Over the last decade, the availability and accessibility of gambling has been expanding and evolving due to technological and sociological developments (Chóliz, 2016; Jiménez-Murcia et al., 2014). Consequently, consumers of gambling products have changed the way they behave and interact with these products, with a greater number of adults reporting gambling from home from their internet-connected devices (Lejoyeux, 2012). Online gambling has drastically increased the accessibility of gambling and as a result, the potential frequency of gambling and risk to experience symptoms of problem gambling (Hing et al., 2016; Lejoyeux, 2012). Of all the available forms of online gambling, sports betting is one of the most widely endorsed forms (Jiménez-Murcia et al., 2014; Mestre-Bach et al., 2022).

The popularity of online sports betting (OSB) has been continuing to increase in part due to its legalization in multiple jurisdictions globally (Lopez-Gonzalez & Griffiths, 2018). In 2018, sports betting was the most popular form of online gambling in Europe (European Gaming & Betting Association, 2019). With increasing legalization, sports betting establishments have proliferated, where other addictive substances such as alcohol could be consumed (Li et al., 2020). In recent years, novel features have been incorporated into sports-betting experiences, such as cash-out features, additional live in-play betting and request-a-bet options, instant deposits, and micro-betting (Lopez-Gonzalez et al., 2019; Winters & Derevensky, 2019). Nevertheless, the fact remains that sports gambling is often done through illegal bookmakers (Morgan Stanley, 2014) which has resulted in some researchers requesting legislators to develop measures for better regulation of the sports betting market (Hing et al., 2015a).

In addition to broadening availability, some studies have reported on the potential influences of advertising on the development of gambling problems as a result of online gambling including OSB (Bouguettaya et al., 2020; Newall et al., 2019). Despite the role of advertising on increasing the risk of gambling problems associated with OSB, individuals that develop problems with gambling tend to have certain predispositions that increase this risk (Chóliz, 2008; Hing et al., 2015a; Russell et al., 2019a, 2019b). Based on the Diagnostic and Statistical Manual Fifth Edition, gambling disorder (GD) is an addictive condition characterized by persistent and recurrent problematic gambling behavior that generates clinically significant levels of distress and impairments in functioning (American Psychiatric Association, 2013). Although the DSM-5 disorder does not specify types of gambling activities, there is evidence suggesting that certain forms of gambling may be associated with greater risks for the development of GD (Lutri et al., 2018; Stevens & Young, 2010; Williams et al., 2021). Due to sports betting in both online and offline forms increasing in popularity, it is essential to identify demographic and clinical characteristics associated with the risk for the development of GD associated with sports betting.

It is known that individuals engaging in OSB gambling represent a particularly vulnerable group, with a higher proportion of individuals who are single, younger, and of lower socioeconomic status, report an earlier onset of gambling participation, endorse higher rates of substance use disorders, report greater psychological distress and have distinct personality profiles (i.e., higher impulsivity, reward dependence, and novelty seeking) (Estévez et al., 2017; Granero et al., 2020). The evidence suggesting that OSB involves gambling participation among younger individuals is of particular concern as adolescents and emerging adults appear at increased risk of gambling problems (Sarabia et al., 2014).

Other relevant factors that may result in maintaining sports betting behaviors and increase the risk for problem gambling are cognitive biases (e.g., illusion of control). Cognitive biases may result in a reduction in the perception of risk and possible long-term effects as a result of gambling, and increase the perception that personal skills contribute significantly to gambling outcomes (Chóliz, 2010). However, cognitive biases specific to OSB remain understudied with inconsistent findings having been reported in their role for differentiating between problematic and non-problematic sports betting (Huberfeld et al., 2013).

Although there are increasing studies investigating the relationship between sports betting and problem/disordered gambling, many investigations conceptualize sports betting as one of the many forms of online gambling, rather than as an entity in and of itself. Moreover, few studies have examined the demographic and clinical characteristics of individuals reporting engagement in sports betting and whether certain characteristics differentiate between sports betting with or without problem/disordered gambling. The association between sports betting and GD has rarely been examined, particularly longitudinally, with no systematic review having been published on this topic. Despite the growing number of individuals experiencing clinically relevant problems with sports betting (Mestre-Bach et al., 2022), to the authors’ knowledge, no previous systematic review has been conducted examining the clinical characteristics of people engaging in sports betting. This marks a significant gap in the field that should be addressed as such information could facilitate the development of more effective prevention and treatment interventions (Winters & Derevensky, 2019). Taken together, the research question this systematic review aims to answer is: what are the clinical correlates (i.e., sociodemographic features, gambling-related variables, co-occurring psychopathology and personality tendencies) of people engaging in sports betting?


