That's a higher rate than 49% of US Police Departments.
We obtained data on 334 Wisconsin police departments.
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Scorecard at a Glance
Average for 4 Sections: 30%
Scores range from 0-100% comparing cities with 100-250k population. Cities with higher scores spend less on policing, use less force, are more likely to hold officers accountable and make fewer arrests for low-level offenses.
Worse
50th Percentile
Better
| Police Funding: 47% | ||||
|---|---|---|---|---|
| Police Budget Cost per Person | ||||
| Misconduct Settlements | ||||
| Fines/Forfeitures | ||||
| Police Presence/Over-Policing (Officers per Population) | ||||
| Police Violence: 30% | ||||
|---|---|---|---|---|
| Force Used per Arrest | ||||
| Deadly Force per Arrest | ||||
| Unarmed Victims of Deadly Force per Arrest | ||||
| Racial Disparities in Deadly Force | ||||
Worse
50th Percentile
Better
| Police Accountability: 10% | ||||
|---|---|---|---|---|
| Misconduct Complaints Upheld | ||||
| Excessive Force Complaints Upheld | ||||
| Discrimination Complaints Upheld | ||||
| Criminal Misconduct Complaints Upheld | ||||
| Approach to Law Enforcement: 32% | ||||
|---|---|---|---|---|
| Arrest Rate for Low Level Offenses | ||||
| Homicides Solved | ||||
| Racial Disparities in Drug Arrests | ||||
Key Findings
6 Killings by Police
22 civilian complaints of police misconduct
Only 1 in every 22 complaints were ruled in favor of civilians from 2016-19.
56,946 arrests made
72% of all arrests were for low-level, non-violent offenses from 2013-21.
Police Funding By Year
$27.89M | 104,649 Residents | $253 per Resident
More Police Funding per Capita than 27% of Depts
Source: US Census Bureau
Number of officers per 1k population
175 Officers | 16.7 per 10k Residents
More Officers per Population than 61% of Depts
Source: Federal LEOKA Database
Police Shootings
More Police Shootings per Arrest than 5% of Depts
2 Shootings | 0.5 every 100k arrests
Open in New Window
Less-Lethal Force
Used More Force per Arrest than 88% of Depts
1,107 Incidents | 194 every 10k arrests | ▶-49%
Source: Police Department
Open in New Window
Deadly Force
6 Killings by Police from 2013-21 | 1.1 every 10k arrests
^ More Killings by Police per Arrest than 49% of Depts
Source: Mapping Police Violence
Deadly Force by Armed Status
17% Unarmed | 50% Did Not Allegedly Have a Gun
Unarmed
Other
Alleged Gun
Vehicle
^ More Unarmed People Killed per Arrest than 61% of Depts
Open in New Window
Police Violence by Race
Black
Latinx
N.Am
API
Other
White
Population of Green Bay
Green Bay Police Dept Demographics
People Arrested
People Killed
^ More Racial Disparities in Deadly Force than 61% of Depts
Source: Uniform Crime Report, Mapping Police Violence, LEMAS
Total civilian complaints
22 from 2016-19 | 5% Ruled in Favor of Civilians
Complaints Not Sustained
Complaints Sustained
Use of Force Complaints
15 Reported | 0% Ruled in Favor of Civilians
Complaints of Police Discrimination
0 Complaints Reported
Alleged Crimes Committed by Police
N/A Reported | N/A Ruled in Favor of Civilians
No Data Found Add Data
Arrests By Year
56,946 Arrests Reported from 2013-2021
Low Level Arrests
Other Arrests
More Info
Arrests for Low Level Offenses
40,992 Arrests | 49 per 1k residents
^ Higher Arrest Rate for Low Level Offenses than 97% of Depts
Disparities in Arrests for Low Level Offenses by Race/Ethnicity
Black people were 12.2x more likely and Latinx people were 1.9x more likely to be arrested for low level, non-violent offenses than a white person.
Black
Latinx
White
Percent of total arrests by type
All Arrests for Low Level Offenses ( 72% )
Drug Possession ( 10% )
Violent Crime ( 5% )
Open in New Window
Homicides Unsolved
24 Homicides from 2013-21 | 2 Unsolved
^ Solved Fewer Homicides than 83% of Depts
Wisconsin Police Department Scores
Rankings are based upon a 0 to 100 percentage scale. Departments with higher scores use less force, make fewer arrests for low level offenses, solve murder cases more often, hold officers more accountable and spend less on policing overall.
Overall Scores for Depts where We Have Obtained the Most Data.
