Monday 1 January 2001

It's Official

To clarify what I mean when I say 'official' results, since there is unfortunately no recognised source for closing prices (or starting prices to use the horse racing term) for any sport with which this blog concerns itself.

For domestic league football betting, I use Football Data's very helpful spreadsheets and since the 2012-13 season, specifically Pinnacle Sports' Closing Prices. These cover the top two leagues for the Big Five footballing nations of Europe namely France, Germany, Italy and Spain and for England the top five leagues. 

Where I reference seasons prior to the Pinnacle era (as mentioned, 2012-13 forward), unless I specify that the raw odds are being used, I generally adjust the prices to 103%, and do the same to Pinnacle's, even where their overround is lower than this, thus ensuring that results are consistent across the years.

If you are new to betting, you not be aware that in the early years of this century, the average overround in EPL matches was 112.2%. 

For domestic cup competitions, European competitions and International matches, I use the average odds provided by Odds Portal generally adjusted to a 102% overround. These are typically higher profile matches, and the average overround on the raw prices is around 105.4% for International games and 106.3% for Europa and Champions League games, though closer to 104.2% for the past couple of years.

For the US sports I follow (NFL, NBA, MLB, NHL) my source, unless otherwise specified, is Killer Sports

None of these sources are perfect, nor are any of them optimal. As always, it pays to shop around and for many of us who find ourselves limited at the soft books, use Pinnacle or betting exchanges such as Betfair.

Bottom line is that my 'official' results can almost always be improved upon but the intent is to give a verifiable baseline to show the viability, or otherwise, of a strategy. 

Sharp And Soft Books

From Nikolai Livori - Sportsbook Soft or Sharp

The sports betting industry is fragmented into Sharp and Soft books, and of course a mix in between. But what does this mean? We use a more precise term by referring to them as Asian and European books respectively - with Asian books being sharper than European ones.

Soft bookmakers like the renowned Unibet, Betsson, William Hill etc. make use of a lot of traders within the company that use manual or semi-automatic odds movements to ultimately rely on gut feelings, knowledge and game statistics within the industry. They operate with high margins. They do not welcome sports traders and most of the time limit such customer accounts thus falling into the trap called a “false positive”. What if the person you just limited could have been one of your VIP Casino players? Soft bookmakers like these target mostly punters and gamblers and usually have other products to support their sports book such as Casinos, Poker, Bingo etc.

The Sharp bookmaker model is based mostly on mathematical and highly efficient automatic risk management tools. They do employ traders as well to compile odds, however balancing their book is sharper and done with the help of mathematical models. Most of the time they are able to offer better prices in the industry, due to being faster and sharper than Soft bookmakers. Most of them also do not limit bettors and accept large bet stakes, thus they welcome traders and punters alike. Examples of such books are Pinnacle Sports, ED3688, SBOBet etc. Their profit is derived on smaller margins due to a huge turnover.

Being a Soft bookmaker is becoming very challenging nowadays, considering that the Asian market is expanding at a very quick rate. Why would I place a bet on a Soft book for a much cheaper return (and also risk being erratically limited) when I could place a much larger bet at a much better price through an Asian book?  

Bundeslayga System

In September 2010, I noticed that the strategy of laying certain Home Favourites in the German Bundesliga was consistently profitable, making this an ideal system for mitigating Betfair's Premium Charges.

The system has been profitable in both the Bundesliga and Bundesliga.2 leagues.

Initially the system was to lay (oppose) most teams priced at odds-on but as more data has become available, the exact range has expanded.

Because this is a Laying System, it’s really only suitable to be applied on the Betting Exchanges, although you could combine backs of the Draw and away team if you were desperate.

A note on the prices used. Since I don’t have reliable historical Lay prices, I use closing price data from Pinnacle Sports, courtesy of, and remove the margin using the "Equal Margin" method detailed in Joseph Buchdahl's excellent book "Squares & Sharps, Suckers & Sharks".

This resulting 'fair' price is usually very close to the closing Exchange price, but remember there’s commission to pay on Exchange winning bets. In the seasons since 2012-13 for which we have the new system has lost money only once in both Bundesliga.1 (2013-14) and Bundesliga.2 (2016-17), and overall only in that one (2016-17) season.

Here’s a real life example as I write this, from Pinnacle Sports:

The Lay price, calculated by removing the margin is 1.673, very close to Betfair’s 1.68.

Because I have included the specifics of this system in the "Sacred Manuscript", it would not be fair to subscribers to give the precise details away for free, but the results from 2012-13 are as shown below:

** Results last updated on September 20th, 2022

UMPO System

UMPO is an acronym for Underdogs MLB Play-Off and is a simple strategy which backs odds-against underdogs in the Major League Baseball Play-offs.

Since 2004 - the first year for which I have data - it has been a steady winning strategy, and the following returns from a US site can generally be beaten on the exchanges.

Note that the vast majority of profits come from games where the Home team is the underdog. Thanks to a suggestion from @HkiBuzz (Frederic J), this strategy is now known as HUMPO:
** Last Updated after the 2023 ended

Maria's Laying System

Maria's Laying System achieved some notoriety in 2005-2006 when its creator (Maria Santonix) increased a starting bank of £3,000 to six figures (£100,603.78 to be precise) in 303 days.

She promised to post all her lays through the end of August, and with perfect timing made it to six figures on the 31st of that month, 2006. As promised, she stopped posting her selections after that.

According to the Honest Betting Reviews site:
What came to light only later was that Maria’s father was connected with several bookmakers, and through her contacts, she was able to obtain privileged information that helped with her selections. No doubt this contributed considerably to her winnings.

While most of us do not have access to the kind of data Maria had, we can still profit from her laying system. But we must state that her selections were, in fact, remarkable. Of her 4,131 selections over 303 days she achieved 3,547 wins; in other words, a strike rate of almost 86%. While Maria’s system does not in any way help us with our selections, it does provide a mathematical plan that will help us maximise our winnings.
She certainly mentions her father several times, and clearly her selections were the key to the success of her system, but it's an interesting study in following a system and how a staking system can increase profits.