Study Selection

The methodology employed in this review adheres to principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Moher, 2009). Relevant studies were identified via searches of NCBI/PubMed and APA PsycInfo databases using the following search terms: "sports bet*" OR "sports wager*" OR "sports gambl*" OR "fantasy sport*" OR "daily fantasy". The final search was conducted on May 28, 2021. No date range limits were applied to avoid selection bias. Only published or in-press empirical studies in peer-reviewed journals written in English, Spanish and French were considered for inclusion. In addition, only studies with an observational or descriptive design (e.g., cross-sectional, longitudinal, case–control) and a quantitative methodology were considered eligible for inclusion. Articles with no abstract, as well as publications that were not full articles, that had a qualitative design or that had the following specific formats (i.e., literature reviews, books, dissertations, case reports or series, editorials, clinical practice guidelines, commentaries, and gray literature) were excluded. Finally, studies evaluating treatment interventions were also excluded.

The present systematic review was performed on the basis of the following eligibility criteria: (1) human samples: general population (including both athletes and non-athletes) and/or individuals with a clinical diagnosis of GD, irrespective of sex and age; (2) administration of at least one clinical interview/psychometric instrument to assess the presence of problematic gambling/GD, (3) involvement of at least one group of participants with sports betting, and (4) direct analysis of associations between sports betting and any of these features: (A) sociodemographic characteristics (e.g., sex, age), (B) gambling-related variables (e.g., GD severity, gambling frequency, gambling-related cognitions, maximum bets), (C) co-occurring psychopathology, and/or (D) personality features (e.g., impulsivity).

Once duplicate results were excluded, all abstracts were screened for inclusion and exclusion criteria. Most studies excluded in this first step either investigated behaviors other than SB, had a dependent variable other than clinical correlates or were published in a language other than English or Spanish. For all studies identified for inclusion, a full text version was retrieved, and all studies were reviewed with regard to their quality and eligibility for the review. In case of exclusion of studies, reasons were documented. Included studies were read thoroughly, and the former defined measures were extracted and included in tables.

Study Assessment and Data Extraction

A two-step process was performed to select the final articles included in the present systematic review. First, two reviewers (EVM and BMM) screened the titles and abstracts of all potential studies individually. For the second level of the screening, articles identified for full review were further screened according to the eligibility criteria by two separate authors (EVM and BMM). Differences in rating between both reviewers were resolved through consensus, with the assistance of a third reviewer (GMB). The complete screening process was conducted using Covidence, a software based on the PRISMA standard and recommended by Cochrane Reviews (Kellermeyer et al., 2018).

A total of 442 records was retrieved from the literature search in the selected databases. After removing 111 duplicates, 155 of the 331 remaining articles were excluded taking title and abstract into account. The remaining 176 records were screened at a full-text level. From the 176 articles screened, 54 were ultimately included in the systematic review. Reasons for exclusion at the full-text screening stage are included in Fig. 1. Data were extracted including the full references of articles, main aims, study designs, sample characteristics and sizes, descriptions of methodology, and results.

Fig. 1
figure 1

The PRISMA flow diagram of the selection process

Risk of Bias Assessment

The risk bias of the included studies was performed using four items of the Effective Public Health Practice Project Quality Assessment Tool (EPHPP): selection bias, study design, data collection methods and appropriate statistical testing; additionally, a global rating was calculated (Thomas et al., 2004). The EPHPP is a guide to systematically appraise study quality in seven ambits: selection bias, study design, confounders, blinding, data collection methods, withdrawal and dropouts, and intervention integrity and analyses. The tool can be used to evaluate the study quality of observational, cross-sectional, before and after, and randomized controlled trial studies and has good content and construct validity and adequate test–retest reliability (Armijo-Olivo, Stiles, Hagen, Biondo, & Cummings, 2012; Thomas et al., 2004). Being that all the studies had cross-sectional designs, the items specific to intervention studies were excluded (i.e., confounders, blinding, withdrawals and dropouts, and intervention integrity). The study design criteria were also slightly modified to reflect the fact that most studies were cross-sectional, with differentiations based on sample size in both general population (Strong: N > 1250; Moderate: N ranging from 630 to 1249; Weak N < 630) and clinical samples (Strong: N > 100; Moderate: N ranging from 30 to 99; Weak N < 30) being included. Two authors (JR and LM) performed the quality assessment separately for each study, and discrepancies were resolved.


