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Bill Radjewski

@collegefootballdata.com

3.3K followers 120 following 390 posts

CFB and CBB graphs and analytics | CollegeFootballData.com | CollegeBasketballData.com | It's pronounced "ruh-jess-key"

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Bill Radjewski @collegefootballdata.com · Jul 12

📦 The CFBD Starter Pack is officially live!

Whether you're building models, dashboards, or just exploring data, this is your launchpad.

What’s inside + how to get it 👇
#cfb #cfbd #sportsanalytics

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Bill Radjewski @collegefootballdata.com · 15h

I haven't had much time to jazz this up, but this is what I have for now. I'd like to go back and break it down by DC rather than HC.

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Bill Radjewski @collegefootballdata.com · 19h

Congrats to all weekly leaders!

Full leaderboard: buff.ly/AXms8Iv

Bill Radjewski @collegefootballdata.com · 19h

Top 5 Models - MSE

1. @ram_dub (-11.900)
2. @mmender2 (-10.050)
3. @DomerIHardlyKno (-7.360)
4. @ArnoldJohn_cfb (-6.960)
5. u/forescore_regular_v2 (-5.810)

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Bill Radjewski @collegefootballdata.com · 19h

Top 5 Models - MAE

1. @ram_dub (-0.240)
2. @Stephen_Hill (-0.120)
3. @johnbedwards.io (-0.020)
4. u/hypercube42342 (+0.110)
5. @jhnhrris (+0.120)

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Bill Radjewski @collegefootballdata.com · 19h

Top 5 Models - Picks ATS

1. u/Traditional_Trifle95 (+0.098)
2. u/forescore_regular_v2 (+0.093)
3. @ram_dub (+0.082)
4. @DomerIHardlyKno (+0.073)
5. @ArnoldJohn_cfb (+0.071)
5. @RyderAnalytics (+0.071)

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Bill Radjewski @collegefootballdata.com · 19h

Top 5 Models - Straight Up Picks

1. @DomerIHardlyKno (+0.042)
2. @sseljan (+0.039)
2. @mmender2 (+0.039)
4. u/Danger-007-Mouse (+0.037)
5. @spacemanOTH (+0.036)
5. @RyderAnalytics (+0.036)

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Bill Radjewski @collegefootballdata.com · 19h

Computer Model Pick'em Week 7 Update

Congrats to @ram_dub AND @DomerIHardlyKno for taking the top overall spot this week!

Here are the Top 5 Models by Composite Ranking:

1. @ram_dub
1. @DomerIHardlyKno
3. @Stephen_Hill
4. @ArnoldJohn_cfb
5. @jhnhrris
5. u/forescore_regular_v2

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Bill Radjewski @collegefootballdata.com · 21h

🔥 QB Efficiency Leaders (through Week 7) 🔥

Here are the Top 15 QBs in opponent-adjusted EPA per dropback.

USC’s Jayden Maiava still owns the top spot. Ohio State’s Julian Sayin is moving on up. B1G QBs comprise 3 of the top 4 spots. 👀

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Bill Radjewski @collegefootballdata.com · 21h

Indiana football, from forgotten to feared.

Curt Cignetti’s squad has reached its highest Elo rating ever after this past weekend's emphatic victory over Oregon.

The Hoosiers are officially elite.

Bill Radjewski @collegefootballdata.com · 1d

Yeah I was actually working on that as well. Wanted to initially share the scatter plot to illustrate the historical context of this one data point (plus the median performance of the offense).

Bill Radjewski @collegefootballdata.com · 1d

Oh, it's on the list. #5.

Bill Radjewski @collegefootballdata.com · 1d

The 61% success rate given up by Wink Martindale's defense against USC is the worst I have on record for all Michigan games dating back to 2003.

Next worst games:

- 58.9% against Wisconsin in 2020
- 57.1% against NIU in 2005

Seems bad!

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Bill Radjewski @collegefootballdata.com · 1d

Now the defenses 🔒

📊 Opp-adjusted success rate allowed (through Week 6)

Oklahoma still looks like a brick wall 🧱
Auburn, Texas Tech, and Indiana in the next tier

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Bill Radjewski @collegefootballdata.com · 1d

Offensive efficiency through Week 7

X = Opp-adjusted success rate on standard downs
Y = Opp-adjusted success rate on passing downs

🚀 USC remains untouchable at the top
💪 Vandy, Arky, and Utah still holding strong
⚡ FSU, AFA, and IU right up there

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Bill Radjewski @collegefootballdata.com · 1d

I had USC with a 66% (!) offensive success rate on standard downs and a 60% overall success rate. These are the type of numbers you'd expect to see against a MAC or FCS defense.

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Bill Radjewski @collegefootballdata.com · 5d

Whoops! Thanks for letting me know! Hope you enjoy.

Bill Radjewski @collegefootballdata.com · 5d

Ever wondered how a player’s shot mix actually breaks down? 🏀

Here’s a quick look from one of the new Jupyter notebooks in the College Basketball Data Starter Pack: stacked shot shares by type (dunks, layups, jumpers, 3s).

Available now on Gumroad: buff.ly/aJuInMK

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Bill Radjewski @collegefootballdata.com · 5d

More info on what's included:

Data Files guide - buff.ly/584TBwU
Data Headers - buff.ly/onRE3Ts
Notebooks guide - buff.ly/8QShiEA

Bill Radjewski @collegefootballdata.com · 5d

If you previously picked up any of the CFB packs, check your email 👀 — a special discount was just sent out as a thank-you.

Everyone else can grab the new pack here:
🔗https://buff.ly/aJuInMK

Available now at the promotional launch price of $39.

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Bill Radjewski @collegefootballdata.com · 5d

Includes:
📊 Team & player stats (2005–2025)
📈 Advanced tempo-free & Four Factors metrics
🎯 Detailed shot breakdowns (layups, dunks, jumpers, 3s)
💻 14 beginner-friendly notebooks for rankings, dashboards, and opponent adjustments

Perfect for analysts, modelers, and students.

Bill Radjewski @collegefootballdata.com · 5d

🏀 The College Basketball Data Starter Pack is here!

A complete, ready-to-use dataset + 14 Jupyter notebooks to help you explore, visualize, and build your own analytics projects for CBB.

Built in the same spirit as the popular CFB Starter Pack — but made for the hardwood.

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Bill Radjewski @collegefootballdata.com · 6d

💡 Launches soon with an early discount for CFB pack owners.

See what's included:

Data Files guide - buff.ly/584TBwU
Data Headers - buff.ly/onRE3Ts
Notebooks guide - buff.ly/8QShiEA

Bill Radjewski @collegefootballdata.com · 6d

✅ Team & player stats (2005–2025)
✅ Advanced tempo-free & Four Factors metrics
✅ Shooting breakdowns (layups, dunks, jumpers, 3s)
✅ 14 beginner-friendly notebooks for rankings, dashboards, & opponent adjustments

If you grabbed the CFB Starter Pack, you’ll feel right at home.

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Bill Radjewski @collegefootballdata.com · 6d

It’s almost hoops season and that means the College Basketball Data Starter Pack is coming soon. 🏀

A complete, ready-to-use dataset + 14 Jupyter notebooks designed to help you explore, visualize, and build your own analytics models for college basketball.

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Bill Radjewski @collegefootballdata.com · 6d

Now flip it to the other side of the ball.

Which defenses are forcing long 3rd downs, and which are actually getting stops?

Here’s the same view for defenses: average 3rd down distance to go allowed vs. 3rd down conversion rates allowed.

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