My Team’s Week 5 Recap
This last weekend started out extremely slowly for me. At least for the first hour of football Sunday afternoon, I was biting my nails thinking nothing good was happening for my team. My opponent had already gained about 19 points on me based on the Thursday night game, and I wasn’t sure if I was going to be able to keep up.
Then I received the alert that RB Saquon Barkley (New York Giants) had caught a TD pass from WR Odell Beckham Jr. Say what again? After that it was off to the races as Barkley ended up with 29 PPR points. I also had a massive amount of help from TE Zach Ertz (Philadelphia) with 27 points, WR Tyler Lockett (Seattle) with 19 points, and WR Stefon Diggs (Minnesota) with 22 points. My opponent didn’t fare so well as I ran away with the win scoring 120 points to his 77 points.
I improve to 3-2 on the season with a huge match-up with a team that is 4-1 in my league this upcoming weekend. I ended up picking up RB Lamar Miller (Houston) off the waiver wire in my league. He didn’t play last week due to a chest injury, but it sounds like he will be good to go this week. I’m hoping that will give me at least a boost in the right direction!
Model Updates
I spent a good chunk of the early morning hours Monday scraping Football Outsiders for some of their proprietary statistics to add to my model. They are essentially team statistics. Unfortunately I don’t think FO has historical individual player data; they report out player data weekly, but it shows season totals and doesn’t break it out week-by-week. I scraped that particular season data when I made my initial season projections before the season started. However, with the new team data I scraped, I was hoping to find features that would be better predictors for an individual’s performance based on the team around him. That analysis will continue in the coming weeks, but I was able to use a few of those features this week.
The new data also has information on teams and their opponents. My next step is to try and leverage that opponent data to be able to predict how a player will perform specific to the team their playing in the upcoming week especially in terms of how they’ve performed historically against that team. Obviously on my own that could prove to be complicated, but it’s definitely a challenge that I wholeheartedly accept!
One more change I made was to the tables that you see below. If a player or team’s previous week’s fantasy points were zero, I indicate whether they were in a BYE week or did not play (DNP). If a player/team still shows zero, then it means that they played in the previous week, and just were not all that useful to their team. I also indicated the injury status for players that had injuries provided by Rotoworld. For this week that information is current as of Wednesday October 10 at 8 AM CST. Much can change through Sunday afternoon so be sure and keep an eye on your own individual rosters up through game time!!
Quarterbacks
Top 20 Quarterback Week 6 Fantasy Predictions
| Player | Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions | Injuries |
|---|---|---|---|---|
| Philip Rivers | LAC | 25 | 29 | |
| C.J. Beathard | SF | 32 | 28 | |
| Jared Goff | LAR | 22 | 28 | |
| Deshaun Watson | HOU | 27 | 28 | Questionable: Chest Injury - Likely to Play |
| Patrick Mahomes | KC | 23 | 25 | |
| Aaron Rodgers | GB | 35 | 24 | |
| Andrew Luck | IND | 30 | 23 | |
| Tom Brady | NE | 35 | 22 | |
| Russell Wilson | SEA | 22 | 22 | |
| Matt Ryan | ATL | 19 | 21 | |
| Baker Mayfield | CLE | 23 | 20 | |
| Carson Wentz | PHI | 26 | 20 | |
| Andy Dalton | CIN | 17 | 19 | |
| Blake Bortles | JAC | 35 | 19 | |
| Kirk Cousins | MIN | 19 | 17 | |
| Dak Prescott | DAL | 18 | 17 | |
| Jameis Winston | TB | BYE | 17 | |
| Ben Roethlisberger | PIT | 26 | 16 | |
| Marcus Mariota | TEN | 7 | 16 | |
| Case Keenum | DEN | 27 | 15 |
Does anybody watch THE GOOD PLACE (currently in it’s 3rd season) that airs on NBC on Thursday nights? It’s a fantastic show; I highly recommend it especially if you can keep away from spoilers for the first season. One of the characters from that show is from Jacksonville and has a huge love for the Jaguars and especially Blake Bortles. The show runners/writers have had to factor in how good the Jaguars have become in the last two years, and it’s been fun to see how they’ve been doing that (spoiler alert: they’ve handled it very, very well). In any case, Bortles had a fine performance last week with 430 yards passing and 1 TD along with 34 yards rushing and 1 TD. Had it not been for 1 lost fumble and 4 interceptions to go along with that performance, he would have been considered pretty darn perfect!