The present article is a systematic review of the literature, and no studies with human participants or animals were performed by any of the authors to conduct this work.


Study Characteristics

Descriptions of the included studies and their findings are summarized in Table 1. Fifty-four articles were included in the systematic review. Australia was the country with the most published research on sports betting. All studies included in the systematic review had a cross-sectional design. Sample sizes ranged from 60 to 20,587. One study included only females (McCarthy et al., 2018), three studies included only males (Barrera-Algarín & Vázquez-Fernández, 2021; DiCicco-Bloom & Romer, 2012; Estévez et al., 2017), and the remaining 50 studies included both males and females. The percentage of males and females included in the last group of studies varied considerably, with the percentage of females being lower than that of males in most cases, with the exception of eight studies (Baggio et al., 2018; Hing & Haw, 2009).

Table 1 Description of the selected studies


Most (n = 52) studies involved adults from the general population. Seven studies included clinical samples with alcohol use disorders (Bodor et al., 2018) or GD (Barrera-Algarín & Vázquez-Fernández, 2021; Estévez et al., 2017; Håkansson et al., 2017; Jiménez-Murcia et al., 2021; Quilty et al., 2014; Valleur et al., 2016). Ten studies included samples of college students and/or athletes (Grall-Bronnec et al., 2016; Marchica & Derevensky, 2016; Martin & Nelson, 2014; Martin et al., 2016, 2018; Phillips et al., 2013; Richard et al., 2019; Roderique-Davies et al., 2020; Wang et al., 2021; Weiss & Loubier, 2010).

Assessment of Sports Betting and GD

Most studies assessed past-year engagement in sports betting, online sports betting, or fantasy sports. Some studies assessed engagement in sports betting during average weeks or months. Other factors assessed included: sports gambling expenditures, frequency of sports lottery purchasing in a week, time commitments to daily sports lottery-related activities, types of sports lottery purchased, channels used to bet on sports, devices used, engagement with in-play betting, gambling activities participation (frequency, seasonal fantasy sports betting, daily fantasy sports betting, and sports betting in general), monthly sports-betting expenditures over the past year, frequency of sports-betting behaviors, proportion of sports bets in land-based venues, via the internet and via telephone calls, payment methods used for sports betting, and age of first sport betting.

The psychometric instruments used to assess GD were heterogeneous and are described in Table 2. The most frequently used measures to assess for the presence of problem gambling and/or GD were PGSI (Ferris & Wynne, 2001), DSM-IV criteria (American Psychiatric Association, 2010) and DSM-5 criteria (American Psychiatric Association, 2013).

Table 2 Psychometric instruments used to assess GD

Risk Bias Assessment Results

As depicted in Table 3, most studies had global ratings corresponding to strong and moderate quality, almost in equal proportions (strong n = 24; moderate n = 25), and only 5 studies were rated as having a weak global quality.

Table 3 Risk bias assessment and results

Sports Betting and Sociodemographic Characteristics

Sports betting was highly associated with sex, with males being more likely to participate in sports-betting and fantasy-sports leagues (Håkansson et al., 2017; Marchica & Derevensky, 2016; Martin & Nelson, 2014; Richard et al., 2019). Differences have also been reported between males and females in the association between sports betting and substance use. While in the case of females, this association seems to be relatively weak, for males it appears to be particularly strong (Baggio et al., 2018). Regarding age, Marchica et al. (2017) observed that students aged 16–19 years were more likely to exhibit features of problem gambling when they engaged in sports-related gambling regularly, compared with younger adolescents aged 13–15 years.

