Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

The rate of fatal police shootings in the United States shows large differences based on ethnicity. Among Black Americans, the rate of fatal police shootings between 2015 and December 2024 stood at 6.1 per million of the population per year, while for white Americans, the rate stood at 2.4 fatal police shootings per million of the population per year. Police brutality in the United States Police brutality is a major issue in the United States, but recently saw a spike in online awareness and protests following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Just a few months before, Breonna Taylor was fatally shot in her apartment when Louisville police officers forced entry into her apartment. Despite the repeated fatal police shootings across the country, police accountability has not been adequate according to many Americans. A majority of Black Americans thought that police officers were not held accountable for their misconduct, while less than half of White Americans thought the same. Political opinions Not only are there differences in opinion between ethnicities on police brutality, but there are also major differences between political parties. A majority of Democrats in the United States thought that police officers were not held accountable for their misconduct, while a majority of Republicans that they were held accountable. Despite opposing views on police accountability, both Democrats and Republicans agree that police should be required to be trained in nonviolent alternatives to deadly force.

As of November 17, 277 Black people were killed by the police in the United States in 2024. This compares to 201 Hispanic people and 445 white people. The rate of police shootings of Black Americans is much higher than any other ethnicity, at 6.2 per million people. This rate stands at 2.8 per million for Hispanic people and 2.4 per million for white people.

Between 2015 and 2022, ** percent of police killings of Black people in the United States were committed while the victim was fleeing, the highest percentage of any ethnicity. Over the same time period, ** percent of police killings of Asian Americans occurred while the victim was fleeing - the lowest percentage of any ethnicity.

As of March 13, 479 people were killed by police in the United States in 2025, *** of whom were White. However, the rate of U.S. police killings has been much higher among Black Americans compared to other racial or ethnic groups.

The study was a comprehensive analysis of felonious killings of officers. The purposes of the study were (1) to analyze the nature and circumstances of incidents of felonious police killings and (2) to analyze trends in the numbers and rates of killings across different types of agencies and to explain these differences. For Part 1, Incident-Level Data, an incident-level database was created to capture all incidents involving the death of a police officer from 1983 through 1992. Data on officers and incidents were collected from the Law Enforcement Officers Killed and Assaulted (LEOKA) data collection as coded by the Uniform Crime Reporting (UCR) program. In addition to the UCR data, the Police Foundation also coded information from the LEOKA narratives that are not part of the computerized LEOKA database from the FBI. For Part 2, Agency-Level Data, the researchers created an agency-level database to research systematic differences among rates at which law enforcement officers had been feloniously killed from 1977 through 1992. The investigators focused on the 56 largest law enforcement agencies because of the availability of data for explanatory variables. Variables in Part 1 include year of killing, involvement of other officers, if the officer was killed with his/her own weapon, circumstances of the killing, location of fatal wounds, distance between officer and offender, if the victim was wearing body armor, if different officers were killed in the same incident, if the officer was in uniform, actions of the killer and of the officer at entry and final stage, if the killer was visible at first, if the officer thought the killer was a felon suspect, if the officer was shot at entry, and circumstances at anticipation, entry, and final stages. Demographic variables for Part 1 include victim's sex, age, race, type of assignment, rank, years of experience, agency, population group, and if the officer was working a security job. Part 2 contains variables describing the general municipal environment, such as whether the agency is located in the South, level of poverty according to a poverty index, population density, percent of population that was Hispanic or Black, and population aged 15-34 years old. Variables capturing the crime environment include the violent crime rate, property crime rate, and a gun-related crime index. Lastly, variables on the environment of the police agencies include violent and property crime arrests per 1,000 sworn officers, percentage of officers injured in assaults, and number of sworn officers.

