Monthly Traffic Safety Analysis

22 CRASHES IN
SPENCER, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, SPENCER, MA experienced 22 crashes, a decrease of 4.3% compared to the 23 crashes in January 2025. A notable shift was observed in contributing factors, with 'No improper driving' increasing from 5 crashes in January 2025 to 13 crashes in January 2026, becoming the most frequent factor.

22

-4.3%was 23

Total Crash Events

0

Persons Killed

2

-50.0%was 4

Persons Injured

0

-100.0%was 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 · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in January 2026 showed a slight decrease, with total crashes falling by 1 (4.3%) from 23 to 22. Total injuries also saw a significant reduction, dropping by 50% from 4 injuries in January 2025 to 2 injuries in January 2026.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 4-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Tuesday, which had 5 crashes in January 2025, to Thursday, which recorded 6 crashes in January 2026. Similarly, the peak hour for crashes shifted from 6 p.m. with 4 crashes in the prior period to 3 p.m. with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both January 2025 and January 2026. However, total injuries decreased by 50%, from 4 injuries in the prior period to 2 injuries in the current period. The proportion of crashes resulting in minor injuries also decreased, from 17.4% in January 2025 to 9.1% in January 2026.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes9.1%
-50.0%prior 4
No Injury20no injury crashes90.9%
5.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Failed to yield right of way' (7 crashes, 30.4% share) in January 2025 to 'No improper driving' (13 crashes, 59.1% share) in January 2026. 'Failed to yield right of way' crashes decreased by 5, from 7 to 2, while crashes attributed to 'No improper driving' increased by 8. Additionally, 'Driving too fast for conditions' emerged as a factor in January 2026 with 2 crashes, having not been present in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving13 (59.1%)160.0%prior 5
Failed to yield right of way2 (9.1%)-71.4%prior 7
Driving too fast for conditions2 (9.1%)
Inattention1 (4.5%)
Other improper action1 (4.5%)
Wrong side or wrong way1 (4.5%)
Failure to keep in proper lane or running off road1 (4.5%)
Followed too closely1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions decreased from 17 in January 2025 to 10 in January 2026, while crashes during 'Snow/Snow' conditions increased from 2 to 6. Correspondingly, crashes on 'Dry' road surfaces decreased from 16 to 6, whereas crashes on 'Snow' surfaces increased from 3 to 9, and on 'Ice' surfaces from 1 to 3. Lighting conditions remained relatively stable, with 'Daylight' crashes at 13 in the prior period and 14 in the current period.

Weather

Clear/Clear10 (45.5%)
-41.2%prior 17
Snow/Snow6 (27.3%)
Snow/Blowing sand, snow2 (9.1%)
Snow/Sleet, hail (freezing rain or drizzle)2 (9.1%)
Rain/Cloudy1 (4.5%)
Snow/Cloudy1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight14 (63.6%)
7.7%prior 13
Dark - roadway not lighted4 (18.2%)
Dark - lighted roadway3 (13.6%)
Dusk1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Snow9 (40.9%)
Dry6 (27.3%)
-62.5%prior 16
Wet4 (18.2%)
Ice3 (13.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
TOYOTA5 (15.6%)
-28.6%prior 7
2
FORD4 (12.5%)
-20.0%prior 5
3
CHEVROLET4 (12.5%)
-55.6%prior 9
4
SUBARU3 (9.4%)
5
HYUNDAI2 (6.3%)
6
GMC2 (6.3%)
7
BMW2 (6.3%)
8
HONDA1 (3.1%)
-80.0%prior 5
9
CHRYSLER1 (3.1%)
10
JEEP1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

Sex Distribution (36 persons with recorded sex)

Male20 (55.6%)
-25.9%prior 27
Female16 (44.4%)
-15.8%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

The highest concentration of crashes continued to be in the 30 mph speed zone, though the count decreased from 12 crashes in January 2025 to 10 crashes in January 2026. Crashes in the 40 mph zone also saw a reduction from 8 to 5, while those in the 25 mph zone increased from 2 to 4. Notably, the current period introduced crashes in the 20 mph (1 crash) and 45 mph (1 crash) zones, which had no recorded crashes in the prior period, and no fatal crashes occurred in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: SPENCER, MA
  • Total crash records analyzed: 22
  • Total persons involved: 36
  • Total vehicles involved: 32

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). "SPENCER, MA Crash Intelligence Report: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/spencer/january-2026-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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Spencer, MA Crash Report — January 2026 | ThatCarHitMe.com