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Baylor-Syracuse: Data Analysis of Each Team’s Big Advantage that May Decide the Game

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Offensive rebounding and turnovers will control so much

NCAA Basketball: Baylor at Wichita State Peter G. Aiken

Baylor’s best tournament win of the decade happened because they won a big matchup. In 2014, Baylor was the country’s 41st best 3-point shooting team. Creighton finished 232nd in 3-point attempts allowed. The Bears took advantage of their big strength and Creighton’s key weakness. Behind an 11-of-19 shooting day from deep, No. 6 seed Baylor knocked off No. 3 seed Creighton 85-55.

In 2017, Baylor was the nation’s No. 1 team heading into Morgantown. But the 2017 Bears had a giant weakness: turnovers. Baylor finished the season 308th in offensive turnover rate. That year’s West Virginia team finished first in defensive turnover rate. West Virginia took advantage of their big strength and Baylor’s key weakness. By forcing 29 turnovers—or one on 37.2% of Baylor’s possessions—the Mountaineers gave No. 1 Baylor their first and largest loss of the season, 89-68.

Baylor-Syracuse presents two giant matchup gaps, and each side has the edge in one area.

Baylor dominates in offensive rebounding, while Syracuse is terrible at defensive rebounding. The Bears are the country’s second best offensive rebounding team, securing an offensive rebound on 38.2% of their possessions. Syracuse is one of the country’s worst defensive rebounding teams, as they rank 335th in defensive rebounding.

Syracuse dominates at turning teams over, while Baylor is terrible at not turning it over. The Orange are 10th in defensive turnover rate. They force an opponent turnover on 23.2% of defensive possessions. The Bears are one of the country’s worst at not turning it over—coming in at 264th in offensive turnover rate.

This seems simple. Baylor’s going to dominate the offensive glass because Syracuse is terrible at defensive rebounding, and Baylor is great at offensive rebounding. Syracuse is going to force a million turnovers because they’re great at forcing them, and Baylor is bad at not turning it over.

Things may not be so simple though. It may turn out that dominance isn’t linear. Let’s look at flying. If someone is nervous about flying, the act of getting on a plane may be what causes them a problem. They might just always be nervous. It may not matter if the pilot is the best, or if the pilot is the worst. Their fear might just always exist. If that framework is correct, maybe Syracuse is good at turning nearly everyone over, and they don’t excel against just the worst teams. Maybe Baylor is great at offensive rebounding against everyone, and they don’t boost their numbers by dominating against bad defensive rebounding teams.

To test that proposition, I gathered data from every Baylor and Syracuse game. We’ll start with turnovers, then look at offensive rebounding. Each time we’ll start with Syracuse.

To look at whether Syracuse turns over their opponents more when the opponent is bad, I gathered Syracuse’s defensive turnover percentage in each game. I then plotted that against that opponent’s offensive turnover percentage for the season. For example, Eastern Washington turned it over 27.9% of the time against Syracuse, and Eastern Washington is 76th in that category. That makes that bullet point in the third square from the right and second from the bottom in the graph below.

@kendallkaut

The above Syracuse graph shows that Syracuse was more dominant as their opponents got worse. There aren’t too many teams with lower percentages on the x-axis (low opponent offensive turnover percentage in that game) that have high scores on the y-axis (high opponent offensive turnover performance on the season). A higher turnover percentage score is bad for the offense—if you rank 350th in offensive turnover percentage, it’s worse than ranking 1st. Again, that seems to make intuitive sense—but given the airline example, and as we’ll see below, that’s not always how it works.

@kendallkaut

For Baylor’s turnover percentage, I plotted Baylor’s turnover percentage in each game (x-axis) against what their opponent’s defensive turnover ranking was for the full season (y-axis). For example, Baylor turned it over 28.9% of the time in their second game against Texas Tech, and the Red Raiders rank 11th in defensive turnover percentage (a low ranking for the defense is good in that category; a high ranking is bad). That point is plotted as the lowest one in the second square from the right and the lowest square on the board.

As the line of best fit shows, Baylor struggles more with turnovers as their opponent quality increases. But the slope isn’t quite as steep for Baylor as it was for Syracuse. Baylor has plenty of times where they were terrible at turning it over against bad teams, and Baylor had a few strong nights against good defensive turnover teams too. That means Baylor isn’t doomed to just throw up on themselves against Syracuse.