This way of staking is actually truly excellent but it wont change a losing system into a winning one. This is something that many people need to understand before they try and replicate what Maria did. Maria felt she had a winning system for laying horses and so she used this staking plan to compound the profits and grow her bank. Something she certainly achieved by turning £3000 into £100,000 within a year!
Her initial posts on the system from September 2005 are reproduced here, lightly edited for clarity.

I've been reluctant to start off this thread, because I'm frightened of its turning out to be the kiss of death. You have what you imagine to be a good system and start to explain it in public, and suddenly a wheel comes off?

I've come up with a laying system.

I'll record its daily selections and results in this thread, until I get jeered off, anyway.

I'll try to post each day's selections by 1.00pm at the very latest, but I don't think I'll often manage to post them the night before.

Comments, general heckling and questions (but not about the details of my selection-process, please) are very welcome as we go along, but I'd better start off with something like an "FAQ".

STAKING: I want to minimise risks and maximise returns, of course (who doesn't?), which are always pretty difficult, not to say conflicting, objectives to combine. Like all forms of betting, the selections are only a part of the story. Betting on horses is notorious for people being able to have good selections and still lose money through poor money management. With laying in particular, IMHO the commonest reasons for failure are under-funding (not having a bank big enough for what you're trying to do) and disillusionment (getting too easily fed up with an inevitable losing run).

This isn't the time or place to get involved in a big discussion about whether the selections or the money management are more important - it suffices to say that without both aspects being good, sensible, reliable and proven, it's not possible to make steady profits.

The two common staking methods for laying are:-

(i) Laying to a fixed stake: I don't use this for two main reasons: first, the "accidents" are proportionally too expensive; secondly, it seems to me that it fails adequately to make the profits "deserved" after successfully identifying and laying shorter-priced losers.

(ii) Laying to a fixed liability: I don't use this either, because it's inherently mathematically unsound - it ignores the fact that accidents are far more likely to happen at the lower end of the scale: if I lay a 2/1 favourite (i.e. I lay it at an exchange price of 3.0), the overall risk of that bet losing (the horse winning) is of course higher than one which was a lay at 8.0 (7/1).

Instead I try to combine the best of both worlds by using what looks like a complicated mixture of the two systems mentioned above, but it's actually perfectly straightforward.

My staking system: I lay in three distinct exchange-price-bands of fixed backer's stakes.

At one end of the scale, if the exchange price available about the horse is less than 3.5 (less than 5/2), I lay to a stake of 1% of my current laying system bank. At the other end, if the price is between 7.5 and 11 (the latter figure being my cut-off: I don't lay anything higher than 10/1), I lay to a stake of 0.4% of my current bank. If the price is in-between these two bands (i.e. prices of 3.6 to 7.4), then I lay to a stake of 0.6% of my bank. As they say in those TV infomercials, "But wait - there's more!": I also combine this staking plan with a ratchet system (see below).

The are two other advantages with this staking system: first, the practicality of the situation when using the exchanges is that the backer's stake (rather than one's own liability) is the value which has to be typed into the little box on the screen, and this makes it quick and simple to do; secondly, nearly a year's figures have proven to me that this method minimises the variability of the results, and that's very, very important.

To summarise, with examples based on a starting bank of £3,000 (if you're reckless enough to try them, you can scale up or down proportionally to your own bank).

Prices below 3.5: lay to 1% of bank - backer's stake £30 (my liability under £75)

Prices from 3.6 to 7.4: lay to 0.6% of bank - backer's stake £18 (my liability £46.80 - £115.20)

Prices from 7.5 to 11: lay to 0.4% of bank - backer's stake £12 (my liability £78 - £132)

Ratchet System

If making profits, I increase all stakes in proportion to the bank on a daily basis. (I'd love to do it on a bet-by-bet basis, but that would assume that anyone following the system can be glued to their screen all afternoon, which isn't realistic. If you're working for a living - shock horror: please excuse my language! - you need to be able to put the bets on during your lunch-hour.)

This means that at the end of each day, the next day's "current bank" figure is known. For example, if there's a good start and the £3,000 bank grows, then the stakes are worked out as proportion of the new higher figure, and increase slightly the next day. This may sound insignificant but it makes a huge difference to the results.

In contrast, after a losing day, I don't reduce stakes unless and until 35% of the highest level of the bank is lost, when I essentially re-start using the same percentages, but now of the new "65%-sized bank".

Example: from a £3,000 start, if there's a net loss on the first day, the next day I still stake as if from a bank of £3,000 (i.e. to backer's stakes of £30, £18 and £12 depending on the price about each selection) until reaching £1,950 when those backer's stakes would become £19.50, £11.70 and £7.80 until the bank gets back up to £3,000 again (or - dare I mention it? - down to £1,267.50 - a further 35% loss).

The 35% drop is always worked out from the highest point of the bank. If it happens (and so far it hasn't - famous last words!) I'll explain it again.

It may sound a bit complicated but it's actually very simple. Not easy, but very simple.

Please don't imagine that I'm claiming this to be a perfect laying system. There are one or two anomalies in it, but after lots of analysis and calculation in the early days, over the last year I've found this system practicable, straightforward and robust. And that's what matters.


(i) It's essential to keep (at the very least on paper) a separate bank for this system: the money can, if unavoidable, be mixed up in an account with other betting funds, but at the very least the "books" must be kept separately, otherwise you don't know where you are - it's not possible to win in the long run without keeping good records -oooh, contentious!

(ii) Terminology: there's always understandable confusion about discussing laying. For the record, if there's any apparent ambiguity, I'm always referring to the bet rather than the horse. So if I say that out of the day's selections, three won and one lost, and that the day's strike-rate was 75%, I mean that three of the horses lost and one was a winner on which I paid out. (But if that's the actual strike-rate every day, we won't get far: mixed-price-bracket laying systems generally need a very high strike-rate).

(iii) This is a slow and steady system, not a get-rich-quick scheme, and any attempt to turn it into that, or to escalate the stakes when losing, is destined for disaster. With laying, in particular, the swings and arrows of outrageous fortune can be particularly vicious, and it's all too easy for gradually accumulated profits to be wiped out quickly by an uncharacteristically unlucky run. I hope that my staking system allows for this, to a large degree.

