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10 Thoughts On College Basketball's Opening Weekend

1. Some of our preseason predictions will be right.

Luke Winn and I identified George Mason’s Patrick Holloway as one of this year’s breakout scorers. In fact, we had him as the 46th highest scorer in the country. Through two games he is averaging 20.5 PPG.

One of the predictions that I was the most nervous about was on our Top 50 freshmen scorers’ list. Our model had Montaque Gill-Caeser as the #19 freshman scorer because Missouri needed a shot-taker. But since Gill-Caeser re-classified (meaning he was not originally going to play college basketball this year), I was very nervous whether he was ready to play a big role immediately. Through two games, the prediction is looking good. Gill-Caeser took a team-leading 23 shots and scored 21 points in the opener. And he took a team-leading 13 shots and scored 9 points on Sunday. Missouri also lost the opener in embarrassing fashion to UMKC, and that seems par for the course for a team we pegged near the bottom of the SEC. When a freshman outside the Top 20 is leading your team, this is a rebuilding season.

We also had Rashad Vaughn near the top of the freshmen scoring list and he is averaging 22 PPG through two games. But with Running Rebels winning their opening two games by a combined 3 points, Vaughn is going to need a lot more help.

2. Many of our preseason projections are going to be wrong and I love it.

Of course, the more you project, the more opportunities you have to be wrong. But the beauty of college basketball is the unpredictability, and I love when players surprise us.

Georgetown’s LJ Peak went 9 for 9 from the floor and scored 23 in the opener for the Hoyas. Our preseason projections were based on recruiting data from ESPN, Scout, and Rivals. And based on the recruiting rankings, we liked Georgetown’s Isaac Copeland to be the Hoyas breakout freshman. But Georgetown observers who watched summer league games said that LJ Peak had blown up over the summer, and at least in the opener Peak put on a dominant performance. Perhaps someday summer league stats will be more readily available and we can see how much predictive power they have. But in the meantime, players like Peak remain hidden gems to everyone except the true team insiders.

3. The most important thing in the early games is the surprise roster news.

Jamie Dixon surprised us by announcing that Durand Johnson would not play this year for Pittsburgh. Cameron Wright (injured) and Durand Johnson (suspended) were projected to be Pittsburgh’s top two scorers in August, and the narrow home win against Samford may be a sign that eventually player losses add up, even for a coach as brilliant as Jamie Dixon.

Oklahoma got great news with TaShawn Thomas’s surprise eligibility. I see their offense being about 1.6 points better and their defense being about 1.5 points better with Thomas in the fold, which makes them neck and neck with Wichita St. in my preseason rankings. I’m not quite willing to endorse them as a Top 10 squad because of the defensive concerns. (Not only was Oklahoma terrible defensively last year, but Thomas was only an average defender on a Houston team that struggled to get stops.) But there is no question that having Thomas upgrades Oklahoma’s frontline tremendously.

4. The next most important thing is rotation patterns.

If you can learn something from watching Duke blowout mismatched opponents, then you are a better observer than me. The main thing I watch for in mismatch games is rotation patterns. It looks like North Carolina will play lineups with four forwards (with Theo Pinson, Justin Jackson, or J.P Tokoto at the off-guard slot). That makes a lot of sense because it gets the Tar Heels best players on the floor, but if spacing was a problem last year, the lack of a three point-gunner besides Marcus Paige could hurt the North Carolina offense again.

5. But don’t draw huge conclusions from early games.

Even if I like to study rotation patterns, I don’t want to get too carried away. Kansas’ Kelly Oubre played only 4 minutes in the opening night win. Does that mean the Top 10 recruit is one of the biggest busts in the country? Seton Hall super-freshman Isaiah Whitehead opened the year with a 1-10 night. Was he over-hyped? I’d like to see a lot more games before I draw these types of conclusions.

6. Early games can confirm your suspicions.

Askia Booker has been a high scorer for Colorado, but his lack of efficiency has been a liability. And his 2 of 14 shooting night to open this season looks like more of the same.

If you had concerns about Nebraska’s PGs after last year, it probably wasn’t comforting that Tai Webster and Benny Parker went a combined 3 of 14 in the opener.

Harvard’s guard depth is going to be an issue and they are going to have to play three guards at times this season because of matchups. But Harvard had to stick with Corbin Miller (2 of 8 from the floor), and Siyani Chambers (an uncharacteristic 9 turnovers) in the loss to Holy Cross, because they just don’t have a lot of choices on the perimeter right now.

Meanwhile, St. Joseph’s home loss to Fairleigh Dickinson should not have been a shock. While the preseason polls claimed St. Joe’s would finish in the middle of the A10, that was largely a courtesy vote based on last year. Based on their current roster, I expect this to be a rebuilding year for the Hawks.

(The more interesting story to me is that FDU pulled the upset. FDU has been near the bottom of the Pomeroy rankings the last two years and they won only ten games last year. And yet over the last two years they’ve beaten Seton Hall, Rutgers, and now St. Joe’s. FDU is starting to be the team that no power conference team should schedule.)

Meanwhile, USC, East Carolina, Rutgers, and Boston College may play in major conferences, but we all knew they had flawed rosters. Their early losses weren’t huge surprises.

7. Give teams time to build chemistry.

The big surprise was Ole Miss losing at home to Charleston Southern. I’m willing to give Ole Miss the benefit of the doubt for now. Ole Miss has a number of transfers and they obviously don’t have perfect chemistry yet. If LeBron James, Kyrie Irving, and Kevin Love need some time to build chemistry in the NBA, I’m willing to give a bunch of college transfers some time. But the selection committee might not feel the same way. And for a likely bubble team like Ole Miss, the opening loss to a non-Top 100 squad could be costly.

But the Ole Miss situation also illustrates why Houston’s opening win was so impressive. Despite playing with a number of new transfers, despite playing under a new head coach with a new system, and despite playing without lead-guard LJ Rose who is injured and out until at least December, Houston won on the road at a very good Murray St. team. Kelvin Sampson still knows how to coach.

8. Early in the year, things often go wrong.

The start of the college basketball season is relatively quiet, but maybe there is a reason these games are not in the spotlight. I’m guessing Temple (who won 40-37 against American) is happy that not many people watched their opening game. Temple had more turnovers 15 than field goals made 11.

But the players aren’t alone in failing to execute early. In Villanova’s closer than expected win against Lehigh, the possession arrow wasn’t working. The official at the scorers’ table solved the problem by drawing an arrow on a piece of paper. Watching the official manually flip the piece of paper over when the possession arrow changed was priceless.

The shot-clock was also broken early in the VCU/Tennessee game. But as the announcers correctly noted, when VCU is running its HAVOC defense, do you really need a shot clock?

9. Hype doesn’t guarantee a good game.

The Champions Classic may live up to the hype, but the joy of college basketball is the sheer number of games, not the heavily hyped-matchups.

ESPN heavily hyped Richard Pitino vs Rick Pitino, son vs father, in order to promote the Minnesota vs Louisville game on opening night. But what we saw was a painful, whistle-filled game. That’s not to say there weren’t amusing aspects to the game. I’m a huge fan of Minnesota PG Deandre Mathieu, and I was stunned by how well Terry Rozier and Chris Jones’ on-ball pressure shut him down. Louisville’s defense is going to be dominant again. It seemed somehow appropriate that Louisville’s Wayne Blackshear followed up his dominant exhibition performances with a quiet foul-prone game. That’s the story of Blackshear’s career at this point. The recruiting rankings and efficiency stats keep pointing to Blackshear becoming a dominant player, but it is never seems to happen in real games. On the other hand Montrezl Harrell complimented his explosive dunking with a newfound outside shot and looked fantastic. And it is always fun whenever a walk-on gets to play real minutes, as Louisville’s David Levitch did thanks to Shaqquan Aaron’s temporary ineligibility and Louisville’s foul trouble. But while these type of minor nuances can keep me amused during almost any game, I have to assume for any casual fan, Minnesota vs Louisville was just painful.

10. Maryland Terrapins Watch

Last year I thought Harvard was the most interesting story in college basketball so I tried to write about them each weak. This year my plan is to write about Maryland each week. The Terrapins will be playing in a new league, they have a coach on the hot seat, they have some talented veterans, and they have a roster full of talented young freshmen whose development is intriguing. Their journey should be fascinating.

Maryland won their opening game easily and I don’t like to comment on mismatches, but there is something I want to discuss. What does it mean that Charles Mitchell, who transferred from Maryland to Georgia Tech this off-season, had 20 points and 9 rebounds in his opener for his new team? Mitchell dominated a Georgia team that many expect to be on the NCAA tournament bubble. When Mitchell transferred, I was willing to believe it might not be critical, as Mitchell had never been an efficient player. Mitchell had an ORtg of 94 and 95 the last two years and was basically a role player for the Terrapins. But if Mitchell becomes a star at Georgia Tech, that adds more fuel to the critics of head coach Mark Turgeon.

Five Player Defense (And Offense)

Ken Pomeroy added some data to his website last season showing the most common five-player lineups for college basketball teams. One of the things I'd love to see him add is the defensive rating when various five-player lineups are on the floor.

For example, last year I was very curious whether Duke's defense was generally better in five-player lineups that included the 7'0" Marshall Plumlee.

I don't know of a source that tracks five-player lineup defensive efficiency (or offensive efficiency) for every team, but @nuclearbdgr currently tracks this type of data for Wisconsin. And he was nice enough to share his data with me for last season. The next table shows Wisconsin's two most common lineups last year. This featured a trade-off of Frank Kaminsky and Nigel Hayes:

Starters

Minutes

Off. Eff.

Def. Eff.

Diff

Traevon Jackson, Josh Gasser, Ben Brust, Sam Dekker and Frank Kaminsky

485

1.20

0.97

0.24

Traevon Jackson, Josh Gasser, Ben Brust, Sam Dekker and Nigel Hayes

164

1.15

1.03

0.12

We could probably guess that because of Kaminsky's outside shooting that the Badger offense was better with Kaminsky on the floor. But not everyone would necessarily conclude Kaminsky was the better defender. Kaminsky is not the most agile defender, and Hayes was quite strong if undersized in the post. But the numbers suggest that having the 7 foot Kaminsky on the floor did make a big difference to the Badgers' defense. Wisconsin’s defense allowed 1.03 points per possession with Hayes vs 0.97 points per possession with Kaminsky with the same set of teammates on the floor.

Admittedly, this data isn’t adjusted for opponent. But the bigger problem with this data, as with most college basketball data, is simply the small sample sizes. These were the only five-player lineups that Wisconsin used for over 100 minutes last season. I can think of a lot more fun questions to ask with this data, but everything else in this column suffers from a significant small sample problem.

Many people project Traevon Jackson, Josh Gasser, Sam Dekker, Nigel Hayes, and Frank Kaminsky to be Wisconsin's five-man starting rotation this year, so a natural question is how these five played together last year. But this lineup played only 13.5 minutes together last season. I can tell you it was a dynamic group, scoring 1.54 points per possession while allowing 0.73 points per possession, but drawing conclusions based on 13.5 minutes of data is foolish.

To expand the sample size, we might ask how Wisconsin played last year whenever they played the three big men with any guards. When Dekker, Hayes, and Kaminsky were on the floor together, how did the Badgers perform?

Three Bigs With

Minutes

UW Pts

Opp Pts

UW Poss

Opp Poss

Jackson/Gasser

13.5

30

16

19.5

22

Gasser/Brust

15.1

25

29

21

21

Jackson/Brust

13.4

31

22

22

20

Koenig/Gasser

1.1

1

2

2

2

Jackson/Koenig

6.3

6

10

10.5

10

Koenig/Brust

7.6

21

9

11.5

12

3 Big Total

56.8

114

88

86.5

87

Dividing Wisconsin's points by Wisconsin's possessions we see that a lineup with these three big men was much better offensively, with basically no impact on the team's defense:

Wisconsin

Off Eff

Def Eff

Diff

Dekker/Hayes/Kaminsky together

1.32

1.01

0.31

All other Lineups

1.16

1.01

0.16

I find this fairly fascinating, even if the sample size is too small. Probably the biggest surprise is that the offense was so great last year with these three big men playing together. You might be surprised to see this since Hayes was Wisconsin's least efficient rotation player. But ORtg doesn't always explain a player's role in putting pressure on a defense.

For example, Traevon Jackson has never been Wisconsin's most efficient player, in part because he turns  the ball over on occasion. But that doesn't mean he isn't vital to making the Wisconsin offense work. Jackson is the best player at beating his man off the dribble and causing the defense to collapse. And when the shot-clock is winding down, Jackson is the one player who can create a shot other than a jacked-up three.

In the same vein, Hayes puts a real pressure on the defense whenever he is on the floor because he is such a great back-to-the basket player. Hayes is incredible at drawing fouls, and the attention he draws in the paint makes the Wisconsin offense better.

I think what you see here is that teams guarding Wisconsin faced a real dilemma with this bigger lineup. If they kept their big defenders in the paint to stop Hayes from posting up, that often means Dekker or Kaminsky were shooting over a shorter player, and three point shots are always easier without a hand in your face.

You might think with a taller group of players on the floor that Wisconsin would be better defensively, but the numbers don't support that. I suspect that with the bigger lineup that Wisconsin struggled to keep certain players from driving to the basket.

Of course, you may also wonder if these numbers are slanted because of the quality of competition. According to the data, Wisconsin used this lineup of three big men against a variety of opponents, as listed in the next table. The small sample size is a concern, but I don't think the quality of opponent is greatly impacting these numbers.  

Wisconsin played Minnesota three times, which is one reason they used this lineup the most against the Gophers.

Opponent

Minutes

Minnesota

11.2

Green Bay

6.4

Northwestern

6.2

St. Louis

5.9

Iowa

4.8

Michigan

4.3

Indiana

2.9

Oral Roberts

2.5

E. Kentucky

2.3

Milwaukee

1.9

Ohio St.

1.8

Purdue

1.4

Arizona

1.2

Michigan St.

1.1

Illinois

1.1

North Dakota

0.9

Penn St.

0.6

Baylor

0.5

Total

56.8

Wisconsin doesn't have to play three big men this year. I suspect we will see lineups with Traevon Jackson, Josh Gasser, and Bronson Koenig playing together as well. But according to Nuclear Badgers' calculations, those lineups were not quite as dominant, with an offensive efficiency rating of 1.16 and a defensive efficiency rating of 1.04, a difference of just 0.12. Those three guards played together 132 minutes last year so we have a little more data on that group.

We also need to remember that Hayes and Koenig were true freshmen last year. Typically players improve a lot in their second season. So whether the Badgers use three guards or three forwards, the experience that Hayes and Koenig gained last season should significantly improve their efficiency.

And the reality with this team is clear. Any lineup with Dekker and Kaminsky, two forwards that have a chance to play in the NBA, is going to be extremely dangerous.

Projections, The Year After A Breakout Season, And The Importance Of Scouting

This past week at Sports Illustrated, Luke Winn and I revealed our Top 100 Scorers for 2014-15, our Top Freshman Scorers, our Breakout Scorers and our Top D1 Transfers. Past college stats, coach effects, and recruiting rankings were used to predict player performance.

Every year I try to do something new with my projections. Last year I added a simulation. Rather than simply project a mean for each player, I looked at the variance in performance based on player type (freshman, senior, transfer), and I allowed individual performances to vary as some players outperform or underperform expectations. I simulated the season 10,000 times and used the median projections to rank all 351 D1 teams. This year’s team rankings will be revealed by SI on Nov 4th.

This year the biggest thing I wanted to do was to make player projections more accessible to readers by projecting PPG, RPG, APG for some of the nation’s top players. I chose to focus on PPG in large part because I think it is more accessible to most casual fans of college basketball. I certainly understand how PPG can be misleading in certain situations. There are certainly a large group of fans that value ORtg and usage over PPG and would prefer we not indulge in “paceism” thereby elevating players from North Carolina at the expense of players from Virginia.

But I don’t think we should completely trash PPG. As a single measure, it contains a lot of information. PPG incorporates both information on efficiency and usage. It also incorporates information on a player’s relative value to a team. Coaches are interested in playing their best players major minutes. In the preseason, it doesn’t make sense to project a bench player to be very efficient and under-utilized unless a team is extremely deep at a certain position. Certainly in most sensible preseason models, minutes will be correlated with player quality. And because PPG incorporates efficiency, usage, and player value (through minutes), it says a lot about who are the most important players in college basketball.

PPG is very sensitive to the minutes’ projection. And that’s why working with Luke Winn has been such a tremendous advantage. Luke has the contacts to help vet more of our lineup projections. But Luke also has a great statistical background as well. One of the first things Luke noticed when he saw the player projections was that we needed to adjust playing time based on coach-specific rotation patterns. For example, Notre Dame’s Mike Brey tends to give his best players major minutes, while Arkansas’ Mike Anderson tends to use a more balanced rotation. Thus this year we added coach-specific rotations to the model.

That said I am always looking for areas to improve the model. And that’s why I love Twitter questions. Sometimes readers innocently ask questions that shed a lot of nuance and light into the projection process:

Paraphrasing @DarenHill: Why is Branden Dawson projected to have fewer RPG than last year?

First, we think Dawson will be one of the best rebounders in college basketball this year. We project him to have the 26th most rebounds per game in the nation.

When I first saw this question, I panicked and wondered if the model was putting too much emphasis on Dawson’s height. I have a separate regression equation for freshman, transfers, and veteran players based on various characteristics, and height is an important predictor of rebounding. Dawson is an under-sized post-player and I was worried that the model might be weighting his height too heavily. But when I double-checked the numbers, Dawson’s height was not the key factor. For a senior like Dawson with three years of player stats, height is almost irrelevant in the model.

The second thing I was worried about was that we had Dawson’s minutes’ projection wrong. We project Dawson to play around 30 minutes per game. That could be low for a player many of us think will be Michigan St.’s best player this season. But keep in mind that Dawson is a forward and it is hard for forwards to get major minutes because they are more likely to get foul trouble. The current model will sometimes project a guard to play 35 minutes per game, but that’s a very dubious prediction for a post player. More importantly, Tom Izzo is not a coach who overuses his best players early in the season. Izzo really likes to give his bench a chance to play to evaluate his players. Dawson was playing more than 30 minutes per game in the post-season last year, but on the full year that was a fair representation of his playing time.

As it turns out, the reasons for Dawson’s slight decrease in rebounding is Dawson’s past college stats. But before I delve into Dawson’s situation, I want to talk about the problem of small sample sizes and bounce-back seasons. If I have a college three point shooter who shoots 40% on 30 shots from three as a freshman and 30% on 50 shots from three as a sophomore, I think we’d all acknowledge that we would expect him to bounce back and shoot better on his threes as a junior. And 10 years of historical data back that up. Last year’s performance is the best predictor, but we shouldn’t throw out the data on what happened two years ago.

The dilemma we often face when projecting players is what to make of players with a huge improvement in performance. For example, if a player shot 30% on 30 shots from three as a freshman and 40% on 50 shots from three as a sophomore, is that a breakout performance or a hot-streak? I can tell you based on the historic stats that when a player has this profile, on average he will make about 38.5% of his threes as a junior. And that slight drop in efficiency can actually lead to a lower ORtg prediction and a lower PPG prediction for what everyone perceived to be a breakout player.

Oklahoma’s Isaiah Cousins is a good current example of this. He improved his ORtg from 72.9 as a freshman and 112.8 last year. I now project him to have an ORtg of 110.0 this year. The reason last year gets so much weight is because college players are at the developmental stage of their career and breakouts are quite common. But it should also make some sense that the previous season should get some weight. The college season is short and we have a limited sample of games to ever have full confidence in a player’s ability. Cousins made 38 of 94 threes last year, but that’s not a large enough sample to really know that he is an elite three point shooter. (The model is also worried because Cousins was a 2.7 star recruit out of high school. Star ratings often provide information about a players potential and they suggest that Cousins may be close to his ceiling.) Regardless, when you see my projections for Oklahoma this is one of the reasons my model doesn’t have the Sooners as high as some other college basketball experts.

Jumping back to Branden Dawson, as a sophomore he grabbed 16% of the available defensive rebounds. As a junior he grabbed 21% of the available defensive rebounds. My model projects him to grab 20% of the available defensive rebounds this season. Thus his overall rebounding numbers are projected to be a little worse.

The historic stats say this is the most likely outcome for Cousins and we can debate whether last year’s improvement was real. But there’s an added wrinkle with Dawson and that’s the reason I wrote this longer column. Dawson essentially changed positions between his sophomore and junior seasons. As a sophomore, Dawson played a lot on the wing and spent a lot less time close to the basket. As a junior, particularly late in the season, Dawson was playing almost exclusively at the four-spot. And Dawson is expected to play major minutes at the four this year. Thus we should probably weight last season even more highly and discount his sophomore season when projecting Dawson’s numbers.

This is a hard adjustment to make systematically. In terms of Dawson’s position on the official Michigan St. roster, nothing has changed. But there is some data of this type available. Here at RealGM.com, we have a projection for player position based on the recorded stats. Ken Pomeroy also added this feature last season. Perhaps by incorporating this type of information, we can do an even better job projecting players in the future.

