Gambling Statistics By Race
'A Statistical Approach to Betting the Horse Races' provides historical results from over 8,000 races and 23 racetracks. In the beginning sections, simple probability and statistics are discussed to give the reader a basic understanding of how statistics relate to gambling in general. Remote gambling increased by £3,270.2m (146.1%) from £2239.0m to £5509.2m between periods April 2014 - Mar ch 2015 and October 2018 - September 2019, and over took land based gambling for the fir st time in the latest period. A betting odd opportunity should be considered valuable if the probability assessed for an outcome is higher than the implied probability estimated by the bookmaker. Read more on the math behind.
Executive Summary
This report provides an overview of gambling activity in Australia in 2015, with respect to participation, expenditure, and problems among regular gamblers. The report follows a format and style common to gambling prevalence studies conducted in Australia and elsewhere.
![Gambling Gambling](https://www.statista.com/graphic/1/188417/share-of-casino-gamblers-in-the-us-adult-population-2010.jpg)
As with those studies, the report is intended as a reference document. It is written primarily for researchers and government officials who have an interest in Australian gambling statistics. This report makes a unique contribution to knowledge of gambling in Australia, since Australia has no prior history of surveying and reporting on gambling activity among regular gamblers at the national level.
The content consists primarily of descriptive statistics with a focus on population estimates. The statistics were obtained from cross-sectional analysis of Household, Income and Labour Dynamics in Australia (HILDA) Survey data, wave 15, which is the first wave to include gambling questions. The HILDA Survey was designed so that participants' responses (17,606 participants in wave 15) could be generalised to the Australian adult population.
The participation statistics include population-representative estimates of the proportion and number of Australians who spent money on up to ten common gambling activities (lotteries, instant scratch tickets, electronic gaming machines, race betting, sports betting, keno, casino table games, bingo, private betting and poker) in a typical month of 2015. The report refers almost entirely to these gamblers, which we refer to as regular gamblers.
Chapter 1 of this report provides the background to the study and details regarding study design and methodology. Chapters 2 and 3 respectively provide statistics regarding typical gambling participation and expenditure.Chapters 4 and 5 address participation and expenditure among adults who experienced gambling-related problems. In Chapter 6 gambling expenditure is positioned within the household budgets of low, middle and high-income households. As well, rates of financial stress are compared between households that contain members with and without gambling problems. Additional tables, including a comparison of the HILDA Survey gambling statistics with recent state/territory and national prevalence data and industry revenue data, can be found in the Appendices.
The report identifies an estimated 6.8 million regular gamblers in 2015, among whom lottery participation was very common (76%). Instant scratch tickets (22%) and electronic gaming machines (EGMs; 21%) followed, attracting 1.4 to 1.5 million gamblers. Less than a million gambled regularly on anything else, including racing (14%), sports betting (8%), keno (8%), casino table games (3%), bingo (3%), private betting (2%) and poker (2%). It was common for people to participate either solely in lotteries (59%), or a combination of lotteries and up to two additional activities.
While lotteries and instant scratch tickets were the most popular activities, individual gamblers spent comparatively little on these activities in a typical month, and therefore over the entirety of the year ($695 and $248 per year on average). Those who gambled on Electronic Gaming Machines spent a great deal more per year ($1,292 on average). So too did those who regularly gambled on races ($1,308), sports ($1,032), casino table games ($1,369), and particularly poker ($1,758).
Regular gamblers, viewed by activity, have quite different profiles. For example, compared to the Australian population:
- lottery participants were over-represented among older couples living without children;
- EGM participants were over-represented among people for whom welfare payments formed their main source of income;
- bingo participants were over-represented among retired women living alone;
- regular race or sports bettors were over-represented among men on higher incomes, yet the race bettors were more likely to be older and live in outer regional/remote areas; and
- sports bettors were more likely to be younger and live in an inner-regional area or major city.