(iv) Some of the selections tend to shorten in price and others tend to drift. The reality is that it's not possible, overall, to lay at SP and I would therefore be misleading people about my profits if I quoted the results to SP. So I'm going to keep two separate sets of results.

1. SP + 10%: These results will quote all prices to SP + 10% (i.e. as if the price, from the layer's point of view, was 10% worse than SP).

2. My own actual results, recording the prices I've found and used.

No method of doing this is going to be perfect, but before deciding on this method of keeping the results, I've talked it over with the Administrator and we've decided, hopefully, that this "double results" system is the least open to criticism.

(v) If a selection is priced at more than 11 on the exchanges when I first look at it (and this really isn't going to happen often, because they make me nervous), then with one exception I leave my bet unmatched at 11 and just wait and see what happens. The exception is that if it's priced at more than 14 to lay, I cross it off the list completely and don't even go back to look at it again (this is a half-hearted attempt to avoid becoming the victim of any "major coups"). In the "starting-price + 10% results", I won't be recording as a bet anything that set off at more than 10/1.

(vi) The exchanges charge a variable commission on profits. I'm going to allow for the highest commission at the most expensive of the exchanges, and deduct 5% from all wins. (Note that this is calculated on a "per event" basis, so if you lay two or more horses in a race, the commission is charged only on your net profit on that race.)

(vii) This is (comparatively, at least) a "high turnover" system. The idea is that every bet made represents "value" and has a positive expectation, and therefore the more of them there are, the better the returns. It's not for the faint-hearted! Back these with real money at your own risk and never with money that you can't afford to lose.

(viii) I've found that it's nearly always a mistake to "pick and choose" with this system. Lay all the selections (that can be done within the cut-off of 11) or none of them.

(ix) When I put the bets on, I don't always just take the best current price, depending partly on how much of a hurry I'm in and whether I have shoe-shopping plans for the afternoon. Unless I think the price is particularly likely to lengthen (see "Lay, Back and Think of Winning" by Nigel Paul for the best simple explanation of how you can judge this), I'm likely to leave my lay unmatched at a price in-between what's available to back and what's available to back. Usually my lay will get matched. But I only do this if I can keep an eye on it, and change my mind quickly about what price to lay at if the market moves against me.

(x) Within my cut-off of 11, the market moving against me when I have an unmatched bet is not a reason for me to abandon a lay: if it's part of the system and it's not above 11, I lay it.

(xi) The overwhelming majority of the lays in this thread will be win lays, but there will be the occasional place lay included too. These are much rarer, but I have a very high strike-rate with them.

(xii) Patience and discipline lead to profits.

Maria, who I believe was from Riga in Latvia and in her twenties, posted her selections (lays of horses in the UK and Ireland) and recorded her results in a dedicated thread on the “Expert Betting Advice” forum for almost a year, 884 pages! 

While she kept her selection process to herself, 
What criteria do you use to select the lays?

Ooooh, I could tell you, Atc ... but then I would have to kill you ...
she did sometimes expand a little on her method:
The thing is that a lot more of my selections drift than shorten in the market. This is, really, how I get away with listing the selections here in the first place, to be honest, without it having much effect on the prices I lay to myself. I take loads of early laying prices if I think they'll drift, which I try to judge, with varying degrees of success by "trading-style chart-reading" on the exchange. 

The times that this causes me a problem are (like yesterday's accident) when it's too early to tell, for a late evening runner, because even Betfair doesn't have enough liquidity on those earlier in the day. So I just leave positions unmatched at 11.0 (just like I leave a lot of earlier ones unmatched at 7.4).

I'm gradually been learning from nearly 2 years of doing this, now, that overall I make more profit and a better POI on my higher selections, and less on my lower ones. I happen to know a few full-time professional layers (mostly because my father's one of them!) and they all tell me the same thing: the way to make secure and steady income is by laying in the sort of 5.0 or 6.0 up to 15.0 bracket; nothing much shorter - with the exception of some "value shorties" which I'm stuck with for the moment anyway, because my system produces them and I'm usually pretty strict about including system selections and not just leaving them out because I "don't like the look of them" because my judgement isn't good enough to start doing that, and I'm putting it mildly! 

So for me, making the cut-off any shorter is an absolute no: I want to make it longer, really, not shorter. I imagine that the reality of available prices is such that if you make it 10.5 or less, you'll actually be missing out a much higher proportion of the selections than you might expect just from looking at the SP's, and really you'll end up following "selected selections" rather than "selections". It might be a good and viable and profitable system, and it might work well for you, and I'm not trying to talk you out of it at all; but it's not my system, and it's not what works for me.
Towards the end, she posted some more details about her background and her thoughts on following systems were perceptive:
It's incredibly hard work. I have, in my case, been particularly lucky to have had very good teaching (and from quite a young age!) from a very long-term successful punter who happened to be my father, an opportunity obviously not available to the overwhelming majority of punters. But it has also been very hard work, and very many years of it. 
I think that a lot of people imagine that it's as easy as dreaming up a suitable system or method that works, and then just sticking to it. The reality is that that's terribly, terribly difficult to do, and things tend to have a limited shelf-life of viability and profitability anyway. 
I think it's also very true that different styles and approaches suit different people.

What many people are looking for, in my opinion, is (one way or another) a "short-cut" and there really aren't any. Or at least, the ones that do very occasionally arise are pretty difficult to identify and also not so easy for many people to follow (like this thread, perhaps!). But the reality is that many people find that when they follow a successful system, it isn't successful for them, because actually following a successful system is something that some people are (for various different reasons) not so well equipped to do.
The point I'm trying to build my way up to making here is that developing, analysing, researching and using "systems" (for the benefit of those of us who are not exactly steeped in racing, barely know one end of a horse from the other and have no real, on-the-ground experience at all), isn't in any way a "quick or lazy substitute" for all
that knowledge and experience; it's every bit as time-consuming, difficult, specialised and labour-intensive as any other approach. It just entails a different sort of work.

When asked:

"is there a reasoning behind your price limits, i.e. up to 3.5, 3.6 to 7.4, 7.5 to 11?

she generously expanded on her thinking with a detailed reply:

Well, yes there was when I produced it a couple of years ago, after fiddling about with many different possibilities (and having some much more sophisticated software available then than I have now). 

I wanted to be able to break it up into four chunks (there's 11.5 to about 15.5 as well, but those don't appear in this thread) for all the reasons given in the thread's first couple of posts, to be able to avoid the worst features of laying either purely to fixed stakes or purely to fixed liabilities, and these turned out to be the most natural dividing lines, the first cut-off of 3.5 mostly for "money management reasons" and the second of 7.5 on "frequency" grounds (the point being that in practice, many selections that I want to lay tend to cross that line at some point during their market travels and it therefore seemed a potentially good discipline to create one's arbitrary chart/table landmark there, "waiting for 7.4" being an activity with a reasonable expectation of avoiding disappointment often enough to make it worthwhile). 

I haven't looked at it much since then, I'm suitably embarrassed to say, and of course there's absolutely no reason whatsoever to imagine that it would be suitable for anyone else's selections. This is why I'm always (even now) a bit taken aback when people thank me for the "brilliant staking system" which they are adopting for use with their own selections. I would actually think it far more promising if they were adapting it for use with their own selections (after studying a few thousand results in detail with appropriate spreadsheets etc. - not by "guessing"!!), rather than just adopting it! But this, I think, is really what you're asking about, and my answer is "yes; do that".

I think the overall concept of having these different price-brackets as a way of breaking the thing up, rather than using the "sliding-scale approach" of fixed liability is a valid and sound one, and constitutes a staking system which is safe and profitable if the selections are profitable at fixed liability to start with, obviously.

There will always be people who will try to come up with a staking system which will make profitable a system that wasn't profitable to start with at level stakes/liability; and even more alarmingly there will always be some who apparently manage to do it (the key word, of course, being "apparently"!), but there have to be large numbers of "new layers" coming into the markets all the time and eventually wiping themselves out: that's how markets work, I'm afraid.

The key sentence there is that the system is profitable because the selections are profitable at fixed liability, not because there is anything magical about the laying bands. 

Elo Ratings In Football


Often incorrectly written as ELO, Elo ratings actually take their name from the inventor, Arpad Elo, a Hungarian-born American physics professor and Chess player who invented the ratings method as a way of comparing the skill levels of players from his game. Its use has expanded, and has been adapted for several sports including American Football and basketball, but also in football, and it is their use here that is the focus for the rest of this article.

The Basics

The essence of Elo ratings is that each team has a rating. When comparing two teams, the team with the higher rating is considered to be stronger. The ratings are constantly changing, and are calculated based upon the results of matches. The winner of a match between two teams typically gains a certain number of points in their rating while the losing team loses the same amount. The number of points in the total pool thus remains the same. The number of points won or lost in a contest depends on the difference in the ratings of the teams, so a team will gain more points by beating a higher-rated team than by beating a lower-rated team.

Raw Elo suggests that both teams ‘risk' a certain percentage of their rating in each contest, with the winner gaining the total pot, i.e. their rating increases by the losing team’s ante. In the event of a draw, the pot is shared equally.

A Simple Example

A simple example shows how this works when two evenly matched teams meet, and both have 5% of their rating at risk. Arsenal and Chelsea both have a rating of 1000 so both teams risk 5%, i.e. 50 points, and the pot contains 100 points.

There are three possible outcomes.

1) Arsenal win, and the result of this is that Chelsea’s rating drops by 50 to 950, and Arsenal’s rating increases by 50 to 1050.

2) Chelsea win, and the result of this is that Arsenal’s rating drops by 50 to 950, and Chelsea’s rating increases by 50 to 1050.

3) The result is a draw. The pot is divided between the two teams, resulting in the ratings for both Arsenal and Chelsea remaining unchanged at 1000.

A Second Example

A second example shows how this works when the home side is stronger. Manchester City (with a rating of 1200) plays Aston Villa (with a rating of 1000). Again, both sides risk 5% (60 points and 50 points respectively), so the pot contains 110 points.

The three possible results and their effect of the ratings are:

1) Manchester City win, and the result of this is that Aston Villa’s rating drops by 50 to 950, while Manchester City’s rating increases by 50 to 1250.

2) Aston Villa win, in which case Manchester City lose their 60 points and their rating drops to 1140, while Aston Villa gain the 60 to improve their rating to 1060.

3) The result is a draw. The (60+50) 110 points in the pot are divided by two, resulting in Manchester City’s rating dropping by 5 points to 1195, and Aston Villa’s rating improving to 1005.

A Third Example

A third example shows how this works when the away side is stronger. Wigan Athletic (with a rating of 800) plays Manchester United (with a rating of 1000). Again, both sides risk 5% (40 points and 50 points respectively), so the pot contains 90 points.

The three possible results and their effect of the ratings are:

1) Wigan win. Their rating increases by 50 to 850, while Manchester United’s rating decreases by 50 to 950.

2) Manchester United win, in which case Wigan lose their 40 points and their rating drops to 760, while Manchester United gain the 40 to improve their rating to 1040.

3) The result is a draw. The (40+50) 90points in the pot are divided by two, resulting in Manchester United’s rating dropping by 5 points to 995, and Wigan’s rating improving to 805.

The table below summarises these combinations of pre-match ratings, match results, and updated ratings:

Some Issues

All very simple, but for football, it is much too simple. Anyone with a basic understanding of football can see a number of problems with the above examples. One obvious problem is that home advantage is not taken into account, so in a match between two evenly rated teams, in the event of a draw, the away side should be rewarded, and the home side penalised. In the ‘teams evenly rated’ example above, a draw for Chelsea at Arsenal is clearly a better result for them than it is for Arsenal, and it is illogical that both teams walk away at full-time with the same rating as when the match started.

In Part Two, I will look at some ways in which these problems can be remediated.

In Part One we explained the basic premise of Elo ratings, and illustrated how they are applied. Part two will offer some suggestions on how the principles of Elo can be enhanced to make our ratings more useful. It is important to understand that these are only suggestions. There are no hard and fast rules that dictate what these parameters should be. There is no right and no wrong, only what works and what doesn’t work.