@kendallkaut

The above graph plots Syracuse’s defensive rebounding percentage (x-axis) against their opponent’s offensive rebounding rate (y-axis). A lower offensive rebounding score means the opponent is a better offensive rebounding team.

As the line of best fit shows, Syracuse was much worse at defensive rebounding when their opponents were better at offensive rebounding. They had a terrible offensive rebounding day against North Carolina, which is that point on the lowest far right box. The Tar Heels rank 21st in offensive rebounding, and they grabbed an offensive rebound on 51.4% of their shots.

@kendallkaut

Baylor is radically different when it comes to offensive rebounding. We finally have our fear of flying example. Baylor was a good offensive rebounding team, but they didn’t become the nation’s second best offensive rebounding team by crushing the nation’s worst defensive rebounding squads. Baylor grabbed 57.6% of their missed shots against Arizona, and the Wildcats rank 74th in defensive rebounding rate. And as the graph shows, the Bears grabbed well below their average against some of the sub 300 defensive rebounding teams they played.

Looking at that data, it become especially complicated. We know Syracuse has been much worse against good offensive rebounding teams, but we know Baylor hasn’t necessarily been much better at offensive rebounding as their opponents get worse at defensive rebounding.

Let’s make this even more complicated though. Someone might wonder: Isn’t Baylor a lot different without Tristan Clark? The Bears lost their best player to injury after the Iowa State game, which was the the 14th game of the season. If we look at just the 19 games that Baylor played without Clark, we get this data:

@kendallkaut

This graph shows that Baylor was a better offensive rebounding against their worst defensive rebounding opponents (there is not a corresponding change for Baylor in turnovers; the data is almost eerily similar with and without him). There are a couple outlier performances—for example, the Bears grabbed 46.9% of their offensive rebound opportunities against Kansas State, ranked 63rd in defensive rebounding. But as the line of best fit shows, Baylor was much better at offensive rebounding as the opponent got worse at defensive rebounding.

What’s it mean, nerd?

Data is hard to parse for a lot of reasons.

Do we trust Baylor’s full season data, which shows they weren’t that much better at offensive rebounding when their opponent was terrible at defensive rebounding? We have a larger sample for that. But we still have 19 games without Clark, and in those games, Baylor was much better at offensive rebounding as the opponent was terrible at defensive rebounding.

If we accept that conclusion—the Clarkless-Bears are better at offensive rebounding as the opponent gets worse at defensive rebounding—then we also have to ask: Is that because of a concentrated effort or other shift? Maybe Baylor offensive rebounds better in those games because the Bears especially focus on attacking the glass when they know their opponent is bad. That may not mean there is anything unique about opponent quality; it might mean there’s something unique to Baylor making that a key focus.

Syracuse might suffer the same fate in defensive rebounding. The Orange may truly be even worse at defensive rebounding against the best offensive rebounding teams, but maybe the best offensive rebounding teams come in and make that a priority. The worst offensive rebounding teams might notice the Orange are terrible at defensive rebounding, but they might not be able to become something they’re not. If I notice someone I’d like to date wants to date really attractive people, I’m not going to be able to undo all the Raising Cane’s I’ve been eating instantly. Similarly, a bad offensive rebounding team can’t just make themselves great in a week and attack a weakness.

The data does provide some value though. We know that Baylor is a great offensive rebounding team. We know that without Clark, they’ve been their best at offensive rebounding when they play the worst defensive rebounding teams. And we know Syracuse is a bad defensive rebounding team. We also know Syracuse has done the worst at defensive rebounding when playing the best offensive rebounding teams.

The situation is similar when it comes to turnovers. Syracuse is elite at turning over the worst offenses at not turning it over, and Baylor has a problem turning it over as defenses get better at turning over their opponent.

From the data, the takeaway is that we have two huge areas where each team appears to have a massive advantage. When Baylor misses a shot, they’re likely to grab a ton of offensive rebounds. And Syracuse is likely to turn Baylor over enough that the Bears won’t fire as many first shots as they’d like.

It figures that which team can overwhelm in their advantage area will have a giant boost in this game. Looking at the data tells us quite a bit, but tomorrow we’ll combine the data with the film to figure out who might have the edge in the game.