Also congratulations to Drew Brees (New Orleans) for becoming the NFL’s all-time passing yards leader previously held by Peyton Manning (Indianapolis and Denver). Brees currently has 72,103 passing yards, and he definitely doesn’t look like he’ll be stopping anytime soon.
As for this week, you can already tell the differences that some of the new features to the model makes. Before, Patrick Mahomes (Kansas City) and Deshaun Watson (Houston) would lead the predictions, but now we have Philip Rivers (Los Angeles Chargers), C.J. Beathard (San Francisco), and Jared Goff (Los Angeles Rams) in the Top 3. Once this week is over, I may want to go back to see how they fare against the model for next week’s analysis.
Running Backs
Top 20 Running Back Week 6 Fantasy Predictions
| Player | Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions | Injuries |
|---|---|---|---|---|
| Melvin Gordon | LAC | 22 | 36 | |
| Todd Gurley | LAR | 33 | 36 | |
| Ezekiel Elliott | DAL | 15 | 31 | |
| Saquon Barkley | NYG | 29 | 26 | |
| Kareem Hunt | KC | 16 | 24 | |
| Austin Ekeler | LAC | 13 | 18 | |
| Royce Freeman | DEN | 8 | 18 | |
| Sony Michel | NE | 18 | 17 | |
| David Johnson | ARI | 21 | 16 | |
| LeSean McCoy | BUF | 13 | 15 | |
| Frank Gore | MIA | 6 | 13 | |
| Jordan Howard | CHI | BYE | 12 | |
| Marshawn Lynch | OAK | 6 | 12 | |
| Nyheim Hines | IND | 16 | 11 | |
| Phillip Lindsay | DEN | 11 | 11 | |
| Ito Smith | ATL | 8 | 11 | |
| Dalvin Cook | MIN | DNP | 11 | Questionable: Hamstring - Week to Week |
| Lamar Miller | HOU | DNP | 10 | Questionable: Chest-Likely to play |
| T.J. Yeldon | JAC | 26 | 10 | |
| Duke Johnson Jr. | CLE | 5 | 10 |
One of the most important things to consider is whether your model makes intuitive sense. One thing you may or may not have noticed is the absence of James Conner (Pittsburgh) from the top 20 list. With Le’Veon Bell still holding out, Conner has done very well as a starter. This season alone he’s averaging 22 FF points per game. One of the issues for my particular model is that it looks at a player’s entire career. In that case, Conner’s average falls to just under 8 FF points per game. My model doesn’t seem to take too kindly to that and predicted Conner to have only one point this upcoming week. Unless he has some sort of injury during the game, that is extremely unlikely.
Earlier in the year I mentioned that my model seemed to favor new players/rookies who came out of the gate scoring lots of points. On the flip side, the model does not factor inr players who historically have not done well but have had significant improvement in more recent performances. Obviously more work needs to be done by me to weigh those two things differently in the model to be flexible to either situation. It’s a learning process, and the more things like this I see, the more I enjoy this whole project!! What a challenge, right?!?
Wide Receivers
Top 20 Wide Receiver Week 6 Fantasy Projections
| Player | Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions | Injuries |
|---|---|---|---|---|
| Cooper Kupp | LAR | 21 | 31 | |
| Calvin Ridley | ATL | 8 | 30 | |
| Julio Jones | ATL | 11 | 29 | |
| Odell Beckham Jr | NYG | 27 | 26 | |
| Mike Evans | TB | BYE | 24 | |
| DeAndre Hopkins | HOU | 24 | 24 | |
| Antonio Brown | PIT | 28 | 24 | |
| A.J. Green | CIN | 17 | 24 | |
| Demaryius Thomas | DEN | 22 | 23 | |
| Brandin Cooks | LAR | 0 | 22 | Questionable: Concussion - Status Uncertain |
| Keke Coutee | HOU | 17 | 22 | Questionable: Hamstring-Game Time Decision |
| JuJu Smith-Schuster | PIT | 13 | 22 | |
| Josh Gordon | NE | 13 | 22 | Questionable: Hamstring-Likely will play |
| Stefon Diggs | MIN | 22 | 21 | |
| Allen Robinson II | CHI | BYE | 20 | |
| Alshon Jeffery | PHI | 6 | 20 | |
| Tyreek Hill | KC | 13 | 20 | |
| Brandon Marshall | SEA | 0 | 20 | |
| Amari Cooper | OAK | 2 | 20 | |
| Larry Fitzgerald | ARI | 6 | 20 |
Admittedly, these predictions leave me scratching my head. I mean, seriously, how awesome would it be for two WR’s on the same team to score 29 or more point fantasy points in one game each (note to self: see if that’s happened). The current model shows Calvin Ridley and Julio Jones (Atlanta) scoring 30 and 29 points, respectively. Oh, how I wish…actually I wouldn’t mind if Jones received all of the points that Ridley would get so 59 points for Jones, please! Going to need it in my match-up this weekend!