We finished Part One with an example of two evenly rated teams, risking the same percentage of their ratings, and identified one major problem which is that an away draw is better than a home draw, and it is thus illogical for both teams to end the match with the same rating as they started.

The Punter’s Revenge: Adjusting For Home Field Advantage

One way to handle this is by having the home team risk a slightly higher percentage of their rating than the away team. Back in the early 1980s, two authors, Tony Drapkin and Richard Forsyth wrote a book called “The Punter’s Revenge: Computers In The World Of Gambling”, which was targeted at computer literate punters at a time when the personal computer was just becoming popular. One of the more memorable chapters was on rating football teams, and the author’s suggestion, after running trials, was to use 7% for the home team, and 5% for the away team. I’ve found no reason to diverge too far from these numbers.

If we re-visit the earlier examples from part one, using the 7% and 5% numbers, the results become:

When the teams are identically rated going in, after a drawn match, the away team gains slightly, the home team loses slightly, something that intuitively seems right. If you’re not happy with the adjustments that 7% and 5% give you, then there’s absolutely no reason not to tweak these, but I would caution against exceeding 10% or going below 3%. Changes in rating should be in modest increments, but at the same time, not too modest that it takes a season for a declining team’s rating to reflect its form.

Result Adjustment: Incorporating Margin Of Victory

Now to address the next problem – match results. Basic Elo doesn’t quantify wins. A win is a win, whether it is by one goal or by a dozen. Most readers will agree that this is an unsatisfactory state of affairs, and will make adjustments. One method is to increase the percentages that each team risks, but to award a certain percentage of the pool to the winners / losers varying depending on the margin of victory / defeat.

For example, Arsenal and Liverpool are both rated at 1000, and Arsenal are at home. The pot (or pool) contains 120 points, 70 from Arsenal, 50 from Liverpool. If the game finishes 6-0 to Arsenal, it’s reasonable to give all the points to them. My own preference is for a four-goal win or more to be sufficient to secure the entire pot. A three-goal win is pretty good, and earns most of the pool, whereas a two-goal win earns a little less, and a one-goal win the minimum. The following table is a suggestion.

Winning is worth at least 70% of the pot, with the margin of victory becoming less significant as it grows. Winning 6-0 rather than 5-0 is neither here nor there, but winning 1-0 rather than drawing 0-0 is much more significant – even though the difference between both pairs of scores is just one goal. You may want to consider a 1-2 defeat as a better result than a 0-1 defeat, but again, decisions such as these come down to personal preference. With all the time in the world, you might analyse goal times, and conclude that a 2-0 win decided in the 30th minute is a stronger win than a 2-0 win in which the second goal was scored on a breakaway in the 93rd minute with the vanquished team pressing hard for an equalizer. A fair conclusion in my opinion, and an example of how you can modify Elo to suit your own needs, and add flexibility based on the amount of time you have available.

Maintaining accurate ratings is time consuming, and in previous years I would attempt to maintain ratings for the Premier League, Football League and Conference as well as the Scottish Leagues. These days, I restrict my tracking to the top divisions of England, France, Germany, Italy and Spain, in part because there is a wealth of data readily available to input, and on the output side, there are many liquid markets available. It is also my opinion that in the lower leagues, ratings are not so stable. A modest amount of money goes a long way, as recently seen with Crawley Town and Fleetwood Town, and ratings can soon be out of date.

In Part Three, I will look at more ideas for maintaining accurate ratings.

In Part Two, I looked at one way in which Elo ratings could be improved by measuring the strength of a win based on winning margin. However, the low scoring nature of football means that the match result often does not reflect the performance of the teams.

We have all seen games where one team has dominated, only to lose 0-1 to a goal very much against the run of play. If you limit your input to this single figure, goals scored minus goals conceded, you risk entering less than accurate data into your ratings.

While it is true that Birmingham City did beat Chelsea 1-0 on November 20th, 2010 is it fair and reasonable to award 100% or 70% of the points available to them? You might think it is, and I would say that is your decision to make, but my take on it is to look behind the result and use some of the other data that is readily available these days.

When deciding what data I should include, my rule is that there is a correlation between the data and goals. For example, simple logic tells you that there is a relationship between shots, shots on target, and goals. 10 shots, of which 5 were on target, doesn’t necessarily mean that a team will score 2 goals, but for each league there are fairly consistent ratios which we can use.

Charles Reep: Incorporating Shots On Goal

Pioneering football statistician Charles Reep began his research in 1950 (at 3:50pm on 18 March while watching Swindon Town play Bristol Rovers to be precise) and discovered (among other things) "that over a number of seasons it appears that it takes 10 shots to get 1 goal (on average)".

This average will of course vary from season to season, by league and by team, but the important thing is that there is a correlation between shots, shots on target, and goals scored. A note here that some of this data has an element of subjectivity about it, and you will often see major differences in the statistics for the same game from individual observers.

Again, how much effort you want to put into this is a personal choice. Researching the leagues you are interested in will show there are differences, which you can incorporate if you wish, for example as of 2011, the EPL is more efficient at converting shots to goals than Serie A.

I would however caution against changing these parameters too frequently once you have determined reasonable values, with my preference being to use an average for the past three seasons. The website often has some interesting articles on this subject, along the lines of this entry from January 2011:

"Recall that, over the long run, the goal to shot ratio tends to be around .111 - or 1 goal in 9 shots. Across the four big leagues, it's clear that Serie A has by far the lowest goal to shot ratio - that is, it takes Serie A teams systematically more shots to score goals than teams in the other leagues. So far this season, Serie A is at .085 or roughly 1 in 12 shots - a third lower than what is "normal" for the big leagues. In contrast, the other three leagues are around the historical average at .104 (La Liga), .117 (EPL), and .123 (Bundesliga). So spectators in the Bundesliga only have had to see their teams take 8 shots before scoring a goal, while those in Serie A have seen their teams take a full 50% more shots (12) before getting on the scoreboard."

