ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NATICK, MA · MAY 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/natick/may-2023-report
Monthly Traffic Safety Analysis
69 CRASHES IN
NATICK, MA
MAY 2023
In May 2023, Natick experienced 69 total crashes, a 4.55% increase from the 66 crashes reported in May 2022. The most notable shift was a significant decrease in total injuries, which fell from 16 in May 2022 to 6 in May 2023, representing a 62.5% reduction.
69
▲ 4.5%was 66
Total Crash Events
0
Persons Killed
6
▼ -62.5%was 16
Persons Injured
5
▼ -28.6%was 7
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a slight increase in total crashes year-over-year, rising from 66 to 69 crashes, an increase of 4.55%. Conversely, total injuries saw a substantial decrease, dropping from 16 to 6, indicating a positive trend in reducing crash severity.
5
Hit-and-Run Crashes — May 2023
▼ -28.6% vs prior (7)
Hit-and-run crashes decreased from 7 in May 2022 to 5 in May 2023. This corresponds to a decrease in the hit-and-run rate from 10.6% to 7.2% year-over-year, indicating a downward trend in these types of incidents.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday with 12 crashes in May 2022 to Thursday with 13 crashes in May 2023. The peak hour remained 5 p.m. in both periods, though the count decreased slightly from 11 crashes to 10 crashes. Crashes on Saturdays increased from 4 to 9, while crashes on Sundays decreased from 11 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either May 2022 or May 2023. Total injuries decreased significantly from 16 to 6, a 62.5% reduction. The proportion of crashes resulting in minor injuries decreased from 10.6% to 5.8%, and possible injuries decreased from 9.1% to 2.9%, indicating a shift towards less severe outcomes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Inattention,' remained constant at 21 crashes in both periods, though its share decreased from 31.8% to 30.4%. 'Followed too closely' saw a significant increase in count from 3 to 8 crashes, and 'Failed to yield right of way' increased from 3 to 7 crashes. Conversely, 'No improper driving' decreased from 16 crashes to 11 crashes year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet road surfaces increased from 2 in May 2022 to 7 in May 2023. Similarly, crashes during rainy conditions increased from 2 to 4, and 'Cloudy/Rain' conditions, which were not present in the prior period, accounted for 2 crashes in the current period. Despite these increases, the majority of crashes continued to occur in clear weather and daylight conditions, increasing slightly from 56 to 58 for clear weather and 58 to 60 for daylight.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
Toyota, Honda, and Ford remained the most frequently involved vehicle makes, with Toyota involvement increasing from 22 to 30 and Ford from 12 to 19. The 16-20, 35-44, and 45-54 age groups saw an increase in the number of persons involved in crashes. Conversely, the 0-15, 21-25, and 55-64 age groups experienced a decrease in persons involved.
Top Vehicle Makes (134 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (151 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 35 mph zones increased from 13 to 18, and in 50 mph zones from 8 to 11. Conversely, crashes in 30 mph zones slightly decreased from 24 to 23, and in 40 mph zones from 5 to 3. Fatal crash rates remained at 0 across all speed zones for both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: NATICK, MA
- Total crash records analyzed: 69
- Total persons involved: 158
- Total vehicles involved: 134
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). "NATICK, MA Crash Intelligence Report: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/natick/may-2023-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: 2023-05-01 – 2023-05-31
Generated: June 21, 2026 · All rights reserved