But in college basketball there is still a lot that the stats overlook and that we can only learn from watching the games. As much as I believe in the projection model Luke Winn and I have been working on, I can say emphatically that over the next month as teams begin to have exhibition games and host their first early season opponents, you will learn things that dispute what our numbers suggest. Basketball is still a sport where scouting and watching film is incredibly important. But to me, this is also the beauty of college basketball relative to MLB. In baseball, almost everything, including range on defense, can now be quantified to some degree. But in basketball, there is still a lot to be learned by watching the games.

College Basketball Preview 14-15: Big Ten

Wisconsin was dominant on a per-possession basis last year, they went to the Final Four, and they bring nearly everyone back, which will make challenging for the Big Ten very difficult for everyone else.

College Basketball Preview 14-15: The Rest

In this piece, we preview the Ivy, Big West, MAC, Horizon, MAAC, Conference-USA, Patriot, Summit, CAA, Ohio Valley, Sun Belt, Big South, WAC, Big Sky, America East, Atlantic Sun, Southern, NEC, Southland, MEAC and SWAC.

College Basketball Preview 14-15: Big 12 Conference

Despite an uncertain point guard situation, Kansas remains the clear favorite in the Big 12 with Texas and Iowa State a clear step behind.

College Basketball Preview 14-15: Missouri Valley Conference

While it is unclear where Wichita State ranks nationally, they're the clear favorites to win the Missouri Valley Conference ahead of Northern Iowa.

College Basketball Preview 14-15: Pacific-12

Arizona are the clear favorites to win the Pac-12 again in 2015 with UCLA, Stanford and Utah hoping for a place in the top-25.

College Basketball Preview 14-15: American Athletic Conference

SMU and UConn are the co-favorites to win the American Conference, with Memphis, Tulsa and Cincinnati hoping to reach the Big Dance.

College Basketball Preview 14-15: Big East

Villanova won the Big East last season and it hardly seems fair that they also have the most returning minutes. Georgetown will be hoping for a place in the top-25, while Xavier, St. John's, Marquette and Providence will be tourney bubble teams.

College Basketball Preview 14-15: Atlantic-10

The problem for teams in the A10 is that it can take longer to restock the cabinet. When talented seniors leave, teams in the A10 sometimes need a year or two to rebuild, while teams in the Power Five conferences simply reload.

College Basketball Preview 14-15: WCC

Gonzaga could become a top-10 team in the country, while BYU and Saint Mary's are hoping to merely make the NCAA tournament.

College Basketball Preview 14-15: SEC

Kentucky and Florida are obviously playing for top seeds in the tourney, while Arkansas should comfortably be in the field. You can throw the next eight teams in a hat, and defend almost any ordering.

College Basketball Preview 14-15: Mountain West

UNLV has talent. Wyoming should be strong defensively. Boise St., Colorado St., and Fresno St. should be strong on offense. And New Mexico has some quality players. But San Diego St. is the class of the league, and no one else is even close.

College Basketball Preview 14-15: ACC

Duke are their favorites and their season will hinge on the play of Jahlil Okafor and Tyus Jones, while Louisville, North Carolina and Virginia will challenge.

Ten College Teams That Will Play Faster

Every summer coaches tend to give interviews and talk about how they plan to play faster the following season, but it rarely happens. Here are 10 teams we expect to actually play faster.

Which Types of Players Benefited the Most From Change in Way Fouls Called? (Part 2)

The rule changes increased points per possession scoring and increased ORtgs at every position, but the increase in free throw rate and decrease in turnovers was not equivalent for all positions.

Which Types of Players Benefited The Most From Change In Way Fouls Called? (Part 1)

Points per possession were higher, free throw attempts were up, and turnovers were down. But we have not seen any discussion about how this impacted different types of players.

College Basketball Greatness Is Always Fleeting

In the major conferences, no team has improved more than three years in a row right now. Iowa St., Oklahoma, Houston, Wake Forest, and Virginia have all made improvements for three straight years.

Players In NCAA With Biggest Jumps In Points Per Game

Itís easy to look at the summer as a chance to earn money, play video games, and catch your breath. But for a select few players every year, the time they put into the gym results in huge gains in every measurable category.

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