Adding Meaning

This data is important because it allows you to enter more meaningful data into your calculations. Arsenal 2 Chelsea 1 is a start, but in my view, the data is made more valuable by entering the shots and shots-on-target figures also, so you now have for example Arsenal 2:5:12 Chelsea 1:8:19 - a set of numbers that might reasonably lead you to conclude that Chelsea were a little unlucky in that their goals scored were lower than might have been expected.

You can include other data too, although I have yet to see any evidence of correlation between free-kicks or yellow cards. Red cards can obviously be more significant, but you would want to factor in the amount of time remaining at the time of the dismissal. A headline of "10 man City see of United" might sound dramatic and sell newspapers, or draw clicks, but if the dismissal was in the 90th minute, it's a little misleading to say the least.

In Part Four, I'll look at corner kicks and whether this additional data should be included in your Elo based ratings.  

Dangerous Corner

I concluded Part Three with a discussion about what data can or should be included when adjusting a team's Elo ratings. It might seem logical and reasonable to include corner kicks, but perhaps surprisingly, the evidence shows that there is essentially no correlation between the number of corner kicks and goals scored. The English Premier League is actually the strongest, while Serie A and La Liga are the weakest.

This isn’t to say that corners do not lead to goals. One of the problems is that the readily available data is based on match totals, i.e. they do not reveal how many corners lead to a goal; only that over the course of a match, Team A had 2 goals and 12 corners. Both goals may have come from corners, but at this 'macro' level, there is no evidence that says there should be say one goal for every eight corners.

Having decided what data to include, we are no win a position to expand upon the simple table seen in Part Two, which looked like this:

Putting It All Together

By using more data than simply the round figure of goals, it is possible to 'more accurately' reflect the result of a game. I mentioned in Part Three the real-life example of Birmingham City beating Chelsea 1-0 on November 20th, 2011, and we will use this match as an example of how additional data can be incorporated.

Birmingham City had one shot, and they scored one goal. Chelsea had 24 shots, 9 were on target, yet none resulted in a goal. If we have done our analysis and concluded that from ten shots, you can expect one goal (on average), or that from three shots on target, one goal can be expected, you have tripled the amount of data you are entering, and this helps to smooth out any outlying data points.

It is at this point that a basic knowledge of spreadsheets will be useful, since the easiest way to automate these calculations is by creating LOOKUP tables.

Using the ratios for this example (Shots : Shots-On-Target : Goals) we have a result of 4:1:1 to 20:10:0. Dividing the first parameter by 10 (10 shots approximates to 1 goal), and the second by 3 (3 shots-on-goal approximates to 1 goal), we have in goal units 0.4:0.33:1 to 2:3.33:0. You can average (mean or median) these numbers out, or apply a weighting to them so that the match result becomes Birmingham City 0.58 Chelsea1.78. Any weightings or the choice of average is a personal preference. While Chelsea did not win the game, their overall performance based on these numbers suggests they were the better team, and my ratings would adjust in accord with a more accurate scale, for example:

Again, it is personal preference how granular you make these numbers. Breaking them down into 0.25 increments is one idea, but you can use any number. Once the factors are entered into your spreadsheet, and you have set the LOOKUPs correctly, they do not need to be maintained. Your spreadsheet can calculate your match result, e.g. 1.78 to 0.58 and update the Elo ratings accordingly.

Modified Results

At this point in the process, you might also want to consider weighting the ‘modified’ result based on the strength of the opposition. An implied score of 1.5 to 0.5 can reasonably be considered a more merit worthy achievement against Manchester City than against a struggling team.

Update the Elo ratings based on the Table A above, or your version of it, and you’re done. Most matches will see a small change in rating for both teams, some one-sided affairs may see a bigger shift, but the ratings, once established, ‘should’ reflect the strength of one team when compared with another.


How do I use my ratings to make a fortune I hear you ask? One way is to expand your spreadsheet to incorporate a predictive feature. For predicting a future match, you would enter in the two team’s ratings, say 800 and 1000. Create a table with the same margins as there are in Table A, and this can easily be programmed to calculate the post-match Elo ratings for each team if the winning margin is 0, 0.25, 0.5 etc. Your spreadsheet can be coded to display the margin of victory which will keep the ratings as close to their pre-game position as possible. Note that you will also need to allow for the negative equivalents to cater for away wins, and the table above would also have values assigned for -0.25, -0.5 etc.

For example, Wigan Athletic are currently rated at 1257, Manchester United at 1549. If Wigan plays Manchester United at home, a margin of 0 would result in the ratings being unchanged (top right number 0.00) as in the picture below:

If we look at the reverse fixture between these teams using the same ratings, the spreadsheet shows the following:

The ‘expected’ result in this example is that Manchester United will win by 1.5 goals.

If the modified result entered is 3.21 to 0.91, (e.g. United win 3:1 and these numbers are modified for shots and other criteria) the picture below shows how the ratings would change. Manchester United would gain 9 points, and Wigan Athletic would lose the same 9 points. United's win by a margin of 2.3 exceeded expectations, so they are duly rewarded, but winning does not always boost a team's ratings.

By entering in all the upcoming fixtures, your spreadsheet will give you a starting point before you bet. Whether your preference is to focus on the matches expected to be draws, or to look for value on the Asian Handicaps based on your computations, is up to you. I tend to focus on the draws, matches where the predicted result is 0 to 0.5, but that’s just my preference as I consider the draw price to be somewhat ignored, and thus be more likely to offer value.


I mentioned that this prediction is a starting point. You should always be aware of the relevance of the match to both teams – early and late season can be treacherous, and if you use the ratings in domestic cup games that some teams may take less seriously than others, the spreadsheet won’t help you.

This also raises the question of whether you should include Cup matches in your ratings or not. My preference is to not use domestic cup matches, but I do use inter-league Champions League games or Europa League games to adjust my ratings, e.g. AC Milan v Chelsea.

For anyone interested in my starting point for these ratings, I used the 2008-09 season standings, and used UEFAs coefficient to make the English league stronger than the French league for example. After three years of maturity, the top four clubs in sequence are Barcelona, Real Madrid, Manchester City and Manchester United. The weakest is Ligue 1’s EspĂ©rance Sportive Troyes Aube Champagne – a.k.a. Troyes.