Tap "show more" to see extended list
| Police Department | Score | 5YR |
|---|---|---|
| 7. Green Bay 30% | ▶-12% | |
| 6. Waukesha 31% | ▶-6% | |
| 5. Eau Claire 37% | ▶+5% | |
| 4. Milwaukee 40% | ▶-9% | |
| 3. Appleton 47% | ▶+12% | |
| 2. Oshkosh 49% | ▶+3% | |
| 1. Madison 49% | ▶+11% | |
| * West Milwaukee 25% | ▶-6% | |
| ▶-11% | ||
| ▶-4% | ||
| ▶+3% | ||
| ▶+2% | ||
| ▶-1% | ||
| ▶+1% | ||
| ▶+1% | ||
| ▶+11% | ||
| ▶-6% | ||
| ▶-2% | ||
| ▶+7% | ||
| ▶-1% | ||
| ▶+5% | ||
| ▶+1% | ||
| ▶+3% | ||
| ▶+1% | ||
| ▶+9% | ||
| ▶+9% | ||
| ▶+1% | ||
| ▶-3% | ||
| ▶-2% | ||
| ▶-15% | ||
| ▶-2% | ||
| ▶-4% | ||
| ▶-1% | ||
| ▶-1% | ||
| ▶+1% | ||
| ▶-8% | ||
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| ▶-10% | ||
| ▶-8% | ||
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| ▶-7% | ||
| ▶-1% | ||
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| ▶-4% | ||
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| ▶+6% | ||
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| ▶-1% | ||
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| ▶+4% | ||
| ▶+1% | ||
| ▶-5% | ||
| ▶+4% | ||
| ▶-1% | ||
| ▶-4% | ||
| ▶-13% | ||
| ▶-2% | ||
| ▶-3% | ||
| ▶-4% | ||
| ▶+2% | ||
| ▶+2% | ||
| ▶-2% | ||
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| ▶+4% | ||
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| ▶+3% | ||
| ▶+3% | ||
| ▶-2% | ||
| ▶-8% | ||
| ▶-1% | ||
| ▶-1% | ||
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| ▶-3% | ||
| ▶+1% | ||
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| ▶+3% | ||
| ▶+1% | ||
| ▶+1% | ||
| ▶+8% | ||
| ▶-7% | ||
| ▶+4% | ||
| ▶+4% | ||
| ▶-5% | ||
| ▶-1% | ||
| ▶+3% | ||
| ▶-9% | ||
| ▶-2% | ||
| ▶-8% | ||
| ▶+2% | ||
| ▶+1% | ||
| ▶-2% | ||
| ▶-1% | ||
| ▶-2% | ||
| ▶+3% | ||
| ▶-8% | ||
| ▶-12% | ||
| ▶-1% | ||
| ▶+3% | ||
| ▶-1% | ||
| ▶+1% | ||
| ▶+1% | ||
| ▶+3% | ||
| ▶-5% | ||
| ▶-2% | ||
| ▶-2% | ||
| ▶-9% | ||
| ▶+2% | ||
| ▶+7% | ||
| ▶+1% | ||
| ▶+3% | ||
| ▶+3% | ||
| ▶+3% | ||
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| ▶-2% | ||
| ▶-1% | ||
| ▶-2% | ||
| ▶+8% | ||
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| ▶+4% | ||
| ▶+1% | ||
| ▶-6% | ||
| Police Department | Score | 5YR |
|---|---|---|
| * Beaver Dam 46% | ▶+2% | |
| * Germantown 46% | ▶-2% | |
| * Oconomowoc 46% | ▶-9% | |
| * Hartford 46% | ▶+3% | |
| * Kiel 46% | ▶-3% | |
| * Kewaskum 46% | ▶+3% | |
| * Shorewood 46% | ▶+5% | |
| * Adams 46% | ▶+1% | |
| ▶-9% | ||
| ▶+2% | ||
| ▶+1% | ||
| ▶+1% | ||
| ▶-1% | ||
| ▶+2% | ||
| ▶-2% | ||
| ▶+2% | ||
| ▶-2% | ||
| ▶+2% | ||
| ▶+2% | ||
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| ▶-2% | ||
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| ▶-1% | ||
| ▶-1% | ||
| ▶+2% | ||
| ▶-2% | ||
| ▶-4% | ||
| ▶+6% | ||
| ▶-6% | ||
| ▶+1% | ||
| ▶+3% | ||
| ▶+3% | ||
| ▶-4% | ||
| ▶-4% | ||
| ▶-2% | ||
| ▶-9% | ||
| ▶-9% | ||
| ▶-3% | ||
| ▶-3% | ||
| ▶-3% | ||
| ▶+2% | ||
| ▶+3% | ||
| ▶-3% | ||
| ▶+2% | ||
| ▶-2% | ||
| ▶+2% | ||
| ▶-2% | ||
| ▶-1% | ||
| ▶+3% | ||
| ▶-1% | ||
| ▶-3% | ||
| ▶-2% | ||
| ▶-11% | ||
| ▶-3% | ||
| ▶-4% | ||
| ▶-3% | ||
| ▶+2% | ||
| ▶-1% | ||
| ▶+4% | ||
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| ▶+4% | ||
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| ▶-1% | ||
| ▶-1% | ||
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| ▶-6% | ||
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| ▶+2% | ||
| ▶+2% | ||
| ▶-8% | ||
| ▶-8% | ||
| ▶-2% | ||
| ▶-3% | ||
| ▶+1% | ||
| ▶-2% | ||