The Family Violence Prevention and Services Act of 1984 (FVPSA) provided funding, through the Office of Victims of Crime in the United States Department of Justice, for 23 law enforcement training projects across the nation from 1986 to 1992. FVPSA was enacted to assist states in (1) developing and maintaining programs for the prevention of family violence and for the provision of shelter to victims and their dependents and (2) providing training and technical assistance for personnel who provide services for victims of family violence. The National Institute of Justice awarded a grant to the Urban Institute in late 1992 to evaluate the police training projects. One of the program evaluation methods the Urban Institute used was to conduct surveys of victims in New York and Texas. The primary objectives of the survey were to find out, from victims who had contact with law enforcement officers in the pre-training period and/or in the post-training period, what their experiences and evaluations of law enforcement services were, how police interventions had changed over time, and how the quality of services and changes related to the police training funded under the FVPSA. Following the conclusion of training, victims of domestic assault in New York and Texas were surveyed through victim service programs across each state. Similar, but not identical, instruments were used at the two sites. Service providers were asked to distribute the questionnaires to victims of physical or sexual abuse who had contact with law enforcement officers. The survey instruments were developed to obtain information and victim perceptions of the following key subject areas: history of abuse, characteristics of the victim-abuser relationship, demographic characteristics of the abuser and the victim, history of law enforcement contacts, services received from law enforcement officers, and victims' evaluations of these services. Variables on history of abuse include types of abuse experienced, first and last time physically or sexually abused, and frequency of abuse. Characteristics of the victim-abuser relationship include length of involvement with the abuser, living arrangement and relationship status at time of last abuse, number of children the victim had, and number of children at home at the time of last abuse. Demographic variables provide age, race/ethnicity, employment status, and education level of the abuser and the victim. Variables on the history of law enforcement contacts and services received include number of times law enforcement officers were called because of assaults on the victim, number of times law enforcement officers actually came to the scene, first and last time officers came to the scene, number of times officers were involved because of assaults on the victim, number of times officers were involved in the last 12 months, and type of law enforcement agencies the officers were from. Data are also included on city size by population, city median household income, county population density, county crime rate, and region of state of the responding law enforcement agencies. Over 30 variables record the victims' evaluations of the officers' responsiveness, helpfulness, and attitudes.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

The killing of Tyre Nichols in January 2023 by Memphis Police Officers has reignited debates about police brutality in the United States. Between 2013 and 2024, over 1,000 people have been killed by police every year. Some of the most infamous examples include the murder of George Floyd in May 2020 and the shooting of Breonna Taylor earlier that year. Within the provided time period, the most people killed by police in the United States was in 2024, at 1,375 people. Police Violence in the U.S. Police violence is defined as any instance where a police officer’s use of force results in a civilian’s death, regardless of whether it is considered justified by the law. While many people killed by police in the U.S. were shot, other causes of death have included tasers, vehicles, and physical restraints or beatings. In the United States, the rate of police shootings is much higher for Black Americans than it is for any other ethnicity, and recent incidents of police killing unarmed Black men and women in the United States have led to widespread protests against police brutality, particularly towards communities of color. America’s Persistent Police Problem Despite increasing visibility surrounding police violence in recent years, police killings have continued to occur in the United States at a consistently high rate. In comparison to other countries, police in the U.S. have killed people at a rate three times higher than police in Canada and 60 times the rate of police in England. While U.S. police have killed people in almost all 50 states, as well as the District of Columbia, New Mexico was reported to have the highest rate of people killed by the police in the United States, with 8.03 people per million inhabitants killed by police.

A growing literature demonstrates the importance of both race and skin color in one’s lived experiences, including interactions with police. Media discourse and anti-police brutality movements consistently emphasize race while little, if any, attention is given to skin color. This paper seeks to examine how Black Americans navigate the multidimensionality of race with respect to organizing efforts against institutionalized racism. Do Black Americans perceive skin color as informing police interactions and/or support incorporating skin color into anti-brutality movement messaging? Is self-identified skin color associated with these views? A combination of 67 in-depth interviews and two national surveys of Black Americans reveals widespread recognition that darker-skinned Black people are more likely to be brutalized by police and feelings that BLM organizing is implicitly associated with skin color. Yet, there is general hesitancy for movement messaging to explicitly engage with subgroup disparities based on characteristics like skin color or gender. Among self-identified darker-skinned individuals, skin color is perceived as even more tightly interwoven with policing and there is more openness to discussing skin color alongside race. Overall, this mixed-methods project highlights how Black Americans perceive the multidimensionality of racialized interactions and, in search of justice, strategize responses through social movement organizing.

Incidents of police violence can undermine trust in legal authorities. Whether such incidents have this effect will depend on how citizens evaluate victims, the police, and public officials. Citizens’ evaluations may be shaped by information about: 1) a pattern of police violence and 2) government responses. We study citizens’ reactions to police violence by randomly assigning these two types of information in the context of the Stephon Clark shooting in Sacramento. We find that information influences levels of blame for and trust in the police, but the effects depend on citizens’ race and whether they live in the community where the violence occurred. In contrast, information does not alter citizens’ perceptions of local police officer organizations and, in turn, their willingness to follow police endorsements in elections. These results suggest a catch-22 whereby police violence can diminish the standing of police personnel, but favorable local opinion preserves their political influence.

This data set contains New York City Police Department count data for domestic violence related offenses (murder, rape, sex offense, felony assault, strangulation and stalking) by the victim's race and the victim's gender for calendar years 2017, 2018 and 2019.

In response to a growing concern about hate crimes, the United States Congress enacted the Hate Crime Statistics Act of 1990. The Act requires the attorney general to establish guidelines and collect, as part of the Uniform Crime Reporting (UCR) Program, data "about crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity, including where appropriate the crimes of murder and non-negligent manslaughter, forcible rape, aggravated assault, simple assault, intimidation, arson, and destruction, damage or vandalism of property." Hate crime data collection was required by the Act to begin in calendar year 1990 and to continue for four successive years. In September 1994, the Violent Crime Control and Law Enforcement Act amended the Hate Crime Statistics Act to add disabilities, both physical and mental, as factors that could be considered a basis for hate crimes. Although the Act originally mandated data collection for five years, the Church Arson Prevention Act of 1996 amended the collection duration "for each calendar year," making hate crime statistics a permanent addition to the UCR program. As with the other UCR data, law enforcement agencies contribute reports either directly or through their state reporting programs. Information contained in the data includes number of victims and offenders involved in each hate crime incident, type of victims, bias motivation, offense type, and location type.

This statistic shows the share of Americans that feel stress over police violence towards minorities in 2016 and 2017. In 2017, 71 percent of Black Americans answered that police violence against minorities was either a very or somewhat significant source of stress.

This dataset contains individual-level homicide and non-fatal shooting victimizations, including homicide data from 1991 to the present, and non-fatal shooting data from 2010 to the present (2010 is the earliest available year for shooting data). This dataset includes a "GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized-access dataset, but with "UNKNOWN" in the shooting column.

Each row represents a single victimization, i.e., a unique event when an individual became the victim of a homicide or non-fatal shooting. Each row does not represent a unique victim—if someone is victimized multiple times there will be multiple rows for each of those distinct events.

The dataset is refreshed daily, but excludes the most recent complete day to allow the Chicago Police Department (CPD) time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

A version of this dataset with additional crime types is available by request. To make a request, please email dataportal@cityofchicago.org with the subject line: Violence Reduction Victims Access Request. Access will require an account on this site, which you may create at https://data.cityofchicago.org/signup.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset. For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.” Officer-involved shootings are not included.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: In some instances, CPD's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most reliable crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: Homicide victims names are delayed by two weeks to allow time for the victim’s family to be notified of their passing.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: This dataset includes variables referencing administrative or political boundaries that are subject to change. These include Street Outreach Organization boundary, Ward, Chicago Police Department District, Chicago Police Department Area, Chicago Police Department Beat, Illinois State Senate District, and Illinois State House of Representatives District. These variables reflect current geographic boundaries as of November 1st, 2021. In some instances, current boundaries may conflict with those that were in place at the time that a given incident occurred in prior years. For example, the Chicago Police Department districts 021 and 013 no longer exist. Any historical violent crime victimization that occurred in those districts when they were in existence are marked in this dataset as having occurred in the current districts that expanded to replace 013 and 021."

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 49 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing, per reporting police agency: an agency header record, and 1 to 49 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to logical record length format with the agency header record variables copied onto the detail records. Consequently, each record contains arrest counts for a particular agency-offense.

This is the final imputed list of API decedents used to calculate rates of fatal police violence experienced by Asian American & Pacific Islander subgroups (2013-2019) in "Disaggregating Asian American and Pacific Islander Risk of Fatal Police Violence" (Schwartz & Jahn, PLOS One 2022). Data include the national/ethnic or regional background of decedents, as well as IDs to link these files to the original source data (Fatal Encounters, or via their Fatal Encounters identifier, Mapping Police Violence). We also provide information on how participants' backgrounds were identified; for more detail, see the published version of the paper referenced above.

Police-reported hate crime, by type of motivation (race or ethnicity, religion, sexual orientation, language, disability, sex, age), selected regions and Canada (selected police services), 2014 to 2023.

This article presents evidence that exposure to officer-involved deaths of low-threat black victims increases political interest and voter turnout among black CMPS respondents under age 40. The analysis takes advantage of variation in the timing of exposure to officer-involved deaths, relative to survey participation, to randomly assign survey respondents to treatment and control conditions. The analysis considers socioeconomic status, police contact, police performance, and other factors that might confound this relationship. The results reveal that victim race, threat level, and visibility affect the likelihood that an officer-involved death will mobilize political interest. Political interest and voter turnout are higher among the treatment group, who were exposed to high-visibility/low-threat Black victims only before they participated in the CMPS, than in the control group, who were exposed to such victims only after they took the survey. Exposing young black respondents to all victims without accounting for threat, visibility, or race does not affect political interest or voter turnout, suggesting the importance of these factors for mobilization. The findings clarify role that Black Lives Matter activists, journalists, and watchdog groups can play in countering the police actions that shape the visibility and framing of black victims of police violence.

Domestic violence data from the Washington Association of Sheriffs and Police Chiefs (WASPC).