This concludes the series on Elo ratings, and once again, I would like to make it clear that many of the parameters I use area personal preference and can be adjusted in any way you wish. The process described above is quite possibly unique to me, as it is a combination of ideas and thoughts collected over more years than I care to remember. It is not intended to be a ‘copy and paste’ answer for you; the purpose of these articles has been to show you how one person’s thought process works, and perhaps prompt you to have some ideas of your own.

There is another component to the spreadsheet which is the use of the ‘modified result’ mentioned above as input to a Poisson calculation from which you can estimate the probability of every result, and thus all the Over / Under, Match Odds and Correct Score markets, and that will be the subject of a future article.

While I have tried to make this series as clear and as easy to understand as possible, it is not impossible that I have assumed some knowledge or understanding that I should not have, so if anyone has any questions on the above, please comment or send me an email, and I will try to respond.


"By always making the Kelly bet, your bankroll will increase faster than with any system."

In Kelly's analysis, the smart gambler should be interested in "compound return" on capital. He showed that the same math a colleague (Claude Shannon) had used in his theory of noisy communications channels applies to the gambler. The gambler's optimal policy is to maximize the expected logarithm of wealth.

Though an aggressive policy, this offers important downside protection. Since log(0) is negative infinity, the ideal Kelly gambler never accepts even a small risk of losing everything.

Fortunately for non-mathematical people, you don't even have to know what a logarithm is to use the so-called Kelly Criterion. You should wager this fraction of your bankroll on a favourable bet:

Edge Odds

Edge is how much you expect to win, on the average, assuming you could make this wager over and over with the same probabilities. It is a fraction because the profit is always in proportion to how much you wager. The edge is usually diminished by tax or commission. When your edge is zero or negative, the Kelly Criterion says not to bet.

Odds is a measure of the profit if you win.

In the Kelly Criterion, odds is not necessarily a good measure of probability. Odds are determined by market forces, by everyone else's opinions about the chance of winning. These opinions may be wrong, and in fact MUST be wrong for the Kelly gambler to have an edge.

For example: The odds on Red Rum are 4 to 1 (i.e. the market estimates that Red Rum has a 1 in 5 chance of winning, or a 20% probability), but by your calculations, Red Rum has a 1 in 4 chance of winning (i.e. odds of 3 to 1, or a 25% probability).

Assuming your estimation is correct, then by betting £100 on Red Rum you stand a 1/3 chance of ending up with £500. On the average, that is worth £166.67, a net profit of £66.67. The edge is the £66.67 profit divided by the £100 wager, in this case 0.67.

The Kelly formula of edge/odds, is therefore 0.67 / 4, or 0.1675. This means that you should bet 16.75% of your bankroll on Red Rum.

A quick search of the Internet will provide you with links to a number of easy to use Kelly calculators.

Unlike some mathematical formulas, the Kelly formula does have the virtue of being easy to remember.

By always making the Kelly bet, your bankroll will increase faster than with any other staking method.

However, gamblers need to understand that their progress and bank balance will not be a smooth upward slope, but will be interrupted by frequent drawbacks. For this reason, a common practice among investors and gamblers is to use the Half-Kelly bet. This greatly reduces the volatility of the Kelly bet, but returns 3/4 the compound return. For many gamblers, that is a price worth paying.

It can be shown that a Kelly bettor has a 1/2 chance of halving a bankroll before doubling it, and that you have a 1/n chance or reducing your bankroll to 1/n at some point in the future. For comparison, a “Half Kelly” bettor only has a 1/9 chance of halving their bankroll before doubling it.

For sports betting, there is the added complication that the true odds on an outcome are not known. When calculating your Kelly bet, your estimate may well differ significantly from the true odds.

Both under-betting and over-betting will give you a reduced rate of return. Under-betting, which the Half Kelly is, will provide steadier growth, but with reduced returns, whereas over-betting can be fatal, as betting twice the optimal Kelly bet results in almost no long-term growth at all.

In my opinion, most gamblers are probably best served by using a flat 2% of their bank per bet, since figuring edges in sports is, as mentioned earlier, very difficult. For a season-long win rate of 55% (on a bet paying at evens), a good target for most bettors, this represents a little more than 1/3 Kelly, which is a conservative compromise between risk and return.

Increasing this to 3%, or occasionally 4% on an especially good play, is reasonable. More experienced gamblers, with a good understanding of the downsides of Kelly and an above average ability in estimating betting advantages, may wish to adopt the more aggressive Kelly approach to maximize their returns.

Spoofing / Head-Faking

While the basic concept is easy to grasp and it sounds very easy to do, in fact trading has developed into quite a complex and tricky art, because people have designed bots and software to take advantage of the most obvious situations where trading should give you a profit. In addition there are people out there who manipulate the markets using “spoof” money, large sums which appear suddenly in an attempt to move the market in a particular direction.

These can disappear as fast as they appear, but it is often not easy to tell the difference between spoof money and real money until it is too late. When trading you are swimming in shark-infested waters and you need to have your wits about you or you will get eaten alive.

[Courtesy of Juicestorm]

Head fakes are bets placed on the opposite side of a bettor's actual preferred position on a game. They are used to disguise a bettor's true intentions and, more importantly, move the point spread to a more advantageous number. They occur most often in smaller markets, with less liquidity, such as college basketball, and second-half over/under totals in the NBA or the WNBA, but some bookmakers say they've even happened on the Super Bowl.

Done with precision, the most potent head fakes can prompt sportsbooks all over the world to move the line the wrong way.

It works like this: An influential bettor likes Duke +3 over North Carolina. When the first line appears at a prominent sportsbook, the bettor places a $1,000 head-fake bet on the Tar Heels -3. The bettor, who is aware of their influence on the market, expects the head fake on North Carolina to cause the line to move to -3.5 at the prominent sportsbook, as well as others. If successful, the bettor later places $40,000 in bets on Duke with the sportsbooks that inflated the line to +3.5. For $1,000, the bettor is able to place his larger wagers on the preferred side with a better line.