Numerous attempts have also been made to define a phenotype related to sports betting by considering multiple sociodemographic variables together. Findings suggest that individuals engaging in sports betting are more likely to be male, single, and younger than non-sports-betting individuals (Cooper et al., 2021). They are also more likely to be college-educated, have full-time jobs with higher salaries, and report betting a higher percentage of their monthly incomes (Cooper et al., 2021). In a predictive model of sports betting delineated by DiCicco-Bloom and Romer (2012), non-Hispanic Black ethnicity was a significant statistical predictor of sports betting, as well as having a friend who gambles or approves of one’s gambling. Jiménez-Murcia et al. (2021) reported that being male, younger, engaging in more frequent sports betting, and presenting higher impulsivity and lower self-directedness levels, among other measures, were factors increasing the risk of online sports betting. The highest frequency of sports betting was observed in males, with high social status and low education levels also being implicated (Jiménez-Murcia et al., 2021).

Granero et al. (2020) identified two latent clusters of sports betting. Cluster 1 included individuals most involved in online sports betting. This group was characterized by being younger and unmarried, having a lower socioeconomic status, engaging in gambling activities early in life, reporting higher gambling-related debts, and reporting more substance-use disorders, worse psychopathology and dysfunctional personality traits. Cluster 2 included individuals less involved in online sports betting. These individuals were older, mostly married or with a stable partner, and were of higher socioeconomic status.

Sports Betting and Gambling-Related Variables

Problem and Disordered Gambling Severity

A significant association between sports betting and problem gambling was reported in most studies (Baggio et al., 2018; Lopez-Gonzalez et al., 2020; Nweze et al., 2020; Russell et al., 2019a, 2019b). Cooper et al. (2021) observed that, compared to non-sports-betting individuals, those betting on sports were more likely to report problem gambling, and this could be related to group differences in attitudes towards gambling, cognitive distortions, gambling motivations or the number of gambling activities performed. Similarly, Gainsbury et al. (2019) reported a positive correlation between a higher frequency of online sports betting and problem gambling. In this vein, Bodor et al. (2018) reported that participants with alcohol use disorder who reported a higher frequency of sports betting were more likely to exhibit at-risk/problem gambling or to have GD. In DiCicco-Bloom and Romer’s study (2012), symptoms of GD including tolerance and worry were statistically predictive of sports betting, while withdrawal and subjective loss of control were not.

Not all studies identified clear associations between sports betting and problem gambling. For example, Håkansson and Widinghoff (2020) highlighted associations between problem gambling and the combination of online casino gambling and live sports betting. However, this association was not significant for live-sports betting alone.

Some studies were indicative of a relationship between sports betting and GD severity, with sports betting being a statistical predictor of problem gambling (Hing et al., 2016; Orlowski et al., 2020; Phillips et al., 2013; Russell et al., 2019a, 2019b). Others have reported that problem-gambling severity was the strongest statistical predictor of the frequency of sports betting (). Individuals participating in fantasy sports, including those playing fantasy sports for money, were more likely to report problematic gambling compared to those without such engagement (Lopez-Gonzalez et al., 2019; Martin et al., 2016, 2018), (Martin & Nelson, 2014). Regarding adolescents, the strongest statistical predictor of at-risk gambling for individuals aged 13–15 years was regular participation in daily fantasy sports (Marchica et al., 2017).

Other Gambling Activities and Gambling Frequency

Participation in sports, lottery, and slot-machine gambling have been found to be statistical predictors of sports betting (DiCicco-Bloom & Romer, 2012). Marchica et al. (2017) found that at-risk gambling was statistically predicted by all forms of sport-relevant gambling activities. Other gambling-related variables considered potential risk factors for online sports betting included a higher frequency of sports betting in general and a greater presence of negative attitudes towards gambling (Hing et al., 2017).

In Estévez et al.’s study (2017), online sports betting was associated with higher wagers compared to non-sports online betting and offline gambling. In this vein, Håkansson and Widinghoff (2020) reported that people who combined online casino gambling and live sports betting were more likely to report over-indebtedness, which did not occur in the case of live-sports betting alone. Gambling-related factors, such as betting on a greater number of different sports, more frequent exposure to promotions, and more positive attitudes towards them were statistical predictors of betting on micro-events within sporting events (Russell et al., 2019a, 2019b) or greater intended frequency of sports betting ().

Sports Betting and Psychopathology

In Gainsbury et al.’s study (2019), psychological distress was associated with a higher frequency of sports betting. Similarly, Hing et al. (2017) noticed that problematic online sports betting, as compared to non-problematic online sports betting, was associated with more psychological/emotional distress. Likewise, the use of alcohol and other substances, as well as the presence of other behavioral addictions, have been reported in different studies, with percentages being substantial, ranging from 22.1% to 71.2% among individuals engaged in sports betting (Bodor et al., 2018; Granero et al., 2020; Hing et al., 2017).

