Examining Longitudinal Positional Changes In NFL Combine Performance Tests

Draft prospect identification continues to be a driving factor in the development of professional football organizations and includes various objective and subjective assessments. Understanding the progression of NFL combine results may be of interest due to the changing nature of the game, training, and athlete monitoring. PURPOSE:To examine positional changes in NFL combine results from 2000-2024. METHODS: A total of 8320 American Football players testing at the NFL Combine between 2000-2024 were included in the present analysis, consisting of 910 linebackers (LB), 923 cornerbacks and defensive backs (CB), 1320 defensive linemen (D-Line), 1373 offensive linemen (O-Line), 446 quarterbacks (QB), 849 running backs and fullbacks (RB), 588 safeties, 295 specialists (including kickers, punters, and long snappers), 464 tight ends (TE), and 1152 wide receivers (WR). Combine tests included in the present analysis were height, weight, 40-yard dash (40y), vertical jump (VJ), and bench press (BP). Relative BP volume was calculated by multiplying the number of reps by the load (102 kg) and dividing by body weight. Data was accessed from an open-source website and years were grouped into 5-year quintiles (Q1: 2000-2004, Q2: 2005-2009, etc.). Two-way ANOVAs were conducted to compare positional and year quintile effects on combine tests. Post-hoc analyses were run using Student’s t-test. RESULTS: Since Q1, height has increased in O-Line (vs. Q4), QB (Q3-4), specialists (Q4), and CB/DB (Q4-5), and decreased in RB/FB (Q3-5) (F (4, 36) = 5.4383, p < .001). Weight decreased in Q5 in D-Line (vs. Q1-4), TE (Q1-2), LB (Q1-4), QB (Q2-4), RB (Q1-4), specialists (Q2), safeties (Q2), and WR (Q4) (F (4, 36) = 22.1417, p < .001). In Q5, 40y times have been faster for O-Line, D-Line, QB, LB compared to all other quintiles, and faster in TE, RB, safeties, and WR compared to Q1 (F (4, 36) = 18.8957, p < .001). Across all positional groups, BP (F (3, 34) = 3.537, p < .05) and relative BP volume (F (3, 34) = 4.1208, p < .001) was greatest in Q2. Across all positions, VJ was greatest in Q5 (F (3, 35) = 5.6703, p < .001). CONCLUSIONS: To aid in team draft performance, understanding positional changes over time may aid in draft decisions that could affect operating budgets, personnel, and possibly season performance.

Authors

Institutions

Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2025-09-16
DOI
https://doi.org/10.1249/01.mss.0001157220.87990.22
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Examining Longitudinal Positional Changes In NFL Combine Performance Tests

Jack Marucci, Neil M. Johannsen, Rachel Matthews, Julio B. Morales
Medicine & Science in Sports & Exercise
Sports Analytics and Performance
article

Examining Longitudinal Positional Changes In NFL Combine Performance Tests

Jack Marucci, Neil M. Johannsen, Rachel Matthews, Julio B. Morales
article en

Abstract

Draft prospect identification continues to be a driving factor in the development of professional football organizations and includes various objective and subjective assessments. Understanding the progression of NFL combine results may be of interest due to the changing nature of the game, training, and athlete monitoring. PURPOSE:To examine positional changes in NFL combine results from 2000-2024. METHODS: A total of 8320 American Football players testing at the NFL Combine between 2000-2024 were included in the present analysis, consisting of 910 linebackers (LB), 923 cornerbacks and defensive backs (CB), 1320 defensive linemen (D-Line), 1373 offensive linemen (O-Line), 446 quarterbacks (QB), 849 running backs and fullbacks (RB), 588 safeties, 295 specialists (including kickers, punters, and long snappers), 464 tight ends (TE), and 1152 wide receivers (WR). Combine tests included in the present analysis were height, weight, 40-yard dash (40y), vertical jump (VJ), and bench press (BP). Relative BP volume was calculated by multiplying the number of reps by the load (102 kg) and dividing by body weight. Data was accessed from an open-source website and years were grouped into 5-year quintiles (Q1: 2000-2004, Q2: 2005-2009, etc.). Two-way ANOVAs were conducted to compare positional and year quintile effects on combine tests. Post-hoc analyses were run using Student’s t-test. RESULTS: Since Q1, height has increased in O-Line (vs. Q4), QB (Q3-4), specialists (Q4), and CB/DB (Q4-5), and decreased in RB/FB (Q3-5) (F (4, 36) = 5.4383, p < .001). Weight decreased in Q5 in D-Line (vs. Q1-4), TE (Q1-2), LB (Q1-4), QB (Q2-4), RB (Q1-4), specialists (Q2), safeties (Q2), and WR (Q4) (F (4, 36) = 22.1417, p < .001). In Q5, 40y times have been faster for O-Line, D-Line, QB, LB compared to all other quintiles, and faster in TE, RB, safeties, and WR compared to Q1 (F (4, 36) = 18.8957, p < .001). Across all positional groups, BP (F (3, 34) = 3.537, p < .05) and relative BP volume (F (3, 34) = 4.1208, p < .001) was greatest in Q2. Across all positions, VJ was greatest in Q5 (F (3, 35) = 5.6703, p < .001). CONCLUSIONS: To aid in team draft performance, understanding positional changes over time may aid in draft decisions that could affect operating budgets, personnel, and possibly season performance.

Medicine & Science in Sports & ExerciseVol. 57(10S)
Louisiana State University (US)
Openalex Percentile: Top 66%
Sports Analytics and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.