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# Betting in Australian Open Tennis with Ranking System
- URL: https://jimmakos.com/betting-australian-open-tennis-ranking-system/
- Published: 2009-01-23T15:45:35.000Z
- Updated: 2020-12-13T15:05:55.000Z
- Author: Jim Makos
- Tags: Betting, Gambling

Most bettors are betting on the **tennis** matches at the Australian Open 2009 nowadays. I came across a publication which discusses about forecasting the winner of a **tennis** match and I back tested the suggested mathematical formulas using the historical data from the previous Australian Open Championships. While this is the first formula I found to make use of the world **tennis** **ranking** **system**, the results in my Excel spreadsheets are disappointing.

The publication about [**forecasting the winner of a tennis match**](http://www.hse.ru/data/695/551/1234/Magnus.pdf) is 11 pages long but you don’t need to read them all. The mathematical formula we are interested in is in the 5th page and is the (4) formula. I went on and created the Excel spreadsheet where you can input the **ranking** of two **tennis** player competing in the **tennis** match you are going to bet, and the sheet will automatically calculate the estimated probability the highest ranked player to win the game.

You can **[download the Excel file here](https://docs.google.com/spreadsheets/d/17SyOVLXF67KpqEyC01liF1Tbcuvzpb2brje-gqtyyyI/edit?usp=sharing)**.

For back testing purposes I used the invaluable data found at [****Tennis\-Data.co.uk**](http://www.tennis-data.co.uk/ausopen.php) and I considered the Australian Open statistics since 2006 season. So, betting in 400 games in the Men’s **Tennis** Championship during the last 3 years using the formula above, would lose us a lot of money.

![](https://storage.ghost.io/c/44/8d/448d9c80-c34d-4d74-8a89-3db10bee06f2/content/images/2020/12/backforranking.png)

If you think that by backing the opposite outcome will make you money, guess again. Commission is the big winner here, since we still lose money by backing the other **tennis** player, betting as if the formula picks out the loser. I should note here that I took into account the average bookmakers’ odds and I applied 5% more commission on them, making it a bit more expensive.

![](https://storage.ghost.io/c/44/8d/448d9c80-c34d-4d74-8a89-3db10bee06f2/content/images/2020/12/backagainstranking.png)

However, if we lay the initial selection, we will make money. How’s that possible? Well, when I backed either **tennis** player, I used a fixed amount of money to risk on each bet, €10\. When laying I aimed for a fixed amount of money to be won instead of risking, again €10\. In this situation, there are times that I risk a lot more than €10 since laying at odds over 10, we risk more than €100 to win €10\. Considering that the sample was a bit small and just a few big outsiders won a couple of games, the graph is justified. 3 or 4 losing bets of 15.0 or bigger odds would wipe out all my winnings.

![](https://storage.ghost.io/c/44/8d/448d9c80-c34d-4d74-8a89-3db10bee06f2/content/images/2020/12/layagainstranking.png)

Nevertheless, if you were searching for a formula to calculate probabilities from the **tennis** world **ranking** **system**, you may give it a go and see for yourself. A final warning if you are going to test it in the women’s championship, as the “λ” constant needs to be changed to 0.7150.

And if you happen to make some money using a strategy based on this equation, don’t forget to leave a comment.