Sports Betting and Personality Tendencies

Higher levels of impulsivity, sensation-seeking and positive and negative urgency have been reported among people betting on sports (Cooper et al., 2021). Among the multiple factors analyzed, impulsivity (and more specifically negative urgency) was the measure that most distinguished non-sports-betting and sports-betting groups. DiCicco-Bloom and Romer (2012) observed that one of the most significant statistical predictors of sports betting was sensation-seeking.

When analyzing impulsive in-play bets, Hing et al., (2018a, 2018b) reported that these types of wagers were statistically predicted by problem gambling and greater buying impulsiveness, among other factors. In this vein, Hing et al., (2018a, 2018b) observed that people who gambled on sports immediately before a match were characterized by higher levels of impulsivity, which is in concordance with the study by Jiménez-Murcia et al., (2021).

In reference to persistence as a personality feature, mixed results have been reported. Whereas in some studies it was reported that online sports betting was linked to higher levels of persistence, compared to non-sports online betting and offline gambling (Estévez et al., 2017), others have found that greater sports-betting frequency associated with lower persistence (Jiménez-Murcia et al., 2021). Finally, it has been suggested that, in the case of sports betting, other relevant statistical predictors of problem-gambling severity include lower self-directedness and greater psychopathological distress (Jiménez-Murcia et al., 2021).


The increased participation in sports betting facilitated by online-gambling modalities has led to an increase in the number of sports-betting patients treated in behavioral addiction units (Mestre-Bach et al., 2022). A significant gap in the literature has involved conceptualizing OSB as simply another form of online gambling without attending to the potentially specific risks associated with online or offline forms of sports betting. The present systematic review was conducted to obtain clinically relevant information on sociodemographic characteristics, gambling-related variables, co-occurring psychopathology and personality features related to sports betting.

Most studies included in this systematic review were published within the last decade, underlining the novelty of research in this area. The number of studies reviewed is sufficient to establish sociodemographic and clinical profiles of people who bet on sports who may be at an increased risk of problem or disordered gambling. The present study has synthesized research findings revealing distinctive characteristics of individuals reporting sport betting who suffer from gambling problems.

Gambling problems related to sports betting are associated with being younger, male, single, and college-educated, and experiencing a faster evolution of GD which is often associated with higher levels of severity compared to other subtypes of individuals with gambling problems. We also found that sports betting with gambling problems to be associated with impulsivity sensation-seeking, psychological distress, frequent use of alcohol or other substances and other (non-GD) behavioral addictions. In this sense, sports betting is linked to specific personality profiles with certain biologically based predispositions (e.g., impulsivity, compulsivity and sensitivity to reward and punishment) that may promote vulnerability to addictions. Such an endophenotype may be particularly concerning as it is not only a risk factor for problematic engagement in sports betting, but also a factor that may maintain problematic behaviors across time.

Findings from this systematic review have important implications for prevention and treatment. As sports betting related to problem-gambling risk is linked to younger age, individuals within this subset of the population should be considered a target for preventative actions and programs. As younger individuals with GD are also more likely to drop out of treatment, bolstering the effectiveness of current preventative approaches to decrease the risk of individuals developing problems with gambling is important (Estevez et al., 2021; Ford & Håkansson, 2020; Granero et al., 2020; Jiménez-Murcia et al., 2015). Moreover, as sports-betting advertising has expanded as a form of marketing in sporting events (Bouguettaya et al., 2020; Newall et al., 2019), preventative messages included within these advertising campaigns could help increase awareness of the risks associated with sports betting and knowledge as to when it is important to seek out additional consultation or treatment.

Besides the homogeneity found in the description of people who bet on sports (i.e., male, younger age, single), a recent study identified sports betting with gambling problems to be associated with other distinct features (i.e., earlier onset of gambling activity, higher psychopathological distress, and more dysfunctional personality profile) (Granero et al., 2020). Since this study was conducted in Spain, and most of the studies included within this review were performed in Australia, it will be interesting to increase our efforts in differentiating features linked to sports betting based on cultural backgrounds. This may lead to the development of more specific and effective treatments that are tailored to the needs of people with sports-betting-related GD based on their geographic locations and cultural backgrounds.