Bettors have been giving bookmakers headaches with head fakes for decades in Las Vegas. In the 1990s, renowned sports bettor William T. "Billy" Walters' head fakes became legendary and kept everyone guessing, "Which side is Billy on?" Art Manteris, who ran Las Vegas sportsbooks for 40-plus years, remembers wise guys head-faking on the opening line for Super Bowl XXXII between the Green Bay Packers and Denver Broncos. Today, head fakes play out in real time online, on odds screens that light up when point spreads and totals start to move.

"We're not a group that does head fakes -- that's not our business model," says Shane Sigsbee, who leads the high-volume betting syndicate ImawhaleSports. "But when I watch other groups do these head fakes, it's like art. It's beautiful the way they do it."
The head-fake master

In a world full of cunning wise guys, the most potent head fake of them all belongs to Walters.

"You can get caught with your pants down," longtime professional bettor Gadoon "Spanky" Kyrollos said about trying to decipher head fakes, "and the one that was notorious for it was Billy Walters."

After growing up in hardscrabble rural Kentucky, Walters moved to Las Vegas in the early 1980s, teamed up with the fabled syndicate the Computer Group and rose to the top of the sports betting food chain. For the past 40 years, Walters has had more influence on U.S. sports betting than anyone else. He has almost a mystical presence on the market, causing a sense of paranoia among bettors and bookmakers, who are constantly trying to figure out which of Walters' bets are legitimate and which are head fakes.

Even while Walters was serving time in federal prison for an insider trading conviction, rumors of which side he was on regularly circulated in the sports betting community. (Walters' sentence was commuted in January by President Donald Trump).

The running joke among professional bettors is that Walters never lost.

"If a game won, Billy was on that side," said a sports bettor who goes by "Fats" and worked with Walters for a year in Las Vegas. "If a game lost, well, that was a Billy head-fake game."
Head-fake history

The head-fake game has been going on for a long time.

In the mid-1980s, the Stardust casino and resort in Las Vegas was home to the most influential point spreads, totals and odds in the nation. When Stardust sportsbook director Scotty Schettler's crew put up a number, everyone paid attention -- including competing bookmakers in Las Vegas.

Bettors would line up every morning to get a crack at the Stardust's opening spreads, even going as far as hiring stand-ins to wait overnight and hold their place in line. The sportsbook put up stanchions to keep the herd of bettors organized, but they simply moved them out of the way. Schettler ultimately created a morning lottery, using a deck of cards to determine which bettors would get to go to the betting windows first.

As legend has it, the payphones outside of the sportsbook were the busiest in the nation, with associates of bookmakers from around the nation calling their bosses to report the Stardust lines. Some sportsbooks in Las Vegas would wait until after the initial wave of betting at the Stardust to see how the lines moved. They then copied the adjusted numbers and posted them at their own shops.

"Back in our day, people actually handicapped their own games, did their own work and bet their own opinions," Schettler told ESPN in a recent phone interview. "We actually made the line for the entire country. At 8 o'clock in the morning, we'd put our line up and the entire country followed it. Everybody."

The wise guys quickly figured out how to take advantage of the situation. Betting a few thousand dollars at the Stardust allowed them to basically create the line they preferred at every sportsbook in the nation. That is the true power of the head fake, the ability to move the line throughout the market, not just at one sportsbook.

"It only works if you're convinced other people are going to copy it," said iconic Vegas oddsmaker Roxy Roxborough. "And people copy it."
A bookmaker's head-fake headache

Head fakes play mind games with bookmakers, testing their confidence in their numbers, something that some veterans say is lacking today.

Manteris spent 40 years taking bets at some of the biggest sportsbooks in Las Vegas before retiring earlier this year. Few things rankled him more than head fakes, like the one he believes went down for Super Bowl XXXIII.

The Packers opened as approximately 11-point favorites over the John Elway-led Broncos. Manteris remembers a flurry of early action on Green Bay that pushed the number up to as high as -14. Then, as Super Bowl Sunday approached and limits increased, bigger money came in on the underdog Broncos. By kickoff, the point spread had dropped back down to Green Bay -11.

"It was wise guys betting the favorite," Manteris recalled during a recent phone interview. "It wasn't the public, it was wise guys who in the first 24 hours pushed it up 3, 3.5 points. The weekend of the game the line dropped all the way back to 11. I remember saying to myself, 'I can't believe we just allowed that to happen.'"

In the end, the Broncos won outright, so the point spread didn't matter in terms of the result, but in the long term, Manteris says that kind of up-and-down action cuts into the bookmakers' edge.

"You wind up having all of your money bet on the favorite at the lowest price, and all of your money bet on the underdog at the higher price," Manteris said. "You try to book at a good number, but you can't do that. You can't book the way you want to book with people intentionally manipulating the price.

"The reality is, [if] the bookmaker has total confidence in his own number, then you can negate [head fakes]. But you don't have that today, I don't have that kind of confidence in the numbers anymore. There's too much ambiguity. It's very hard to do in today's world, to have total confidence in the numbers."

And these days, the good numbers don't last long.
Part of the game

The Don Best odds screen is where today's virtual head fakes take place.

The Screen, as it's commonly referred to in the betting community, shows the point spreads, totals and odds from hundreds of sportsbooks from all over the world. Walk into any professional bookmaking operation and you'll find the Don Best screen on computer monitors.

Want to know the price on the latest Russian table tennis match at a sportsbook in Costa Rica? Don Best has it. Want to monitor for the latest line movement for next year's WNBA All-Star Game to post? Watch the Don Best screen, which lights up when the numbers start to move. Everyone is watching it.

Estimates vary on how many betting syndicates currently have enough influence to pull off head fakes, likely no more than a dozen or two at most, though. Trying to spot head fakes is a crap shoot in itself. A point spread will start moving in one direction at one prominent sportsbook; other sportsbooks copy the move, sometimes without even taking a bet, and then suddenly the line will begin moving in the opposite direction.

"You've got a matter of seconds," Sigsbee said. "This isn't something that lasts for seven or eight minutes. You've got 45 seconds to put all of this into action. We're trying to guess what's really happening and get down for ourselves as well. Honestly, sometimes we get faked out, too. We're just caught upside down on it.

"Head fakes are a huge part of the game."

And as long as bookmakers choose to copy lines on events like the WNBA All-Star Game, they always will be.