was a simulation only.

The vast majority of punters don’t even know what a staking plan is or how to calculate a starting bank, let alone deal with a portfolio of multiple systems all running parallel, or calculate the systems in the first place.

I have therefore kept this section of the article as simple as possible just to switch the majority of people on to thinking about proper money management.

Yes, I remember saying in the Summer League Campaign report that we would apply the ratchet and stop-loss simulation separately to each league and show the results, but I just did not have the time to do this – I had not allowed for the early start to some of the 2017-18 leagues this year (due to the World Cup next year), which only became apparent when putting together the Winter League Tables for sale. It was therefore more important to give people as much time to analyse the tables by getting them published as early as possible.

I’m sorry if you’re disappointed, but my advice is to concentrate on the big picture. Sometimes the small details are just not consequential enough to worry about.

If you want to simulate the ratchet and stop-loss applied to each league individually, then I would be happy to publish your findings on the blog. I am sure this approach would have produced even higher profits, but in practise, it is very complicated to manage and more time-consuming to perform. Probably better to stick to the overall approach mentioned, especially as each system is part of a team anyway.

And you must remember that a portfolio approach is all about synergy. The longest losing streak of any one system is always going to be absorbed by the other systems around it. In the case of our portfolio, the EPL suggested the longest individual streak at 31 losses. As it panned out, the portfolio produced a longest run of just 12 consecutive losses.

Don’t worry, it is a good thing to be curious and to want to form your own opinions of things. Nothing is gospel and there is certainly no bible about betting in existence. We write about our own experiences based on our own level of statistical knowledge and maths. Perhaps there are others out there with even higher standards than us, but this is the only website I am aware of prepared to help people increase their levels of knowledge and understanding.

And at the end of the day, we can teach, but we can’t make decisions or place bets on your behalf.

For the sake of good order, I will add a link to the winning and losing streaks article on page 4, and thank you once again for your valuable contribution.

hi Right Winger,

1. how did you calculate starting bank? I used your free excel sheet “winning losing streaks” to calculate starting bank based on your forecast number of 1838 bets and hit rate of 38.87%. With hit rate rounded to 40%, risk coefficient of 3 and 100 units stakes starting bank should be 4500 units. Yours was only 2000 units. Of course, it depends on chosen risk coefficient, but if to take each strategy separately to calculate its starting bank just 3 strategies could easily require larger starting bank than 4500 units. And starting bank for those 22 systems would require quite an amount of money. I’m confused?

2. Why Stake Ratchet & Stop-loss Mechanism was used for the whole portfolio instead of using it for each league separately? This type of approach mean stakes are also increased or reduced for systems that are performing well or failing.

Hi! I am just writing to congratulate you on the excellent analysis on both summer and winter leagues. These material in soccerwidow is mandatory for any serious ante-post bettor. Being a statistician, I value these posts in a way you cannot imagine. Thanks again!

Best regards and profits to us all!

Gabriel

Blush!

Thanks for your kind words, Gabriel!

We shall continue to remain humble servants to our valued readers! 🙂

Hello Acepoint,

Thanks for your questions.

1) It was all just a question of time in preparing the analysis – we were so short on time. The Summer League campaign was already in full flow, there was so much work to do on the website, and in the end, we had to go with the whole season analyses in many of the leagues. Indeed, the current stock of Summer and Winter League tables is the first we have offered for sale with the A/B splits.

2) Scotland and Croatia are newcomers to the fold, so the tables for these weren’t in existence at the start of the 2016-17 seasons. A few seasons ago, we offered Wales and Northern Ireland, but not a single person bought one. What we offer now is simply based on the question of demand and supply.

We try and use the larger, more popular leagues, which tend to be less under-priced than a lot of the fringe leagues.

Remember, the less popular a league is in terms of money wagered by punters, the harder it is for the bookmakers to balance their books, hence their need to under-price far more in, say Wales, than they would in the EPL.

Also, the eastern-European leagues are dogged by match-fixing problems, either criminally, or by mutual consent of the teams involved. You can see this to less of an extent in leagues like Greece or Italy Serie B, where the last few rounds of a season always create strange prices. For example, when a draw is good for both teams, it suddenly becomes the shortest of the 1×2 prices because the bookies know that both teams are likely to play for the draw. Turkey’s last scandal was in 2011.

Hungary, Bulgaria and Serbia may make future appearances in the complement of tables, but Ukraine is in a mess, and personally I wouldn’t wager a penny on the Romanian Liga 1, as sources there tell me it is corrupt to the core, but then again, that’s pretty much public knowledge…

3) No. There didn’t need to be. We knew the portfolio was going to make money, so we have simulated a sensible approach to the staking plan purely as an example to expand readers’ thinking in this direction.

I hope this helps!

Best regards.

Hi again,

first of all thx a lot for your valuable insights. Today I have studied the article and the excel sheet a little bit, and two or three questions/remarks are nagging at me:

1) I would have expected more 1A/1B splits in the winter league, especially for leagues with a true winter break like Switzerland and Poland.

2) You also offer Scotland and Croatia in your HDAFU panel, but I’m missing them in the 2011-16 example. On the other side you don’t offer Countries/leagues like Israel, Northern Ireland and Wales or some East European leagues (maybe there is a reason for excluding the latter, but I don’t see any for the first three).

3) Regarding the ratchet/stop-loss scenario: Is there a direct (maybe negative) correlation between the steps (here 1000 units and 5%) and the longest expected win or loss series?

Tanks in advance and keep on your excellent work!

Hi Soccerwidow,

At first glance, the results of your 2016-17 campaign are fantastic. I’m going to go through your campaign in detail and learn what I can about how and why you put it together, and then hopefully go some way towards achieving what you guys did in that season.

One other thing I wanted to say about what you offer at Soccerwidow….the material – free and paid for – is so valuable and really does teach people what they need to know in order to understand the betting market and what is profitable and what is not, the pitfalls and the best way forward.

I’m very much like you in that I don’t see the value in blindly following another person’s picks, but when someone doesn’t know the betting market or how to go about it themselves, blind faith is what a lot of people gravitate towards.

With your products they really do teach people and empower them to be able to make their own decisions and do things the right way. I feel I have learned a tremendous amount since I found your website and am very much looking forward to putting it into practice in this upcoming football season.

Great job on what you guys do at Soccerwidow!

Simon.

Thanks for your very kind words, Simon.

Yes, the results were good, even with a below par set of results in many of the leagues.

We think the achievement is further glossed by the fact that the stakes used were all relatively small. Replicating our success should therefore be within the financial reach of many people.

Keep in touch and let us know how you get on with your own campaigns!

All the best for now.