Regarding personality, both impulsivity and sensation-seeking have been reported to be frequently present in this profile of individuals with gambling problems (Zilberman et al., 2018) and have been associated with a higher severity or disordered gambling among those meeting the diagnostic criteria (Hing et al., 2018a, 2018b). This may be particularly worrying considering that the types of wagers becoming available via OSB are based on micro-events within sporting events and include in-play bets, which may be particularly attractive to impulsive individuals. This tendency may lead people to spending more money or wagering more frequently than they had initially intended, resulting in various psychological or financial consequences. These findings suggest the importance of the inclusion of features within OSB websites or applications to deactivate certain forms of wagering based on individuals’ preferences or predetermined level of risk. This may be an important aspect to consider in discussions involving regulators and companies providing sports-betting products to an ever-increasing population of people across the globe.

Limitations and Future Research

The studies included in this review have noteworthy limitations. Most studies (1) were cross-sectional, meaning that causality could not be inferred and therefore longitudinal studies are needed to understand temporal relationship between the measured variables; (2) assessed participants using self-administered instruments, which may be subject to biases associated with social desirability or introspective differences; (3) recruited samples using non-probability online panels, which limits the generalizability of the results and could have promoted greater selection of people who bet online versus offline; (4) included small samples; (5) had unbalanced samples, with very low representation of women; and (6) used different instruments to assess each of the measured variables, with this heterogeneity limiting the generalizability of the results. Further, given the heterogeneity of the samples and their geographic locations, with different legislations in different countries, comparability between the studies is complicated and limited.

Limitations specific to the present systematic review should also be noted. First, only studies in English, French and Spanish were included, which could limit generalizability. Second, in some countries, there is considerable gray literature related to GD, as highlighted by other authors (King et al., 2020), which was excluded in the present systematic review due to the desired empirical rigor of the included articles. Third, although the present review was focused on specific sociodemographic and clinical/psychological variables associated with sports betting, there are other factors, including neurobiological, physiological, and sociocultural variables that may be associated with sports betting that were not included. These are hypothetically important variables that should be considered in future reviews.

Based on the findings included within the present systematic review, future investigations of the following topics should be considered. First, empirical studies focused on fantasy sports (both daily and league-based) and their possible associations with GD should be conducted. There was a paucity of such studies included in this review, and this is an important domain of sports betting worth studying. Second, longitudinal studies across different developmental periods (e.g., adolescence, emerging adulthood, adulthood) and involving vulnerable groups are needed to understand the trajectories or maintenance of sports betting and problem/disordered gambling across time while considering factors that may moderate or mediate such relationships.

Clinical Implications

Further exploration of the phenotypes related to sports betting, among both adolescents and adults, especially those with problem gambling, is clinically important. Data obtained regarding risk and maintenance factors associated with sports-gambling behaviors should help treatment-development efforts. Likewise, delving into the possible co-occurrence of problem gambling related to sports betting and other disorders may help to understand poor treatment outcomes in these individuals and promote more personalized interventions.

As described in this systematic review, the findings of the studies published to date suggest that people with sports-gambling-related GD have a specific sociodemographic, clinical and personality profile that differentiates them from others with GD. Thus, their youth, the rapid evolution of the problem, the cognitive distortions (minimizing the risk of sports betting and overestimating their skills and knowledge to obtain prizes), as well as the associated personality traits (high impulsivity and novelty seeking), suggest the need to implement tailor-made treatment programs. In addition, all the characteristics mentioned above are associated with higher likelihoods of dropout from treatment programs. Therefore, cognitive restructuring strategies, the implementation of healthy and alternative leisure activities and the use of new technologies (such as serious games) for the treatment of these underlying personality characteristics, but from a motivating and entertaining environment, may be particularly useful.


Sports betting is becoming increasingly widespread, and a growing number of individuals, both adolescents and adults, are involved in this form of gambling. The present systematic review included studies that explored the sociodemographic and clinical characteristics associated with sports betting. Many studies indicated associations between sports betting and problem gambling. Further, findings indicated that males with high levels of impulsivity reported more frequent engagement in sports betting and had high likelihoods of experiencing gambling problems. Associated psychiatric disorders, especially substance or behavioral addictions, have also been reported. Taken together, the synthesis of findings from this review are an initial step in the direction of identifying individuals at elevated risk for problems associated with sports betting, with further research investigating sports betting and fantasy sports being necessary as the social and technological context of sports betting continues to evolve.