Gambling problems are indicated in the HILDA Survey by endorsing one or more items on the Problem Gambling Severity Index (PGSI). According to the standard use of the PGSI, 1.1 million regular gamblers were estimated to have behaved in ways that caused or put them at risk of gambling-related problems.
Among this subset of regular gamblers, there were more sociodemographic similarities than differences. Those who experienced problems were generally more likely to be young, single, unemployed or not employed (excluding retirees and full-time students), Indigenous, men, living in rental accommodation, in a low socioeconomic area, and were more likely to draw their income from welfare payments than those who had no problems.
Those with problems were also more likely to participate regularly in certain activities. This led to rates of problems being particularly high among participants in six activities (EGMs, race betting, sports betting, casino table games, private betting, and poker) with almost 1-in-2 gamblers on any of these activities experiencing one or more issues.
Another thing those with problems had in common was higher than average spending on gambling. This was particularly so among EGM, race and sports betting participants. Those experiencing the greatest problems spent more than four times as much on these activities, and on gambling overall, as those without problems. Well over half of all expenditure by regular gamblers on these activities came from people who had problems.
Overall, more than forty percent of gambling expenditure by regular gamblers, aggregated across all activities, was accounted for by the 17% who experienced problems.
Gambling expenditure has significant financial ramifications for low-income households, particularly among households where gamblers experienced problems. Gamblers living in low-income households spent a much greater proportion of their household's total disposable income on gambling than high-income households (10% vs 1% on average) - this despite spending less in actual dollar terms ($1,662 vs $2,387).
![Gambling statistics by race against Gambling statistics by race against](https://dvh1deh6tagwk.cloudfront.net/finder-au/wp-uploads/2020/07/gambling-1.png)
Gamblers who had problems spent much more of their households' income on gambling than other regular gamblers, with those experiencing severe problems in low-income households spending an average 27% of their disposable household income on gambling - equivalent to four times their yearly household utility bills, or more than half the grocery bills for that income group.
Consistent with these patterns of expenditure, the households of those with gambling problems had a much greater proportion of stressful financial events. Inability to pay electricity, gas or telephone bills on time, and needing to ask friends or family for financial help, were common occurrences.
Future waves of the HILDA Survey will provide nationally representative longitudinal data with which to measure changes in gambling activity and effects on individuals and their households.
The authors would like to thank all those colleagues who contributed to creating gambling questions for the HILDA survey and for their input into this report. In particular, we would like to thank:
- Doctor Anna Thomas, Australian Gambling Research Centre, Australian Institute of Family Studies
- Doctor Jennifer Baxter, Australian Institute of Family Studies
- Assistant Professor Nicki Dowling, Deakin University
- Professor Bryan Rodgers, Australian National University
- Acting Director Rachel Henry, Welfare Quarantining and Gambling Branch, Department of Social Services
- Professor Mark Wooden, Melbourne Institute of Applied Economic and Social Research, University of Melbourne
- Doctor Diana Warren, Australian Institute of Family Studies
- Director Anne Hollonds, Australian Institute of Family Studies
- And all of the participants who took part in the HILDA Survey and made this report possible.
![Gambling statistics by race against Gambling statistics by race against](https://mma.prnewswire.com/media/1192594/Ethnicity_Distribution.jpg?p=publish)
Disclaimer
This report uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either DSS or the Melbourne Institute. As well, the views expressed may not reflect those of the Australian Institute of Family Studies or the Australian Government.
Cover photo: © iStockphoto/>welcomia
Nowadays gambling has become even more popular than decades ago, owing to the development of Internet technologies. There are millions of gamblers all over the world. Most of the players, who parlay responsibly and don’t cross their safe bankroll limits, will have a great time.
Unfortunately for some people, it’s not just harmless entertainment. Sometimes it can lead to serious issues in different aspects of life. This might happen when a person starts experiencing addiction problems (a player is not capable of controlling his/her gambling behavior).
