ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEICESTER, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/leicester/2022-annual-report
Yearly Traffic Safety Analysis
235 CRASHES IN
LEICESTER, MA
2022
In Leicester, total traffic crashes increased by 15.2% from 204 incidents in 2021 to 235 in 2022. During this period, total injuries rose from 71 to 74, while fatalities remained constant at one. A notable year-over-year shift was a 62.5% decrease in the number of crashes involving suspected drunk driving, which fell from 8 incidents to 3.
235
▲ 15.2%was 204
Total Crash Events
1
Persons Killed
74
▲ 4.2%was 71
Persons Injured
7
▲ 75.0%was 4
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Leicester moved upward from 2021 to 2022. The total number of crashes increased by 15.2%, rising from 204 to 235. The number of people injured in these incidents also saw a slight increase of 4.2%, from 71 to 74, while the number of fatalities held steady at one for both years.
7
Hit-and-Run Crashes — 2022
▲ 75.0% vs prior (4)
Hit-and-run crashes trended upward between 2021 and 2022. The number of such incidents increased from 4 to 7. Consequently, the hit-and-run rate, as a percentage of total crashes, rose from 2.0% in 2021 to 3.0% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
1
Pedestrians Injured
73
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The time patterns of crashes shifted between the two periods. In 2022, the peak day for crashes was Tuesday with 39 incidents, a change from 2021 when Thursday was the peak day with 37 crashes. The busiest hour also shifted later in the day, from 2 p.m. in 2021 (20 crashes) to 3 p.m. in 2022, which saw a higher concentration of 32 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained stable at one in both 2021 and 2022, though the fatal crash rate saw a minor decrease from 0.49% to 0.43%. The proportion of crashes resulting in any type of injury declined from 26.1% in 2021 to 22.1% in 2022. This was largely driven by a reduction in the share of minor injury crashes, which fell from 16.2% of all crashes in 2021 to 12.3% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'Inattention' remained a leading contributing factor in both years, its count decreased slightly from 56 to 54 crashes. Conversely, incidents with 'No improper driving' cited as the primary factor increased by 30.6%, from 36 crashes in 2021 to 47 in 2022. Crashes attributed to 'Failed to yield right of way' also grew in count from 14 to 19, while those linked to 'Distracted' driving saw a significant drop from 10 incidents to just 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather and on dry roads was slightly lower in 2022 compared to 2021. In 2022, 71.1% of crashes happened in clear weather, down from 74.0% the prior year. Crashes on adverse road surfaces increased, with incidents on icy roads more than doubling from 5 to 12, and crashes in snowy weather rising from 4 to 9.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were consistent year-over-year, led by Ford, Toyota, and Chevrolet. Analysis of persons involved in crashes shows a shift in age demographics; the count of individuals in the 16-20 age group decreased from 74 to 56. In contrast, involvement increased for the 45-54 age group (from 35 to 53 people) and the 65+ age group (from 52 to 75 people).
Top Vehicle Makes (386 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
29 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (479 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones were most common in both periods, increasing from 70 incidents in 2021 to 95 in 2022. The single fatal crash of 2022 occurred in a 45 mph zone. This contrasts with 2021, when the year's lone fatal crash took place in a 25 mph zone.
Fatal crashes by zone: 45 mph: 1 of 13 (7.692%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: LEICESTER, MA
- Total crash records analyzed: 235
- Total persons involved: 508
- Total vehicles involved: 386
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "LEICESTER, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leicester/2022-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved