Monthly Traffic Safety Analysis

39 CRASHES IN
WALPOLE, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, Walpole experienced 39 total crashes, an 85.7% increase compared to the 21 crashes recorded in May 2022. The most notable year-over-year shift is the significant rise in total crashes, alongside the appearance of pedestrian and bicycle crashes in the current period, which were absent in the prior year.

39

85.7%was 21

Total Crash Events

0

Persons Killed

14

16.7%was 12

Persons Injured

2

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 · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Walpole shows an upward trend year-over-year. Total crashes increased by 18, from 21 in May 2022 to 39 in May 2023, representing an 85.7% rise. Total injuries also saw an increase, from 12 to 14, marking a 16.7% rise.

2

Hit-and-Run Crashes — May 2023

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 in both May 2022 and May 2023. However, due to the overall increase in total crashes, the hit-and-run rate decreased from 9.5% in May 2022 to 5.1% in May 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

2

Cyclists Injured

Prior: 0%

10

Motorists Injured

Prior: 12-16.7%

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 Tuesday with 7 crashes in May 2022 to Thursday with 8 crashes in May 2023. The peak hour remained consistent in the late afternoon, shifting slightly from 5 PM with 4 crashes in May 2022 to 4 PM with 5 crashes in May 2023. Crashes on Thursdays saw the largest increase, rising from 2 to 8 year-over-year.

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 fatal crashes in either May 2022 or May 2023, maintaining a 0% fatal crash rate for both periods. The number of minor injury crashes increased from 3 to 5, and possible injury crashes rose from 2 to 6 year-over-year. The proportion of crashes resulting in any injury (Minor or Possible) increased from 23.8% (5 of 21 crashes) in May 2022 to 28.2% (11 of 39 crashes) in May 2023.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes12.8%
66.7%prior 3
Possible Injury6possible injury crashes15.4%
200.0%prior 2
No Injury28no injury crashes71.8%
75.0%prior 16

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

Among contributing factors, 'Failed to yield right of way' crashes increased from 2 to 8, a 300% change in count. Crashes attributed to 'No improper driving' rose from 4 to 9, a 125% change in count. 'Followed too closely' crashes also increased significantly, from 1 to 4, a 300% change in count.

Officer-Reported Primary Contributing Cause

No improper driving9 (23.1%)
Failed to yield right of way8 (20.5%)
Inattention4 (10.3%)
Followed too closely4 (10.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (7.7%)
Over-correcting/over-steering2 (5.1%)
Disregarded traffic signs, signals, road markings1 (2.6%)
Failure to keep in proper lane or running off road1 (2.6%)
Exceeded authorized speed limit1 (2.6%)

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 in 'Clear' weather conditions increased from 17 in May 2022 to 30 in May 2023, mirroring the overall rise in crash counts. Similarly, crashes under 'Daylight' conditions increased from 18 to 34, and crashes on 'Dry' road surfaces increased from 20 to 34. These increases reflect the overall rise in crash volume rather than a proportional shift towards adverse conditions.

Weather

Clear30 (76.9%)
76.5%prior 17
Clear/Cloudy4 (10.3%)
Cloudy2 (5.1%)
Rain2 (5.1%)
Cloudy/Rain1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight34 (87.2%)
88.9%prior 18
Dark - lighted roadway3 (7.7%)
Dark - roadway not lighted2 (5.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry34 (87.2%)
70.0%prior 20
Wet5 (12.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (69 vehicles)

1
TOYOTA13 (18.8%)
62.5%prior 8
2
FORD11 (15.9%)
83.3%prior 6
3
NISSAN6 (8.7%)
4
KIA5 (7.2%)
5
CHEVROLET5 (7.2%)
6
MERCEDES-BENZ3 (4.3%)
7
CADI3 (4.3%)
8
LEXUS3 (4.3%)
9
JEEP2 (2.9%)
10
HONDA2 (2.9%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

1 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (87 persons with recorded sex)

Male54 (62.1%)
157.1%prior 21
Female33 (37.9%)
0.0%prior 33

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 30 mph speed zones saw a substantial increase, rising from 6 in May 2022 to 18 in May 2023. Crashes in 25 mph zones increased from 2 to 5, and in 35 mph zones from 2 to 5. Notably, there were 4 crashes in 65 mph zones in May 2022, but no crashes reported at that speed limit in May 2023, with the highest speed limit crash in May 2023 occurring at 55 mph.

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: WALPOLE, MA
  • Total crash records analyzed: 39
  • Total persons involved: 89
  • Total vehicles involved: 69

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). "WALPOLE, 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/walpole/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

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Walpole, MA Crash Report — May 2023 | ThatCarHitMe.com