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Emerg Radiol. Author manuscript; available in PMC 2024 Jun 13.
Published in final edited form as:
Emerg Radiol. 2024 Feb; 31(1): 7–16.
Published online 2023 Nov 28. doi:10.1007/s10140-023-02188-9
PMCID: PMC11175618
NIHMSID: NIHMS2000786
PMID: 38012430
Bharti Khurana,1,2 Jaya Prakash,1,3 Rohan R. Chopra,1,4 and Randall T. Loder5
Author information Copyright and License information PMC Disclaimer
The publisher's final edited version of this article is available at Emerg Radiol
Abstract
Purpose
Through its associations with mass gatherings, alcohol consumption, emotional cues, and gambling, the Super Bowl (SB) has been implicated in increased rates of interpersonal violence and assaults. This study endeavors to investigate the relationship between assault-related injuries, especially intimate partner violence (IPV) and SB.
Method
A retrospective review of prospectively collected data from the National Electronic Injury Surveillance System (NEISS) spanning 2005 to 2017 was conducted. Assault-related injuries were examined in relation to (1) the 4-day Super Bowl weekend (Friday–Monday), (2) Super Bowl Sunday, and (3) the Super Bowl week (Friday–Thursday) for all years, following the loss of the projected winning team (underdog victories), and losses despite a significant point spread favoring one team (upset losses). National estimates of injuries and associated variables were derived using the SUDAAN software.
Results
While there were no significant differences in the overall number of assaults or assault types during the SB weekend (5.6% vs 5.5%; p = 0.31), relative decreases were observed for altercations (21.1% vs 24.8%; p < 0.01), sexual assault (3.4% vs 4.0%; p < 0.01), and IPV (8.3% vs 12.5%; p < 0.01) on the Friday preceding SB, and robbery incidents on SB Sunday (2.1% vs 3.5%; p = 0.01). No changes in the incidence of assault-related injuries were found based on the favored or underdog status of the teams, including upset losses.
Conclusion
Contrary to expectations, SB was not associated with increased assault-related injuries. This study underscores the need for year-round structural changes in addressing violence rather than relying solely on heightened awareness during specific events.
Keywords: Assault, Injuries, Super Bowl, Intimate partner violence, Interpersonal violence altercation, Robbery
Introduction
Over the past few decades, the effect of sporting events on interpersonal violence perpetration has been a topic of discussion. Mass gatherings during sporting events have been associated with increased rates of intimate partner violence (IPV) and sexual assault [1, 2]. These trends are largely thought to be fueled by the “holy trinity of sports, alcohol, and hegemonic masculinity.” [3] To date, the relationship between sporting events and crime has been explored using routine activity theory. This theory posits that “structural changes in routine activity patterns can influence crime rates by affecting the convergence in space and time of the three minimal elements of direct-contact predatory violations: (1) motivated offenders, (2) suitable targets, and (3) the absence of capable guardians against a violation.” [4] The application of routine activity theory to sporting events argues that such an event destabilize a person’s normal routine due to alterations in their normal routine and environment. Noncriminal individuals are likely to experience higher susceptibility to criminal offenders when the three elements above are satisfied, resulting in increased violence.
The National Football League’s annual Super Bowl (SB), an iconic American sporting event, is one of the most widely watched sporting events in the US, capturing the attention of the general public across the nation [5]. Given its association with large gatherings, alcohol consumption, and emotional cues due to high expectations, SB has been associated with increased rates of violence in prior studies [5, 6]. Two studies noted increased partner maltreatment on SB Sunday—one from a clinical database from the US Air Force [7] and another using incident-based reporting data from Idaho [8]. Conflicting evidence from other studies, however, raises questions about this relationship. Two studies examining the association between professional football events and intimate partner violence (IPV) found no significant associations between the professional football season and emergency department (ED) visits or sheriff dispatches for IPV [8, 9]. In a 1992 study, White et al. [10] found increased rates of female ED presentations for IPV-related traumatic injuries that were associated with the local football team’s victories, bringing into question the role of sporting outcomes in interpersonal violence perpetration.
The role of sporting outcomes is particularly relevant in professional football, as it is the most popular sport for wagers in the US, making up nearly half of all sports bets in the country. Thus, the SB annually tops the list as one of the most wagered events (i.e., the largest betting volume) in the world [11-13]. Sports betting has recently become more accessible with the expansion of legalized betting and online gambling opportunities. Sports betting is now legal in 34 US states and Washington DC [14], and almost 25% of US adults in 2023 placed a bet on the Super Bowl totaling up to $16 billion in wagers [15]. Up to $6.8 billion dollars were circulated in sports betting for the 2020 SB alone, of which 95% of bets were placed illegally [16-18].
For the SB, following the conclusion of the American Football Championship and National Football Championship games, one team is deemed to be the SB “favorite” (i.e., the team favored to win) and the other is deemed to be the “underdog” (i.e., the team not favored to win). There are two major types of bets in the NFL: a point spread bet and a moneyline bet [19]. A point spread refers to the difference between the points scored by the winning team and the points scored by the losing team with bets based on the margin of victory. In a moneyline bet, bettors select the winning team, with odds adjusted based on team strength. A bet on the winning team, regardless of the score or point difference, results in a win. Different prices are offered for favorites and underdogs. An “upset loss” occurs when the favored team loses by four or more points to the underdog [20]. Such losses may be associated with increased perpetration of violence [6, 13]. Criminal justice research has shown a link between upset losses and an increased rate of IPV based on a higher number of phone calls reporting IPV [20]. In contrast, expected losses and upset wins (i.e., the home team wins when the home team was expected to lose) had little to no impact on IPV [20]. However, the existing literature addressing the relationship between sporting events and injuries related to assaults and IPV in the US is deficient. This is particularly critical for emergency radiologists, who are increasingly recognized for their pivotal role in identifying injuries stemming from interpersonal violence and assaults, including IPV. Understanding the potential surge in such injuries around major events like SB enables emergency radiologists to anticipate and accurately identify the nature and extent of injuries, leading to more effective and timely patient care. To address this gap, we aimed to investigate patterns of ED visits for assault-related injuries using data from the National Electronic Injury Surveillance System’s (NEISS) All Injury Program (AIP) during multiple time frames, (1) the 4-day Super Bowl weekend (Friday–Monday), (2) Super Bowl Sunday itself, and (3) the Super Bowl week (Friday–Thursday) following the loss of the projected winning team (underdog victories) and the losses despite a significant point spread favoring one team (upset losses).
Materials and methods
Study design
This study utilized data sourced from the National Electronic Injury Surveillance System’s (NEISS) All Injury Program (AIP). The NEISS is a meticulously organized database managed by the US Consumer Product Safety Commission (USCPSC), which collects injury data from 96 hospitals in the United States and its territories having an ED and is very often used in injury research. This dataset is a widely recognized resource in the field of injury research. By employing appropriate statistical methodologies, it allows researchers to extrapolate national estimates of ED visits. Initially designed to capture injuries associated with consumer products, NEISS recognizes that not all injuries are product-related. Consequently, approximately 65 of these hospitals (with slight annual variations in numbers) were chosen by the USCPSC to provide data on all injuries, irrespective of their connection to consumer products. This specific dataset, stemming from this select group of hospitals, is referred to as the AIP. The NEISS AIP data is publicly available and is maintained by the Inter-University Consortium for Political and Social Research (ICPSR). Access to this dataset can be obtained at https://www.icpsr.umich.edu/icpsrweb/ICPSR/search/studies?q=all+injury+program. The use of this publicly accessible, de-identified data was granted an exemption by our local Institutional Review Board.
The database includes the date of the ED visit, gender/race/age of the injured patient, diagnosis, disposition from the ED, incident locale, body part injured, perpetrator and type of assault, reason for the assault, causative agent/mechanism of the injury, and hospital size. Hospital size (strata) are defined by the number of ED visits per year which are small [1-16], medium [16,831–21,850], large [28,151–41,130], and very large [> 41,130], and one encompassing children’s hospitals of all sizes.
The NEISS-AIP data for the years 2005 through 2017 was used. This period was chosen because 2017 was the last available year at the time the study began in October 2021. (The AIP data typically lags a few years behind the actual year). Data collected prior to 2005 employed different coding conventions for many variables, rendering it challenging to integrate with data from subsequent years. In this study, injury results resulting from assaults were identified using the code INTENT = 1 (assault). The NEISS definition of assault is any injury from an act of violence where physical force by one or more persons is used with the intent of causing harm, injury, or death to another person, or an intentional poisoning by another person [21]. This category includes perpetrators as well as intended and unintended victims of violent acts (e.g., innocent bystanders); it excludes unintentional shooting victims (other than those occurring during an act of violence), unintentional drug overdoses, and children or teenagers “horsing” around. The type of assault was identified by the code REASON, and classified by NEISS as altercation, robbery/burglary, drug-related, sexual assault, gang-related, other specified, and unknown/not specified. An altercation was defined as a heated argument or dispute over traffic, children, gambling, money, property, sex jealousy, politics, ethnicity, race, or sexual preference. Sexual assault was defined as the use of physical force to compel another person to engage in a sexual act against his or her will with attempted or completed sex acts and abusive sexual contact. The other specified category included injuries related to drive-by-shooting, homicide-suicide pacts, mercy killing, revenge, blackmail, extortion, ransom, kidnapping, and contact injuries. When there was inadequate or no information in the narrative to describe the type of assault, it was categorized as unknown in the NEISS database. IPV was defined as INTENT = 1 and PERP (perpetrator of the assault) = 1 (spouse/partner).
Three different methods were used to define the SB time interval: SB Sunday, the entire SB weekend defined as Friday through Monday (SB weekend), and the SB week from Friday to Thursday. The control groups were the Sunday before and after the SB Sunday, the weekend before and after the SB weekend, and the week before and after the SB week. To investigate the effect of underdog victories and upset losses, we used a sports betting database’s archives consisting of the point spread and final score to identify “unexpected” SB underdog victories from 2004 (SB XXXVIII) to 2018 (SB LII) [22]. An underdog victory was defined as a win by the non-favored team. During this period, eight out of fifteen SBs resulted in underdog victories. For these SBs with underdog victories, we further identified upset losses by scrutinizing the point spread. Upset losses represent a subset of underdog wins, where the favored team was expected to win by four or more points. Among the eight underdog victories from 2004 to 2018, five fell into the category of upset losses (Table 1). Subsequently, we conducted comparisons of the number of assault-related injury incidents for all three time frames.
Table 1
Point spread and upset losses for 2004–2016 Super Bowl
| Super Bowl (season) | Date | Favored team | Spread | Underdog team | Winner |
|---|---|---|---|---|---|
| Favored team victories | |||||
| 2016 LI | 2/5/17 | New England Patriots | −3 | Atlanta Falcons | New England Patriots |
| 2010 XLV | 2/6/11 | Green Bay Packers | −3 | Pittsburgh Steelers | Green Bay Packers |
| 2008 XLIII | 2/1/09 | Pittsburgh Steelers | −6.5 | Arizona Cardinals | Pittsburgh Steelers |
| 2006 XLI | 2/4/07 | Indianapolis Colts | −6.5 | Chicago Bears | Indianapolis Colts |
| 2005 XL | 2/5/06 | Pittsburgh Steelers | −4 | Seattle Seahawks | Pittsburgh Steelers |
| 2004 XXXIX | 2/6/05 | New England Patriots | −7 | Philadelphia Eagles | New England Patriots |
| Underdog victories | |||||
| 2015 L | 2/6/16 | Carolina Panthers | −5 | Denver Broncos | Denver Broncos |
| 2014 XLIX | 2/1/15 | Seattle Seahawks | −1 | New England Patriots | New England Patriots |
| 2013 XLVIII | 2/2/14 | Denver Broncos | −2.5 | Seattle Seahawks | Seattle Seahawks |
| 2012 XLVII | 2/3/13 | San Francisco 49ers | −4.5 | Baltimore Ravens | Baltimore Ravens |
| 2011 XLVI | 2/5/12 | New England Patriots | −3 | New York Giants | New York Giants |
| 2009 XLIV | 2/7/10 | Indianapolis Colts | −4.5 | New Orleans Saints | New Orleans Saints |
| 2007 XLII | 2/3/08 | New England Patriots | −12.5 | New York Giants | New York Giants |
| Upset losses (underdog victories with spreads > 4) | |||||
| 2015 L | 2/6/16 | Carolina Panthers | −5 | Denver Broncos | Denver Broncos |
| 2012 XLVII | 2/3/13 | San Francisco 49ers | −4.5 | Baltimore Ravens | Baltimore Ravens |
| 2009 XLIV | 2/7/10 | Indianapolis Colts | −4.5 | New Orleans Saints | New Orleans Saints |
| 2007 XLII | 2/3/08 | New England Patriots | −12.5 | New York Giants | New York Giants |
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Calculation
The national estimates of ED visits due were obtained s using SUDAAN 11.0.01™ software (RTI International, Research Triangle Park, NC, 2013) which accounts for the weighted, stratified nature of the data. The estimated number (N) of injuries/ED visits is calculated along with 95% confidence intervals [CIs] of the estimate. When the actual number of patients (n) is < 20, the estimated number (N) becomes unstable and should be interpreted with caution; thus, we report both the n and N. Analyses between groups of continuous data were performed with the t-test (2 groups) or ANOVA (3 or more groups). Differences between groups of categorical data were analyzed by the χ2 test.
Results
All injuries, including transportation
We first analyzed the entire NEISS AIP data for the three four-day weekends (SB weekend, weekend before SB, and weekend after SB) for all injuries—including those due to transportation, as it could be hypothesized that more people were traveling by car during SB week—which might influence the number of assault-related injuries. The numbers in the control groups are typically double that of the SB group, as the SB group comprises only one day/weekend, while the control comprises both the day/weekend before and after SB assault-related injuries represented 5.6% of all injuries during the four-day SBW and 5.5% for the control timeframe with no significant difference in the number of assault-related injuries (p = 0.31) (Table 2). Similarly, there was no difference in the percentage of assault injuries, including transportation for the SB Sunday and SB week timeframes. No differences in the percentage of assault-type injuries were observed during the SB weekend or week but there was a relative decrease in the percentage of robberies for SB Sunday itself (p = 0.008) (Table 2) (Fig. 1A).
Fig. 1
A The percentage of ED visits due to assault-related injuries on SB Sunday by assault type. B The percentage of ED visits for assault-related injuries on Friday before the Superbowl by assault type
Table 2
Number of ED visits for all assaults and assault types encompassing all 4 days of the Super Bowl weekend including injuries due to transportation mechanisms
| FOR ENTIRE SUPER BOWL 4 DAY WEEKEND | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All | Super Bowl | Control | ||||||||||||||
| n | N | L95% | U95% | % | n | N | L95% | U95% | % | n | N | U | L95% | % | p value | |
| Assault | 200,155 | 11,898,714 | 67,214 | 3,981,141 | 132,941 | 7,917,574 | ||||||||||
| Y | 12,448 | 659,556 | 533,062 | 813,872 | 5.5 | 4,266 | 224,919 | 178,355 | 283,059 | 5.6 | 8,182 | 434,637 | 6.72 | 354,707 | 5.5 | 0.31 |
| N | 187,707 | 11,239,158 | 11,084,842 | 11,365,652 | 94.5 | 62,948 | 3,756,222 | 3,698,082 | 3,802,786 | 94.4 | 124,759 | 7,482,937 | 95.52 | 7,385,513 | 94.5 | |
| Altercation | ||||||||||||||||
| Y | 3,091 | 171,004 | 139,215 | 209,417 | 1.4 | 1,099 | 60,817 | 47,376 | 77,632 | 1.5 | 1,992 | 110,188 | 1.68 | 91,844 | 1.4 | |
| N | 197,064 | 3,920,324 | 11,689,297 | 11,759,499 | 32.9 | 66,115 | 3,920,324 | 3,903,509 | 3,933,765 | 98.5 | 130,949 | 7,807,386 | 98.84 | 7,784,559 | 98.6 | |
| Robbery | ||||||||||||||||
| Y | 306 | 14,855 | 9,519 | 23,797 | 0.1 | 110 | 5,093 | 3,185 | 8,360 | 0.1 | 196 | 9,763 | 0.20 | 6,334 | 0.1 | 0.77 |
| N | 199,849 | 11,883,859 | 11,874,917 | 11,889,195 | 99.9 | 67,104 | 3,976,048 | 3,972,781 | 3,977,956 | 99.9 | 132,745 | 7,907,811 | 99.92 | 7,901,739 | 99.9 | |
| Sexual Assault | ||||||||||||||||
| Y | 841 | 29,357 | 23,797 | 35,696 | 0.2 | 288 | 9,646 | 7,564 | 12,342 | 0.2 | 553 | 19,711 | 0.32 | 15,835 | 0.2 | 0.83 |
| N | 199,314 | 11,869,357 | 11,863,018 | 11,874,917 | 99.8 | 66,926 | 3,971,494 | 3,968,799 | 3,973,577 | 99.8 | 132,388 | 7,897,863 | 99.80 | 7,892,238 | 99.8 | |
| Other Specified | ||||||||||||||||
| Y | 210 | 9,507 | 7,139 | 13,089 | 0.1 | 65 | 3,056 | 1,991 | 4,777 | 0.1 | 145 | 6,451 | 0.12 | 4,751 | 0.1 | 0.79 |
| N | 199,945 | 11,889,208 | 11,885,625 | 11,891,575 | 99.9 | 67,149 | 3,978,085 | 3,976,364 | 3,979,150 | 99.9 | 132,796 | 7,911,123 | 99.94 | 7,908,073 | 99.9 | |
| Unknown Type | ||||||||||||||||
| Y | 7,984 | 433,757 | 346,253 | 541,391 | 3.6 | 2,699 | 146,025 | 115,453 | 184,327 | 3.7 | 5,285 | 287,732 | 4.53 | 230,401 | 3.6 | 0.75 |
| N | 192,171 | 11,464,957 | 11,357,323 | 11,552,461 | 96.4 | 64,515 | 3,835,116 | 3,796,814 | 3,865,688 | 96.3 | 127,656 | 7,629,841 | 97.09 | 7,558,908 | 96.4 | |
| IPV | ||||||||||||||||
| Y | 1,365 | 78,464 | 65,443 | 92,810 | 0.7 | 460 | 27,032 | 22,693 | 31,849 | 0.7 | 905 | 51,432 | 0.79 | 41,963 | 0.6 | 0.53 |
| N | 198,790 | 11,820,251 | 11,805,904 | 11,833,271 | 99.3 | 66,754 | 3,954,109 | 3,949,292 | 3,958,448 | 99.3 | 132,036 | 7,866,142 | 99.47 | 7,855,025 | 99.4 | |
| FOR ONLY SUPER BOWL SUNDAY | ||||||||||||||||
| All | Super Bowl | Control | ||||||||||||||
| n | N | L95% | U95% | % | n | N | L95% | U95% | % | n | N | L95% | U95% | % | p value | |
| Assault | 48,776 | 2,888,545 | 16,443 | 962,883 | 32,333 | 1,925,662 | ||||||||||
| Y | 3,347 | 183,821 | 150,782 | 223,285 | 6.4 | 1,170 | 63,378 | 50,455 | 79,342 | 6.6 | 2,177 | 120,443 | 99,942 | 144,810 | 6.3 | 0.29 |
| N | 45,429 | 2,704,724 | 2,665,260 | 2,737,763 | 93.6 | 15,273 | 899,506 | 883,541 | 912,428 | 93.4 | 30,156 | 1,805,219 | 1,780,852 | 1,825,720 | 93.7 | |
| Altercation | ||||||||||||||||
| Y | 826 | 48,680 | 39,862 | 59,215 | 1.7 | 300 | 18,021 | 13,577 | 23,879 | 1.9 | 526 | 30,659 | 25,419 | 36,780 | 1.6 | 0.19 |
| N | 47,950 | 2,839,865 | 2,829,330 | 2,848,683 | 98.3 | 16,143 | 944,862 | 939,004 | 949,306 | 98.1 | 31,807 | 1,895,003 | 1,888,882 | 1,900,243 | 98.4 | |
| Robbery | ||||||||||||||||
| Y | 78 | 3,419 | 2,022 | 6,066 | 0.1 | 20 | 693 | 289 | 1,541 | 0.1 | 58 | 2,726 | 1,541 | 4,622 | 0.1 | 0.0008 |
| N | 48,698 | 2,885,126 | 2,882,479 | 2,886,523 | 99.9 | 16,423 | 962,190 | 961,342 | 962,594 | 99.9 | 32,275 | 1,922,936 | 1,921,040 | 1,924,121 | 99.9 | |
| Sexual Assault | ||||||||||||||||
| Y | 217 | 8,311 | 6,066 | 11,265 | 0.3 | 79 | 3,109 | 2,215 | 4,333 | 0.3 | 138 | 5,203 | 3,466 | 7,895 | 0.3 | 0.42 |
| N | 48,559 | 2,880,234 | 2,877,280 | 2,882,479 | 99.7 | 16,364 | 959,775 | 958,550 | 960,668 | 99.7 | 32,195 | 1,920,459 | 1,917,767 | 1,922,196 | 99.7 | |
| Other Specified | ||||||||||||||||
| Y | 53 | 2,510 | 1,733 | 3,755 | 0.1 | 16 | 625 | 289 | 1,155 | 0.1 | 37 | 1,885 | 963 | 3,466 | 0.1 | 0.42 |
| N | 48,723 | 2,886,035 | 2,884,790 | 2,886,812 | 99.9 | 16,427 | 962,259 | 961,728 | 962,594 | 99.9 | 32,296 | 1,923,777 | 1,922,196 | 1,924,699 | 99.9 | |
| Unknown Type | ||||||||||||||||
| Y | 2,167 | 120,479 | 97,633 | 148,471 | 4.2 | 753 | 40,816 | 32,160 | 51,611 | 4.2 | 1,414 | 79,664 | 65,087 | 97,438 | 4.1 | 0.62 |
| N | 46,609 | 2,768,066 | 2,740,074 | 2,790,912 | 95.8 | 15,690 | 922,068 | 911,272 | 930,723 | 95.8 | 30,919 | 1,845,998 | 1,828,224 | 1,860,575 | 95.9 | |
| IPV | ||||||||||||||||
| Y | 365 | 21,836 | 17,620 | 27,152 | 0.8 | 131 | 8,103 | 6,451 | 10,207 | 0.8 | 234 | 13,732 | 10,399 | 18,101 | 0.7 | 0.24 |
| N | 48,411 | 2,866,710 | 2,861,393 | 2,870,925 | 99.2 | 16,312 | 954,780 | 952,676 | 956,432 | 99.2 | 32,099 | 1,911,930 | 1,907,561 | 1,915,263 | 99.3 | |
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Assaults for Friday, Saturday, and Monday outside of SB Sunday
There were only differences for the Friday before SB Sunday but not for the Saturday before or Monday after (Table 3). There was a relative decrease in the incidence of IPV (8.3% vs 12.5%; p = 0.0001), altercation (21.1% vs 24.8%; p = 0.0001), sexual assault (3.4% vs 4.0%; p = 0.006) with a relative increase in robbery (3.5% vs 2.1%; p = 0.012) and unknown injuries (61.1% vs 55.3%; p = 0.0001) on the Friday before the Super Bowl (Table 3) (Fig. 1B).