Not too many other surprises there although I did notice that all of the models really seem to like players from both the Rams and the Chargers. This could be due to the new team statistics that I added in as features to the model. Hmmm…interesting…
Tight Ends
Top 12 Tight End Week 6 Fantasy Projections
| Player | Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions | Injuries |
|---|---|---|---|---|
| Rob Gronkowski | NE | 14 | 32 | |
| Travis Kelce | KC | 15 | 24 | |
| Jimmy Graham | GB | 14 | 21 | |
| O.J. Howard | TB | BYE | 18 | |
| Kyle Rudolph | MIN | 9 | 16 | |
| Cameron Brate | TB | BYE | 15 | |
| Zach Ertz | PHI | 27 | 14 | |
| George Kittle | SF | 13 | 13 | |
| Ricky Seals-Jones | ARI | 0 | 12 | |
| Jared Cook | OAK | 6 | 11 | |
| Eric Ebron | IND | 32 | 10 | |
| Charles Clay | BUF | 2 | 10 | Questionable: Ankle - Likely to play |
Over the weekend, a long time friend of mine texted me asking to look over a trade he was mulling over in his league. He was looking to trade a running back and Eric Ebron (Indianapolis) for another TE/RB pairing. I felt that keeping Ebron would be a better idea and to reject that trade (among other factors; I really didn’t like who he was trading for). Turns out Ebron somehow heard about the trade and had a monster week with 32 FF points to prove his worth as a FF Tight End!
By the way, I’m sure that was just a fluke. Advice by me should always be taken with a grain of salt, maybe some black pepper, and heck let’s throw in some Fiesta seasoning!!
Kickers
Top 12 Kickers Week 6 Fantasy Predictions
| Player | Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions |
|---|---|---|---|
| Matthew McCrane | OAK | BYE | 19 |
| Harrison Butker | KC | 12 | 15 |
| Justin Tucker | BAL | 9 | 11 |
| Stephen Gostkowski | NE | 8 | 10 |
| Matt Bryant | ATL | 5 | 9 |
| Dan Bailey | MIN | 11 | 9 |
| Brett Maher | DAL | 10 | 9 |
| Jason Myers | NYJ | 10 | 8 |
| Josh Lambo | JAC | 2 | 8 |
| Jake Elliott | PHI | 7 | 8 |
| Caleb Sturgis | LAC | 8 | 8 |
| Robbie Gould | SF | 0 | 8 |
Defense
Top 12 Defenses Week 6 Fantasy Predictions
| Team | Week 5 Fantasy Points | Week 6 Fantasy Predictions |
|---|---|---|
| CHI | BYE | 9 |
| ARI | 20 | 9 |
| DAL | 5 | 9 |
| NE | 7 | 9 |
| NYG | 5 | 7 |
| TB | BYE | 6 |
| ATL | 2 | 5 |
| DEN | 5 | 5 |
| MIN | 13 | 5 |
| CIN | 21 | 5 |
| SEA | 4 | 5 |
| MIA | 10 | 5 |
I really like the way this model turned out intuitively. Obviously since Defenses are more about a team in FF leagues rather than individual players, it makes sense that adding more team defensive-based statistics to the model would likely improve performance of the model (not all the time, mind you, since there are many factors to consider, but since I’m only working on a handful of features here…). Obviously you’re going to have defenses rack up points like Arizona and Cincinnati did, but it seems to me to be more tempered with the predictions as you can see here with all the predictions being in the single digits.
*The predictions for this model comes from statistics tables scraped from The Huddle and Football Outsiders from 2006-2018 . Injury data is from Rotoworld as of 8 AM Wednesday October 10th, 2018.
As usual I used the Fantasy Points-Per-Reception (PPR) scores for my predictions which comes from the following:
- 1 point per 25 yards passing
- 4 points per passing touchdown
- -2 points per interception thrown
- 1 point per reception
- 1 point per 10 yards rushing/receiving
- 6 points per TD
- 2 points per two-point conversion
- -2 points per fumbles lost
All predictive elements for Fantasy Football Models are for entertainment purposes only. Do your own research before making any decisions on your Fantasy Football team especially in money leagues!!