| ▶-6% | ||
| ▶+5% | ||
| ▶+6% | ||
| ▶-3% | ||
| ▶-3% | ||
| ▶-8% | ||
| ▶-5% | ||
| ▶-4% | ||
| ▶-10% | ||
| ▶-8% | ||
| ▶-7% | ||
| ▶-3% | ||
| ▶+1% | ||
| ▶+6% | ||
| ▶-1% | ||
| ▶-6% | ||
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| ▶+4% | ||
| ▶+4% | ||
| ▶+2% | ||
| ▶-4% | ||
| ▶-2% | ||
| ▶-5% | ||
| ▶-2% | ||
| ▶-2% | ||
| ▶-1% | ||
| ▶-2% | ||
| ▶-8% | ||
| ▶-11% | ||
| ▶+1% | ||
| ▶-1% | ||
| ▶-3% | ||
| ▶-10% | ||
| ▶-1% | ||
| ▶-1% | ||
| ▶-1% | ||
| ▶-1% | ||
| ▶-2% | ||
| ▶-9% | ||
| ▶-5% | ||
| ▶-2% | ||
| ▶-2% | ||
| ▶-2% | ||
| ▶-3% | ||
| ▶-1% | ||
| ▶-2% | ||
| ▶-1% | ||
| ▶-11% | ||
| ▶+4% | ||
| ▶-7% | ||
| ▶-1% | ||
| ▶-1% | ||
| ▶-6% | ||
| ▶-4% | ||
| ▶-6% | ||
| ▶-9% | ||
| ▶-5% | ||
| ▶-13% | ||
* An asterisk indicates this location did not publish enough data to evaluate. Click below to add data to the Scorecard.
About This Scorecard
This is the first nationwide evaluation of policing in the United States. It was built using data from state and federal databases, public records requests to local police departments, and media reports. While police data is never perfect, and there are additional indicators that still need to be tracked, the Police Scorecard is designed to provide insight into many important issues in policing.
Police Scorecard is an independent 501(c)(3) organization, learn more about our team here. If you have feedback, questions about the project, or need support with an advocacy campaign, contact our Founder, Samuel Sinyangwe.
Use this Scorecard to identify issues within police departments that require the most urgent interventions and hold officials accountable for implementing solutions. For example, cities with higher rates of low level arrests could benefit most from solutions that create alternatives to policing and arrest for these offenses. In cities where police make fewer arrests overall but use more force when making arrests, communities could benefit significantly from policies designed to hold police accountable for excessive force. And cities where complaints of police misconduct are rarely ruled in favor of civilians could benefit from creating an oversight structure to independently investigate these complaints.
Here's how to start pushing for change
-
Contact your Mayor and Police Chief, share your scorecard with them and urge them to enact policies to address the issues you've identified:
Advocacy Tip: We've identified problematic language in this city's police union contract that could make it harder to hold officers accountable. Learn more about this contract and how to change it at Nixthe6.org.
-
Look up your state and federal representatives below, then tell them to take action to hold police accountable in your community.
Join a team of researchers, students, data scientists, activists and organizers working to collect, analyze and use data for justice and accountability.
Create data visualizations and content that raises awareness about solutions to the issues identified by the data.
What's Next
Step 1: COMPLETED
Obtain data on 100 California cities. Refine methodology in response to feedback from communities, researchers and local officials.
Step 2: COMPLETED
Expand to every major law enforcement agency in America and include additional indicators such as police budgets and jail incarceration.
Step 3: IN PROGRESS
Inform data-driven solutions nationwide. Update as new federal, state and local data are collected. Track progress and hold cities accountable to results.