Table 3
Number of ED visits by assault type outside of SB Sunday by day
| Super Bowl | Control | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | N | L95% | U95% | % | n | N | L95% | U95% | % | P-value | P-value^ | |
| FRIDAY | ||||||||||||
| Assault type | 964 | 47,843 | 21.3 | 1766 | 93,246 | 21.5 | ||||||
| Altercation | 227 | 10,102 | 8176 | 12,343 | 21.1 | 416 | 23,127 | 20,374 | 26,118 | 24.8 | 0.0001 | 0.0001 |
| Robbery | 31 | 1672 | 1053 | 2636 | 3.5 | 43 | 1997 | 1222 | 3236 | 2.1 | 0.012 | |
| Sexual assault | 59 | 1614 | 957 | 2703 | 3.4 | 107 | 3734 | 2639 | 5250 | 4.0 | 0.006 | |
| Other | 19 | 1224 | 694 | 2143 | 2.6 | 40 | 1159 | 727 | 1846 | 1.2 | 0.12 | |
| Unknown | 546 | 29,251 | 27,132 | 31,289 | 61.1 | 973 | 51,552 | 48,134 | 54,922 | 55.3 | 0.0001 | |
| IPV | 82 | 3979 | 3043 | 5172 | 8.3 | 187 | 11,676 | 9698 | 13,987 | 12.5 | 0.0001 | |
| SATURDAY | ||||||||||||
| Assault type | 1,101 | 58,713 | 2203 | 114,802 | ||||||||
| Altercation | 240 | 13,067 | 11,343 | 14,972 | 22.3 | 448 | 24,500 | 20,928 | 28,494 | 21.3 | 0.14 | |
| Robbery | 34 | 1587 | 957 | 2619 | 2.7 | 44 | 2234 | 1596 | 3134 | 1.9 | ||
| Sexual assault | 65 | 2452 | 1468 | 4045 | 4.2 | 148 | 5683 | 3857 | 8312 | 5.0 | ||
| Other | 10 | 282 | 100 | 816 | 0.5 | 30 | 1271 | 804 | 2021 | 1.1 | ||
| Unknown | 619 | 33,565 | 31,058 | 36,015 | 57.2 | 1275 | 67,391 | 61,970 | 72,635 | 58.7 | ||
| IPV | 133 | 7760 | 6053 | 9858 | 13.2 | 258 | 13,724 | 11,492 | 16,313 | 12.0 | ||
| MONDAY | ||||||||||||
| Assault type | 1,119 | 59,964 | 1940 | 100,571 | ||||||||
| Altercation | 269 | 15,697 | 13,630 | 17,917 | 26.2 | 430 | 22,385 | 19,521 | 25,535 | 22.3 | 0.43 | |
| Robbery | 24 | 1007 | 648 | 1559 | 1.7 | 49 | 2753 | 1820 | 4154 | 2.7 | ||
| Sexual assault | 88 | 2375 | 1649 | 3400 | 4.0 | 128 | 3635 | 2323 | 5652 | 3.6 | ||
| Other | 18 | 813 | 456 | 1451 | 1.4 | 26 | 1377 | 835 | 2273 | 1.4 | ||
| Unknown | 593 | 32,320 | 29,736 | 34,869 | 53.9 | 1088 | 58,479 | 54,238 | 62,595 | 58.1 | ||
| IPV | 127 | 7752 | 5805 | 10,236 | 12.9 | 219 | 11,942 | 9826 | 14,442 | 11.9 | ||
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*Excluding IPV
^Post hoc goodness-of-fit p-values
Favored and underdog victories
There was no change in the overall percentage of assaults and type of assaults based on favored and underdog victories, including upset losses for all three time- frames (Table 4).
Table 4
Number of ED visits by assault types for (A) favored victories vs underdog victories and (B) upset losses with a spread of at least 4 vs upset losses with a spread of less than 4 for the SB weekend timeframe
| (A) | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Assault type | Upset loss | Not upset loss | |||||||||||||
| n = 1821 | N = 89,306 | U | L | U% | L% | % | N = 889 | N = 48,428 | U | L | U% | L% | % | P-value | |
| Altercation | 392 | 19,341 | 24.63 | 18.96 | 21,996 | 16,932 | 21.7 | 227 | 11,854 | 29.05 | 20.42 | 14,068 | 9,889 | 24.5 | 0.28 |
| Robbery | 48 | 2193 | 3.48 | 1.74 | 3104 | 1554 | 2.5 | 18 | 1102 | 3.53 | 1.46 | 1710 | 707 | 2.3 | 0.18^ |
| Sexual assault | 148 | 5233 | 8.18 | 4.17 | 7305 | 3724 | 5.9 | 61 | 2145 | 7.16 | 2.71 | 3467 | 1312 | 4.4 | |
| Other specified | 26 | 1017 | 2.26 | 0.57 | 2018 | 509 | 1.1 | 17 | 722 | 2.79 | 0.79 | 1351 | 383 | 1.5 | |
| Unknown | 1017 | 51,079 | 65.25 | 5.17 | 58,272 | 4616 | 57.2 | 475 | 26,724 | 59.83 | 50.45 | 28,974 | 24,432 | 55.2 | |
| IPV | 190 | 10,442 | 15.69 | 8.61 | 14,012 | 7689 | 11.7 | 91 | 5881 | 15.44 | 9.47 | 7477 | 4586 | 12.1 | 0.82* |
| (B) | |||||||||||||||
| Assault type | Upset loss with spread of at least 4 | Upset loss with spread less than 4 | |||||||||||||
| n = 1,219 | N = 59,526 | U | L | U% | L% | % | n = 1,491 | N = 78,210 | U | L | U% | L% | % | P-value | |
| Altercation | 261 | 13,033 | 24.94 | 19.12 | 14,846 | 11,381 | 21.9 | 358 | 18,162 | 27.03 | 19.80 | 21,140 | 15,486 | 23.2 | 0.94 |
| Robbery | 32 | 1377 | 3.13 | 1.71 | 1863 | 1018 | 2.3 | 34 | 1918 | 3.42 | 1.75 | 2675 | 1369 | 2.5 | 0.90^ |
| Sexual assault | 92 | 3143 | 7.77 | 3.56 | 4625 | 2119 | 5.3 | 117 | 4235 | 7.72 | 3.77 | 6038 | 2949 | 5.4 | |
| Other specified | 17 | 637 | 3.36 | 0.34 | 2000 | 202 | 1.1 | 26 | 1102 | 2.23 | 0.89 | 1744 | 696 | 1.4 | |
| Unknown | 694 | 34,748 | 64.95 | 51.48 | 38,662 | 30,644 | 58.4 | 798 | 43,055 | 58.59 | 51.46 | 45,823 | 40,247 | 55.1 | |
| IPV | 123 | 6586 | 16.00 | 7.51 | 9524 | 4470 | 11.1 | 158 | 9737 | 14.90 | 10.29 | 11,653 | 8048 | 12.4 | 0.47* |
Open in a separate window
^Excludes IPV
*Includes only IPV yes vs no
Upset losses and no upset losses
There was no change in the overall percentage of assaults and type of assaults based on upset losses for all three time frames (Table 4).
Discussion
Several hypotheses have been proposed linking the SB with increased interpersonal violence. First, there is a belief that increased drinking during sporting events such as the SB is associated with increased IPV and sexual assault [23-28]. Second, there is reason to believe that strong emotional cues based on the outcome of a sporting event might impact violence. “Emotional cues” largely refer to visceral factors that can influence a person’s state of being (sexual desire, hunger, pain, anger, etc.) and thereby motivate specific behaviors. Regarding IPV, “hypermasculine activity in which physical force is used to successfully overcome others increases the likelihood that male spectators will become physically aggressive with their partners,” [10] creating a possible mechanism for SB viewing to lead to increased violence perpetration. This hypothesis aligns with prior findings, yet inconsistent with other studies, that IPV is more likely if the perpetrator’s team unexpectedly loses. Upset losses have been reported to be associated with increased at-home violence and IPV by men against their partners [20,29]. Third, as problem gambling has been associated with significantly increased odds of IPV, the high volume of sports betting during the SB may increase violence perpetration during and/or following the event [30, 31]. In fact, a 2000 study examining the link between professional football games and domestic violence using Los Angeles Sheriff Department’s data from 1993 to 1995, found a substantial increase in domestic violence dispatches during playoff and SB weeks, though the overall study did not find a statistically significant association between the football games and domestic violence in Los Angeles County [32].
Despite these hypotheses, our study failed to demonstrate any statistically significant increase in IPV or any other interpersonal violence during the SB Sunday, throughout the SB weekend, or the weekdays after the SB compared to the respective time frames before and after the SB based on the number of assault-related injuries seen in Emergency Departments. While our findings may contradict popular belief, they align with Pena Alexandra’s study assessing the influence of NFL’s SB event on host crime rates from 1990 to 2012 by analyzing 8 different crime trends before, during, and after the event and observing no significant impact on the crime rate of the host city [5].
Misinformation regarding the SB and its alleged association with IPV can be attributed to several factors. The SB draws immense viewership, making it a focal point for media attention, and this attention extends to the NFL and its players. Over the years, the NFL and its players have received significant media attention for their involvement in violent incidents. According to the USA Today’s NFL Arrest Database, 134 players in the NFL have been arrested for IPV since the year 2000 and an additional 15 have been arrested for sexual assault, battery, and/or solicitation [33]. However, the complexity arises when examining the legal outcomes of these cases. A recent study has found that among the 117 NFL players arrested for violence against women between 2000 and 2019, only 21 were ultimately found guilty, and a mere six players were incarcerated [34]. Notably, the study emphasized that the post-arrest career trajectories of these players were predominantly influenced by their on-field value and performance rather than their legal consequences [34]. This lack of accountability and incongruity can foster the development of strong associations between the SB, often regarded as the NFL's flagship event, and a culture of violence [35]. Regrettably, some abusers may perceive NFL players as role models, potentially normalizing such behavior. Victims of domestic violence, on the other hand, may feel threatened and apprehensive as they continue to witness alleged abusers playing and achieving success. This dissonance between media coverage, social media posts, arrests, legal outcomes, and player success shapes public perceptions and contributes to spreading misinformation regarding the SB and its connection to IPV.
Our study found that the lack of connection between SB outcomes and assault-related injuries persisted even in cases of underdog wins and upset losses, emphasizing the complexity and multifaceted nature of the relationship between sports gambling, upset losses, and IPV. This intricate association is influenced by a range of factors, including individual personality traits, pre-existing dynamics within relationships, and the severity of gambling losses. Interviews of 30 women who had experienced IPV due to a male partner’s gambling behavior identified five key elements contributing to this relationship: (1) rigid gender roles of males as authority figures in the relationship, (2) relationships normalizing aggression, (3) attitudes normalizing violence, (4) male as decision-maker in the relationship, and (5) limited female autonomy as well as increased isolation [36]. In other words, sports and gambling create “an intentional and sustained pattern of conduct…to induce fear through the invasive and intrusive tactics of intimidation, confinement, restriction, surveillance, isolation, and threats [37].”
We also explored the previous literature describing potential associations between drinking and sports events. As pointed out by Oths and Robertson, it is essential to recognize that individuals with substance abuse issues may not limit their intoxication to specific occasions, as they may view each weekend as an opportunity for heavy drinking, which can contribute to persistent patterns of crisis calls and shelter admissions across the year [6]. The persistence of these issues is likely rooted in broader social structures and institutions that tolerate violence. For example, certain social and cultural behaviors, such as resource competition, alcohol-related violence, arguments, and sexism have been correlated with increased violence perpetration within the US [6]. These sociocultural behaviors that are associated with violence persist year-round, and our national sociocultural landscape is unlikely to undergo significant change due to a single event like SB.
Of note, we found a statistically significant decrease in robbery-related injuries and a decrease in IPV-related injuries on the Friday preceding SB Sunday compared to the control Fridays before and after SB Friday. The decreased incidence of robbery-related injuries during SB Sunday may be explained by routine activity theory. Although the SB may present more potential victims and opportunities for robbery, our finding aligns with prior studies noting that economically motivated crimes occur less frequently on holidays [18]. Increased guardianship by family, friends, and security protecting potential victims by virtue of social gatherings and residence-based activities during the SB, might explain this pattern [31]. Regarding the decrease in IPV-related injuries and altercations on the Friday of SBW, the SB event itself has been associated with positive emotional sentiments of pride, excitement, attachment, and community spirit [38]. Social gatherings and viewing parties are hosted to foster a sense of community, fortify local pride, and celebrate belonging through this event [39]. Further, regardless of the outcome, watching the SB game in and of itself has been associated with a baseline level of entertainment that provides an average positive effect [40]. These positive sociocultural associations preceding the SB event may outweigh triggers for IPV perpetration.
The limitations of this study must also be acknowledged. This study considers injuries only seen in US EDs and is not representative of injuries treated in additional healthcare settings such as outpatient care, urgent centers, women’s health centers, etc. The NEISS dataset that was used in our data collection and analysis is nationally representative and unable to provide regional or state-level data. Local variations in IPV based on the wins or losses of each SB and team allegiance could not be elucidated from our project. Thus, it is possible that there are microcosms of increased assaults/IPV in the actual cities where the SB is played for each particular year. We have no information regarding those patients who experienced nonviolent events (e.g. emotional IPV) or those not severe enough to result in ED visits.
Conclusions
In conclusion, our study dispels the misconception of an alleged link between SB and IPV by comprehensively analyzing injury data and SB outcomes, revealing no increase in the incidence of overall assaults or specific types of assaults, including IPV during Superbowl Sunday, Superbowl weekend, the week following the Superbowl, underdog victories, or upset losses. These findings indicate that interpersonal violence is pervasive throughout the year and does not change significantly in the context of a single sporting event. Rather than attributing it solely to specific events, such as SB, our prevention efforts should target structural changes and foster enduring interventions that address the intricate roots of violent behavior, moving beyond temporary measures to more sustainable solutions.
Funding
Bharti Khurana received support from the National Institute of Biomedical Imaging and Bioengineering (NIBIB); the Office of the Director, National Institutes of Health (1R01eb032384-01a1); and the National Academy of Medicine of the National Academy of Sciences of award number SCON#10000745 as part of the Scholar in Diagnostic Excellence Program.
Footnotes
Conflict of interests The authors declare that they have no conflict of interest.
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