Problem Gambling Prevalence Rate
Some countries show a higher prevalence rate than others, and it may be explained by cultural, economic, political, and legal factors. We’ll provide thorough information about gambling addiction in different parts of the world, based on recent research from 2016.
Australia
According to the statistics on problem gambling among the population, Australia shows quite high numbers. Approximately 0.5-1% (figures vary in different states) of citizens suffer from this addiction. This is so due to the changes in the betting industry due to digital technologies.
More people can now access betting entertainment via different online services, therefore the cases of unhealthy gambling have increased greatly. Each year Australians spend almost $1.5 billion on online wagering. Moreover, due to the high rate of illegal (in AU) sites, people are losing up to $0.5 billion to overseas companies.
That’s why Australia does everything to prevent unauthorized companies from entering their inner gaming market. According to the Gambling act 2001, with the recent amendment (2016), it is prohibited for foreign casino operators to provide their service there unless they are not licensed in AU.
Such strict rules also serve for decreasing the rate of dangerous betting habits.
Canada
Interestingly, Canada is among the countries with the highest percentage of gambling addicted citizens. Imagine that ¼ of all CA residents (or their friends/relatives) have suffered from some sort of bad consequences (job loss, depression, marriage problems and etc.) owing to their dependence.
And more than 80% of respondents have participated in lotteries during the past year.
It is a serious problem that affects millions of Canadians, although only half of those surveyed agreed that gambling can be dangerous.
New Zealand
New Zealand has the least number of problem gamblers according to the study by Business and Economic Research. It states that only a few citizens are liable to excessive betting behavior. Most of the casino clients in NZ are well aware of possible hazards, and know when it’s better to stop playing.
Norway
Despite the fact that there is government regulation of gambling activities, which provides various measures to decrease addiction problems among citizens, Norway is far away from the minimum rate of dependent people. Approximately 0.7% (more than in Denmark and UK) of the population in this country is grappling with the problem.
UK
Addiction drains a lot of money (about 1.2 billion pounds per year in the UK). Therefore, the government should pay special attention to this issue. According to various scientific sources, the cost also comprises special institutions service (mental health clinics), homelessness and police involvement.
The percentage of people who suffer from the bad influences of gambling varies from 0.6 to 1.1% of the total adult population. Diverse age groups show different liabilities to betting activities, which results in such data as 0.7% (for 25-34-year-olds), and 0.8% (for 18-24-year-olds). Moreover, the research also shows that unemployed, homeless, and people of color tend to be in the risk zone more often than others.
Gambling Statistics By Race In America
USA
The USA is in the top list of countries, where a huge part of the population (2.6% or almost 10 million people) has an addiction problem because of gambling. These activities are represented in every state (even where they are restricted).
Of course, not all players have serious dependences, some just like to have some fun and feel a little risk, while others learn to gamble on a professional level, which helps to avoid big losses.
Unfortunately for other types of people, such an entertainment can lead to an illness, that should be treated (due to the high similarity with drug and alcohol addiction).
Overall, compulsive betting behavior costs about 6 billion dollars per year for U.S. economics.
Distribution of Problem Players
Problem players have a different prevalence and it depends greatly on age and gender. These points are well-documented in the following paragraphs.
Gambling Statistics By Race Statistics
By Age
People are divided into age groups such as:
• 16-24 year olds – who show the most susceptibility (1.4%)
• 25-34 – tend to gamble less than their younger and older mates (0.8%)
• 35-44 – are also at a higher risk (1.1%)
• 45-55 and older – only 0.3% or less.
By Gender
The sharpest contrast we see is in the statistics that differentiate people by gender:
• Men – 1.2%
• Women – 0.1%.
Statistics of Device Usage
Gambling Statistics By Race Results
To understand the subject better, we will also provide statistics, which shows what devices are used mostly by problem gamblers:
• Laptops – 55%
• PCs – 34%
• Mobile phones/tablets – 29%/21%
It’s interesting to note, that mobile phones are used more commonly by 18-44-year-olds, while PCs are more popular among older people.