Intelligent Golf Betting: The Derivative Golf Markets

Derivative betting markets are those invented by the industry, not the sport. In golf for instance, we have Top 5/10/20 and Top European/US/Aussie etc. These provide betting opportunities but are of little (if any) importance to the players themselves.

There are clearly some psychological issues at stake with the prize money below the winner’s. For example, one would expect a lowly journeyman to fight harder to secure a tenth-place finish than the multimillionaires. On the flip side, the superstars are under little pressure once they can’t win a tournament, so are less likely to choke on Sunday afternoon chasing a top-10. All in all, I believe the win market prices are a suitable baseline to use for derivative models, i.e. one can safely assume that no players are intentionally avoiding placing as high as possible.

In the previous article we developed a win model and converted it to a 110% book. To develop an opinion on the derivative markets we employ the same methodology, converting the full-field win over-round to our desired over-round for the other markets.

Place Markets

The primary Betfair golf place markets are Top 5 and Top 10. Depending on the tournament, you may also find Top 3, Top 4, Top 6, Top 8 and Top 20. Depending on your strategy, it’s important to keep an eye on the liquidity available in each market, particularly when there are several place markets on an event. For example, Top 5 will often trade much more than Top 6, but if you are running a book you might lay more Top 6 due to the lack of competition from other layers.

To develop our tissue place prices, we will convert our 100% win prices to x00%, where x is the number of places available. For our example, we will create a Top 3 tissue with an over-round of 300%, using our earlier mythical 10-man event.

RankPlayer50/50 Merge50/50 OddsTop 3%Top 3 Odds
1Dustin Johnson24%4.271%1.41
2Hideki Matsuyama10%9.6231%3.22
3Jordan Spieth13%7.9637%2.67
4Rory McIlroy11%9.2132%3.08
5Jason Day9%11.9225%3.99
6Sergio Garcia8%11.9425%4
7Henrik Stenson8%1323%4.35
8Alex Noren5%19.1316%6.41
9Rickie Fowler8%13.2623%4.44
10Brooks Koepka6%17.6617%5.92
Field Total101%300%

The example above uses the simple conversion method we used earlier applying the same margin to each runner. Here you can see why this method is somewhat limited; it has skewed the favourites too short and the outsiders too long. It has essentially ignored the favourite/long-shot bias. If you were laying at these prices (with a margin applied) you should expect to take money on all the outsiders and nothing on Dustin Johnson, leaving yourself pretty exposed.

Now in a full 156-man field, pre-event, this approach is not too problematic. However, in a small field such as ours, or between rounds when the number of viable winners is limited, it is far from ideal.

A more rounded approach to develop baseline probabilities under these circumstances is to once more use a ‘power of’ multiplier. The maths to get to our desired over-round isn’t and requires iteration, however, so it’s easier to use a tool. In the example below, I use Excel Solver.

RankPlayer50/50 Merge50/50 OddsTop 3% - V2Top 3 - V2
1Dustin Johnson24%4.248%2.09
2Hideki Matsuyama10%9.6231%3.2
3Jordan Spieth13%7.9634%2.9
4Rory McIlroy11%9.2132%3.12
5Jason Day9%11.9228%3.57
6Sergio Garcia8%11.9428%3.57
7Henrik Stenson8%1327%3.73
8Alex Noren5%19.1322%4.55
9Rickie Fowler8%13.2627%3.77
10Brooks Koepka6%17.6623%4.36
Field Total101%300%

Top Regional Markets

Not as popular on the Exchange as they used to be, the top regional markets provide some good opportunities for intelligent bettors as odds creators don’t focus so much on them.

Developing your tissue prices is the same as the other methods, where we use the win model as our baseline. In the example below, I have created a mythical Top Rest of World (non-US) model from our 10-man field.

RankPlayer50/50 Merge50/50 OddsTop ROW %ROW Odds
1Dustin Johnson24%4.2
2Hideki Matsuyama10%9.6220%4.9
3Jordan Spieth13%7.96
4Rory McIlroy11%9.2121%4.69
5Jason Day9%11.9216%6.07
6Sergio Garcia8%11.9416%6.08
7Henrik Stenson8%1315%6.62
8Alex Noren5%19.1310%9.74
9Rickie Fowler8%13.26
10Brooks Koepka6%17.66
Field Total101%
ROW Total51%100%

The image above shows the ‘flat’ method applying the margin to all runners. Below is the same mythical market but using the Solver method to retain the favourite/long-shot bias.

RankPlayer50/50 Merge50/50 OddsROW % - V2Odds - V2
1Dustin Johnson24%4.2
2Hideki Matsuyama10%9.6219%5.16
3Jordan Spieth13%7.96
4Rory McIlroy11%9.2120%4.99
5Jason Day9%11.9217%6.02
6Sergio Garcia8%11.9417%6.03
7Henrik Stenson8%1316%6.41
8Alex Noren5%19.1312%8.48
9Rickie Fowler8%13.26
10Brooks Koepka6%17.66
Field Total101%
ROW Total51%100%

As per the place market note, when there are few viable winners, these methods of estimating probabilities suffer problems. Modellers must always be prepared to adjust the baseline calculated numbers, particularly in very short fields.

One of the more interesting angles of the derivative markets is that bookmakers largely ignore them between rounds (outside of the majors). This potentially presents good opportunities on the Exchange for those that invest the time to develop prices themselves, as the wider market has few reference points.

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