Usage Score
9.2
Player Dossier
2017-2019TCU
Ross Blacklock
DT • 6'4" • 305 lbs • Missouri City, TX, USA
Ball-hunting defenderSplash play profile
Ross Blacklock shows a ball-hunting defender profile with 24.3 disruption score.
Efficiency
24.3
Consistency
29.9
Season Value
23.5
Career Arc
Value trend by season
Best season by value score: 2019 Regular Season · TCU
17171819
Snapshot
- Career Teams
- 1
- Seasons Tracked
- 4
- Program Path
- TCU
- Peak Game
- Peak game by takeover score: Kansas
Scouting Read
Best season and peak-game context are pinned here so the rest of the page can stay analytical without losing the headline story.
Ross Blacklock, DT. Best season Best season by value score: 2019 Regular Season · TCU. Ross Blacklock shows a ball-hunting defender profile with 24.3 disruption score.
Player insights
Lead takeaway
Best season by value score: 2019 Regular Season
TCU paired 12.5 primary output with 24.3 efficiency.
Supporting note
2019 Regular Season role shape
impact-led usage with 24.3 efficiency.
Supporting note
Career value is trending up
2019 Regular Season improved on the prior stop by season value score.
Supporting note
Peak game by takeover score: Kansas
Win with 3 impact plays across the defensive snap sheet. It landed in the 100th percentile of the selected season.
Analysis workspace
Season Workbench
Filter the strongest season sample, inspect game-level shape, and then drop into the full log without losing the story of the year.
Season Explorer
Understand the selected season before dropping into the full game log.
2019 Regular Season · TCU
Games
12
Havoc Plays / G
1.0
Efficiency
24.3
Usage
9.2
Consistency
29.9
Best Game by takeover score
West Virginia
Hover a point or expand a game row to keep the active game context visible here.
Active game
Hover over a point
Hover or select a game to keep its context visible here without the page shifting around.
Game-by-Game Trend
Follow how the selected stat changes from one game to the next. Spikes mark standout outings, while dips show quieter weeks.
Chronological game order.
Game by game trend chart. Unknown: 2. Purdue: 2. SMU: 0. Kansas: 3. Iowa State: 0. Kansas State: 3. Texas: 0.5. Oklahoma State: 0.5. Baylor: 1.5. Texas Tech: 0. Oklahoma: 0. West Virginia: 0
Volume vs Efficiency
Each dot is a game. Farther right means the player carried more of the workload, and higher means they were more efficient with those chances.
Low volumeHigh quality
High volumeHigh quality
Low volumeLower quality
High volumeLower quality
Volume on the x-axis, quality on the y-axis.
Volume versus efficiency scatter chart. Unknown: 1 by 24.2. Purdue: 2 by 28.3. SMU: 5 by 20.8. Kansas: 5 by 50.8. Iowa State: 2 by 8.3. Kansas State: 4 by 46.7. Texas: 3 by 17.5. Oklahoma State: 7 by 34.2. Baylor: 4 by 31.7. Texas Tech: 2 by 8.3. Oklahoma: 3 by 12.5. West Virginia: 2 by 8.3
Split Comparison
Compare how this player performed across different situations. "Games" shows how many matchups are included in each split.
Wins1.4 · Games = 4 · +0.7 vs Losses
Losses0.7 · Games = 7 · -0.7 vs Wins
First Half1.7 · Games = 6 · +1.3 vs Second Half
Second Half0.4 · Games = 6 · -1.3 vs First Half
Game Log
Dense stat lines with inline explanations and season-linked highlights.
12 games
Featured metric
Havoc Plays
Top game by takeover score
Kansas
Best efficiency game
50.8 vs Kansas
| Result | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Fri 11/29 | vs West Virginia | L 17-20 | 2 | 1 | — | 0 | 0 | — | 0 | — | — |
| Sun 11/24 | @ Oklahoma | L 24-28 | 3 | 0 | — | 0 | 0 | — | 0 | — | — |
| Sat 11/16 | @ Texas Tech | W 33-31 | 2 | 2 | — | 0 | 0 | — | 0 | — | — |
| Sat 11/9 | vs Baylor | L 23-29 | 4 | 3 | — | 1.50 | 0 | — | 0 | — | — |
| Sat 11/2 | @ Oklahoma State | L 27-34 | 7 | 4 | — | 0.50 | 0 | — | 0 | — | — |
| Sat 10/26 | vs Texas | W 37-27 | 3 | 1 | — | 0.50 | 0 | — | 0 | — | — |
| Sat 10/19 | @ Kansas StateSplash game | L 17-24 | 4 | 3 | — | 2 | 1 | — | 0 | — | — |
| Sat 10/5 | @ Iowa State | L 24-49 | 2 | 1 | — | 0 | 0 | — | 0 | — | — |
| Sat 9/28 | vs KansasSplash game | W 51-14 | 5 | 2 | — | 2.50 | 0.50 | — | 0 | — | — |
| Sat 9/21 | vs SMU | L 38-41 | 5 | 5 | — | 0 | 0 | — | 0 | — | — |
| Sat 9/14 | @ Purdue | W 34-13 | 2 | 2 | — | 1 | 1 | — | 0 | — | — |
| Sun 9/1 | vs Unknown | — | 1 | 1 | — | 1 | 1 | — | 0 | — | — |
Career Arc
Track team changes, role shifts, and season-to-season movement.
- 1
TCU
2017-2019
Opening stop
Season Progression
2017201720182019
| Season | Team | Primary | Efficiency | Usage | Delta |
|---|---|---|---|---|---|
| 2017 Postseason | TCU | 8.5 | 17.2 | 5.3 | — |
| 2017 Regular Season | TCU | 8.5 | 17.2 | 5.3 | 0 |
| 2018 Regular Season | TCU | 0 | — | — | -8.5 |
| 2019 Regular Season | TCU | 12.5 | 24.3 | 9.2 | 12.5 |
Signature Performances
Top Games
#1 Featured game
Kansas
Win with 3 impact plays across the defensive snap sheet.
3
Primary metric
3 disruption/tackle impact with 58 takeover score.
#2
Kansas State
3
Primary metric
Loss with 3 impact plays across the defensive snap sheet.
3 disruption/tackle impact with 56.6 takeover score.
#3
Kansas
2.5
Primary metric
Win with 2.5 impact plays across the defensive snap sheet.
2.5 disruption/tackle impact with 53 takeover score.
#4
Stanford
2
Primary metric
Win with 2 impact plays across the defensive snap sheet.
2 disruption/tackle impact with 46.2 takeover score.
#5
Texas
2
Primary metric
Win with 2 impact plays across the defensive snap sheet.
2 disruption/tackle impact with 36.8 takeover score.
Top Seasons
#1 Season by value score
2019 Regular Season · TCU
12.5 primary output · 24.3 efficiency · 9.2 usage
23.5
#2
2017 Postseason · TCU
14.6
8.5 primary · 17.2 efficiency · 5.3 usage
#3
2017 Regular Season · TCU
14.6
8.5 primary · 17.2 efficiency · 5.3 usage
Milestones
0
Impact games
3
Splash games
0
10+ tackle games
Bio, Recruit, and Data Context
Recruit Profile
4★
Class 2016 · Rating 0.9094
Elkins · Missouri City, TX
- Committed To
- TCU
- Commit Date
- Jan 1, 2016
Career Facts
1
Career teams
4
Seasons tracked
65
Career Tackles
Data Context
Coverage spans 4 tracked seasons, 23 games, and base opponent context only. Derived metrics fall back to raw production when share or rating context is missing.