ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHESTER, MA · 2023
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/chester/2023-annual-report
Yearly Traffic Safety Analysis
13 CRASHES IN
CHESTER, MA
2023
In 2023, Chester recorded 13 total traffic crashes, a decrease from the 16 crashes reported in 2022, representing an 18.8% year-over-year reduction. While total injuries saw a slight increase from 5 to 6, there were no fatalities in either period. One of the most significant changes was the reduction in crashes involving a driver suspected of being under the influence, which fell from 3 in 2022 to 1 in 2023.
13
▼ -18.8%was 16
Total Crash Events
0
Persons Killed
6
▲ 20.0%was 5
Persons Injured
1
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic collisions in Chester saw a downward trend, with total crashes decreasing by 18.8% from 16 in 2022 to 13 in 2023. Despite the drop in overall incidents, the number of reported injuries slightly increased from 5 to 6. Fatalities remained at zero for both years.
1
Hit-and-Run Crashes — 2023
▼ 0.0% vs prior (1)
The number of hit-and-run incidents remained stable, with one such crash recorded in both 2023 and 2022. Due to the overall decrease in total crashes in 2023, the hit-and-run rate saw a slight increase, rising from 6.3% of all crashes in 2022 to 7.7% in 2023. This indicates that while the absolute count did not change, hit-and-runs constituted a slightly larger proportion of total collisions in the more recent period.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two years. In 2023, the peak day for crashes was Sunday with 4 incidents, a change from 2022 when Thursday was the peak day with 6 crashes. The most common time for crashes also changed, moving from the 10 p.m. hour in 2022 to the 11 p.m. hour in 2023, where 2 of the year's 13 crashes occurred.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes recorded in either 2022 or 2023. However, the proportion of crashes resulting in an injury increased year-over-year. In 2023, 46.2% of crashes involved an injury (6 out of 13), up from 31.3% in 2022 (5 out of 16). Specifically, crashes classified with 'Minor Injury' accounted for 30.8% of incidents in 2023, compared to 25.0% in the prior year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in both periods was 'No improper driving,' which was cited in 6 crashes in 2023, up from 5 in 2022. Crashes attributed to 'Exceeded authorized speed limit' also saw an increase, rising from 2 incidents in 2022 to 3 in 2023. Notably, 'Physical impairment,' which was a factor in 2 crashes in 2022, was not cited for any crashes in 2023. Several factors, including 'Emotional' and 'Followed too closely,' each appeared once in 2023 but were not listed as factors in the prior year's data.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both 2022 and 2023, the majority of crashes occurred in clear weather and on dry road surfaces, with over 61% of crashes in both years happening on dry roads. There was a notable shift in lighting conditions, as the proportion of crashes in 'Dark - roadway not lighted' areas increased from 37.5% in 2022 to 46.2% in 2023, matching the number of daylight crashes. Incidents on icy roads increased from one to two, while crashes on wet roads decreased from four to one.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (16 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
1 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (17 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones shifted between the two years. In 2022, crashes were most frequent in 35 mph (6 crashes) and 30 mph (5 crashes) zones. While the 35 mph zone remained the most common location in 2023 with 4 crashes, there was a notable emergence of crashes in the 50 mph zone, which accounted for 3 incidents in 2023 after having none in 2022. Conversely, crashes in 30 mph zones decreased from 5 in 2022 to 2 in 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: CHESTER, MA
- Total crash records analyzed: 13
- Total persons involved: 19
- Total vehicles involved: 16
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). "CHESTER, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chester/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved