Week 2 Picks

Got an early start this week. This week's spreadsheet can be found at...

Week 2 Picks & Stats
Week 1 Picks & Stats

I add games as the week goes by, so keep checking back!
During the course of the week, if the line changes by at least 1 point I'll redo the sim. Anything less than that only changes the % by 1 or 2 pts. I'll let everyone know of the change when it happens. When I info to the post, I'll separate them at the bottom with '---'.

 Watch out for the NE NYJ game... NYJ to win at 67%. I simulated twice to be sure. The numbers make sense, but Brady is a wild card.
---

The rest of the stats will be up a little later, Friday at the very latest.

---

Most of the stats are up.

CLE at DEN
Check out the Denver game! I don't think I've ever seen such a mismatch. DEN averaging 26 and CLE averaging 11 points. This is the first 70+% straight up game of the season... it's the first 80+%, too. Their passing games are pretty even. It looks like it really came down to the run game. Oddly enough, they perfectly matched each other in rush yds and carries, but on average, DEN scored 1 more rushing TD than CLE. 1.5 to 0.6. Sounds like red zone efficiency to me. Watch Buckhalter and Moreno destroy Cleveland's 32nd ranked run defense.

---

Alright, everything is up for the week. It looks like NFLSim went a little wild this weekend with its predictions. I'm going to chalk it up to the small amount of stats to work with. Then again, last week's predictions were a bit counter-intuitive and they worked out pretty nicely. Use these picks at your own discretion, don't rely on them for anything too important. Next week we'll be in business fo' sho'.

There's a 2nd 70+% straight up game: MIA over IND, who'da thunk it. In both passing and rushing, Miami was able to score more touchdowns.

Then again, there are some experts at ESPN and other sports news outlets that agree with some of the more eccentric picks...

Week 15: Start 'em, Sit 'em

To celebrate the end of finals, here's some fantasy advice.

QB:
Start 'em
1. Payton Manning, IND
2. Donovan McNabb, PHI
3. Kurt Warner, ARI
4. Philip Rivers, SD
5. Chad Pennington, MIA

Sit 'em
1. Ben Roethlisberger, PIT
2. Derek Anderson, CLE
3. Carson Palmer, CIN
4. Joe Flacco, BAL
5. Matt Hasselbeck, SEA

RB:
Start 'em
1. Michael Turner, ATL
2. DeAngelo Williams, CAR
3. Chris Johnson, TEN
4. Clinton Portis, WAS
5. Thomas Jones, NYJ

Sit 'em
1. Frank Gore, SF
2. Edgerrin James, ARI
3. Kevin Smith, DET
4. Pierre Thomas, NO
5. Jamal Lewis, CLE

Defense:
Start 'em
1. MIA
2. PHI
3. WAS
4. IND
5. ATL

Sit 'em
1. DET
2. CLE
3. DEN
4. SF
5. BUF

NFLSim Stats vs. Actual NFL Stats

I'm sure everyone's curious to see how NFLSim actually compares to real life. These are the overall results so far. First, I'll post the comparison of NFLSim averages to NFL averages. Later, I'll post a team-by-team comparison to see how well it works on a smaller scale. I'm only going to focus on the main stats: passing, rushing, and game stats. I'll put up my average alongside the real stats. When you average the stats from all of the teams, the total offensive averages are the same as the defensive averages.

Many stats are very close to reality, some aren't as close. I know many of you out there are interested in sports statistics and many are interested in fantasy football, so this is for you guys. NFLSim is good, but it's not perfect. This is an opportunity for everyone to get a better understanding of what it does as well as for myself to make improvements.

I encourage everyone to email other NFL simulators to find out how they're doing, then post that over here for a comparison. If you're going to be following their models, you should know how those models actually perform.

These numbers tell me that for the most part, everything is going very well. Some changes I need to make include: more passes, decrease the average rush yards, decrease fumble %, and adjust 3rd down play selection. No major changes, just little tweaks. Otherwise, things are going swimmingly. Send me some feedback, I'd like to hear what everyone thinks.

PASSING
ATT/GAME	NFLSim	NFL
Average	27.2	32.4
COMP/G
Average	17.0	19.8
COMP %
Average	62.3%	61.3%
YDS/G
Average	192.2	212.9
YDS/PASS
Average	7.06	6.97
PASS TD/G
Average	1.60	1.30
INT/G
Average	0.79	0.90
SACK/G
Average	2.1	2.1
QB RATING
Average	91.0	83.6

RUSHING
ATT/GAME	NFLSim	NFL
Average	27.6	27.3
YDS/G
Average	118.4	112.3
YDS/RUSH
Average	4.3	4.1
RUSH TD/G
Average	1.2	0.9
FUM/G
Average	0.6	0.4

GAME STATS
PTS/G	NFLSim	NFL
Average	22.9	22.2
PLAYS/G
Average	60.3	61.8
TOTAL YDS/G
Average	310.6	325.2
YDS/PLAY
Average	5.2	5.3
3rd DN %
Average	25.8%	39.4%
YDS/PT
Average	13.6	14.9

Week 11: Stats

Week 11	YDS/PASS	YDS/PLAY	YDS/PT	QB RATING
Arizona Cardinals	8.22	5.52	13.70	108.29
Atlanta Falcons	7.93	5.92	14.61	105.39
Baltimore Ravens	6.50	4.44	14.86	82.55
Buffalo Bills	8.03	5.60	12.55	99.65
Carolina Panthers	8.24	5.69	13.04	104.08
Chicago Bears	5.06	4.07	12.73	64.71
Cincinnati Bengals	6.17	4.45	16.77	73.28
Cleveland Browns	6.20	4.53	15.03	83.65
Dallas Cowboys	6.45	4.60	16.68	81.16
Denver Broncos	6.76	5.17	14.54	86.81
Detroit Lions	5.72	4.30	16.50	74.13
Green Bay Packers	7.25	4.97	13.48	94.74
Houston Texans	5.86	4.54	14.02	78.42
Indianapolis Colts	7.94	5.60	13.70	98.65
Jacksonville Jaguars	6.97	4.94	14.82	88.92
Kansas City Chiefs	6.67	5.11	13.90	86.81
Miami Dolphins	7.49	5.42	13.22	94.58
Minnesota Vikings	6.16	4.62	15.26	76.51
New England Patriots	7.15	4.92	12.35	98.34
New Orleans Saints	8.01	5.76	14.63	101.83
New York Giants	6.52	5.00	14.33	81.69
New York Jets	7.34	5.40	15.38	87.26
Oakland Raiders	6.27	4.48	17.35	77.90
Philadelphia Eagles	6.70	4.95	12.76	96.44
Pittsburgh Steelers	7.41	4.86	13.89	95.48
San Diego Chargers	6.95	4.53	13.89	91.91
San Francisco 49ers	6.80	5.20	15.93	83.15
Seattle Seahawks	6.40	4.88	13.35	83.52
St. Louis Rams	5.82	4.31	14.39	76.82
Tampa Bay Buccaneers	7.04	5.09	15.14	93.85
Tennessee Titans	6.50	4.77	13.70	87.08
Washington Redskins	7.25	5.42	12.59	101.63
Average	6.87	4.97	14.35	88.73

Week 10: Predictions

Ok, here's the new format. Same thing as before, but no I add the average scores as well. Underneath the matchup are the average scores. DEN's average score over the course of 500 simulations was 21.25 and CLE's average score was 21.40. Average scores aren't predictions of the score, they're just measures of relative performance. Every once in a while, one team will be favored to win even though on average they score less. This is the case with the DEN game. I wish there was an easier way to cram more stats into each game, but this blog format is really limiting.

I'm also planning on posting games as I finish them. One last change, instead of reposting everything an a "Results" section, i'm going to color everything in the "Prediction" section. A small "Results" section will sum up the weekend.

Only 2 upsets this week, DEN over CLE (52%) and HOU over BAL (57%). More 'UNDER's than usual. More favorites covering the spread, as well.

DEN at CLE -3.5, 45.5
DEN: 21.25
CLE: 21.40
Winner: DEN, 52%
Spread: DEN +3.5, 60%
O/U: UNDER, 61%

BAL -1 at HOU, 42
BAL: 21.57
HOU: 23.12
Winner: HOU, 57%
Spread: HOU +1, 59%
O/U: OVER, 55%

BUF at NE -3.5, 41.5
BUF: 22.10
NE: 23.41
Winner: NE, 55%
Spread: BUF +3.5, 54%
O/U: OVER, 59%

GB at MIN -2, 45.5
GB: 19.95
MIN: 23.45
Winner: MIN, 57%
Spread: MIN -2, 54%
O/U: UNDER, 59%

JAX -6.5 at DET, 44.5
JAX: 24.65
DET: 22.00
Winner: JAX, 56%
Spread: DET +6.5, 64%
O/U: OVER, 56%

NO at ATL -1, 50
NO: 22.22
ATL: 26.39
Winner: ATL, 59%
Spread: ATL -1, 58%
O/U: UNDER, 57%

SEA at MIA -8.5, 43
SEA: 17.19
MIA: 29.42
Winner: MIA, 79%
Spread: MIA -8.5, 54%
O/U: OVER, 59%

STL at NYJ -8.5, 44
STL: 19.05
NYJ: 27.06
Winner: NYJ, 70%
Spread: STL +8.5, 51%
O/U: OVER, 53%

TEN -3 at CHI, 38.5
TEN: 22.33
CHI: 18.47
Winner: TEN, 60%
Spread: CHI +3, 51%
O/U: OVER, 52%

CAR -9.5 at OAK, 37.5
CAR: 21.15
OAK: 19.93
Winner: CAR, 54%
Spread: OAK +9.5, 72%
O/U: OVER, 58%

IND at PIT -3.5, 39.5
IND: 17.97
PIT: 22.27
Winner: PIT, 62%
Spread: PIT -3.5, 54%
O/U: UNDER, 51%

KC at SD -15, 47
KC: 18.93
SD: 26.02
Winner: SD, 70%
Spread: KC +15, 74%
O/U: UNDER, 60%

NYG at PHI -3, 43.5
NYG: 18.88
PHI: 25.48
Winner: PHI, 65%
Spread: PHI -3, 58%
O/U: OVER, 52%

SF at ARI -9.5, 45.5
SF: 20.34
ARI: 24.25
Winner: ARI, 63%
Spread: SF +9.5, 70%
O/U: UNDER, 57%

Week 8: Results

This past week was an amazing week. Perhaps the best week yet. NFLSim knocked 'em out of the park, going 2 for 3 with underdogs (missed TB), 10-4 (71.4%) picking the winner, 8-4 (66.7%) against the spread, and 7-6 (53.8%) against the O/U. The spread and O/U combined for 15-10 (60%). Even BOA, which I've been tracking, but not posting, returned a solid 19%.

Straight	%	Wins	Games	Win %
	50-59	3	4	75.0%
	60-69	3	6	50.0%
	70-79	4	4	100.0%
	80-89	0	0	---
	90-100	0	0	---
	Total	10	14	71.4%
Spread	%	Wins	Games	Win %
	50-59	4	7	57.1%
	60-69	4	4	100.0%
	70-79	0	1	0.0%
	80-89	0	0	---
	90-100	0	0	---
	Total	8	12	66.7%
Total		Wins	Games	Win %
	50-59	6	11	54.5%
	60-69	0	1	0.0%
	70-79	1	1	100.0%
	80-89	0	0	---
	90-100	0	0	---
	Total	7	13	53.8%

ARI at CAR -4, 43.5
Winner: CAR, 57%
Spread: ARI +4, 59%
O/U: OVER, 51%

ATL at PHI -9, 45
Winner: PHI, 75%
Spread: ATL +9, 51%
O/U: OVER, 58%

BUF -1.5 at MIA, 42
Winner: MIA, 54%
Spread: MIA +1.5, 54%
O/U: OVER, 60%

KC at NYJ -13.5, 39
Winner: NYJ, 72%
Spread: KC +13.5, 64%
O/U: OVER, 71%

OAK at BAL -7.5, 36
Winner: BAL, 65%
Spread: OAK +7.5, 59%
O/U: OVER, 55%

SD -3 at NO, 46
Winner: NO, 54%
Spread: NO +3, 64%
O/U: UNDER, 55%

STL at NE -7, 43.5
Winner: NE, 67%
Spread: STL +7, 59%
O/U: OVER, 56%

TB at DAL -1.5, 40.5
Winner: TB, 68%
Spread: TB +1.5, 70%
O/U: UNDER, 52%

WAS -7.5 at DET, 42
Winner: WAS, 69%
Spread: DET +7.5, 52%
O/U: OVER, 62%

CIN at HOU -9, 44.5
Winner: HOU, 78%
Spread: HOU -9, 56%
O/U: OVER, 57%

CLE at JAX -7, 42
Winner: JAX, 60%
Spread: CLE +7, 66%
O/U: UNDER, 52%

NYG at PIT -3, 42
Winner: PIT, 56%
Spread: NYG +3, 55%
O/U: OVER, 57%

SEA at SF -5, 41
Winner: SF, 60%
Spread: SEA +5, 56%
O/U: OVER, 52%

IND at TEN -4, 41
Winner: TEN, 79%
Spread: TEN -4, 69%
O/U: OVER, 51%

Week 8: Sim Stats

Week 8	YDS/PASS	YDS/PLAY	YDS/PT	QB RATING
Arizona Cardinals	7.06	4.96	15.17	92.37
Atlanta Falcons	6.74	4.80	16.17	83.52
Baltimore Ravens	7.03	5.15	14.10	87.59
Buffalo Bills	8.36	5.15	14.93	105.65
Carolina Panthers	8.00	5.37	12.95	102.12
Chicago Bears
Cincinnati Bengals	7.00	4.76	17.17	90.33
Cleveland Browns	5.81	4.45	13.43	78.52
Dallas Cowboys	6.05	4.69	16.03	71.09
Denver Broncos
Detroit Lions	6.41	4.90	14.23	81.40
Green Bay Packers
Houston Texans	6.99	5.50	11.52	95.98
Indianapolis Colts	6.27	4.37	16.69	76.58
Jacksonville Jaguars	7.33	5.33	13.90	92.84
Kansas City Chiefs	5.83	4.28	13.98	79.56
Miami Dolphins	7.40	5.34	13.38	99.93
Minnesota Vikings
New England Patriots	8.07	5.77	14.12	103.31
New Orleans Saints	8.70	6.08	15.39	107.64
New York Giants	6.47	4.81	13.82	89.33
New York Jets	7.92	6.26	14.17	97.06
Oakland Raiders	5.71	4.13	15.12	73.03
Philadelphia Eagles	7.14	5.48	11.15	99.34
Pittsburgh Steelers	7.51	4.91	12.27	98.24
San Diego Chargers	7.21	4.93	13.91	91.26
San Francisco 49ers	8.51	5.57	13.33	102.46
Seattle Seahawks	5.59	4.54	13.88	72.59
St. Louis Rams	7.13	5.13	15.31	90.66
Tampa Bay Buccaneers	6.25	4.52	12.95	89.82
Tennessee Titans	7.04	5.28	12.31	92.63
Washington Redskins	7.86	5.43	12.84	110.53
Simulated Average	7.05	5.07	14.08	91.26

Week 7: Requested Stats

A while back I got a request to post yds/pass, yds/play, and yds/pt. At this point in the season, I think the numbers are getting accurate, so here are those stats for week 7.

TEAM	YDS/PASS	YDS/PLAY	YDS/PT
Arizona Cardinals
Atlanta Falcons
Baltimore Ravens	6.80	4.49	17.28
Buffalo Bills	7.59	5.32	12.65
Carolina Panthers	6.73	4.93	13.74
Chicago Bears	7.00	4.76	14.23
Cincinnati Bengals	6.39	4.18	13.41
Cleveland Browns	5.86	4.39	15.53
Dallas Cowboys	7.05	5.06	15.32
Denver Broncos	7.41	5.49	12.96
Detroit Lions	6.95	5.04	17.51
Green Bay Packers	8.11	5.71	13.52
Houston Texans	8.09	6.11	11.36
Indianapolis Colts	6.34	4.70	13.02
Jacksonville Jaguars
Kansas City Chiefs	5.38	4.38	14.60
Miami Dolphins	6.91	4.91	12.52
Minnesota Vikings	6.20	4.38	13.67
New England Patriots	7.88	5.68	14.57
New Orleans Saints	7.37	4.94	15.57
New York Giants	7.54	5.91	13.10
New York Jets	7.72	5.22	15.12
Oakland Raiders	6.71	4.94	11.81
Philadelphia Eagles
Pittsburgh Steelers	6.05	4.14	12.52
San Diego Chargers	7.31	4.94	14.76
San Francisco 49ers	7.09	4.93	14.95
Seattle Seahawks	5.83	4.46	15.55
St. Louis Rams	6.90	5.00	12.57
Tampa Bay Buccaneers	7.25	5.55	12.96
Tennessee Titans	6.62	4.90	13.98
Washington Redskins	7.49	5.63	12.20
Average	6.949	5.002	13.962

Week 6: Top 5 / Bottom 5

(The game predictions are below this post)
Let's have a little fun this week.

The top 5 QB's by rating will be:
1. Aaron Rodgers, GB: 109.3
2. Jason Campbell, WAS: 109.2
3. Chad Pennington, MIA: 105.7
4. Jay Cutler, DEN: 104.0
5. Gus Frerotte, MIN: 103.4
Botom 5:
28. Jeff Garcia (in for Griese), TB: 83.0
29. Dan Orlovsky (in for Kitna), DET: 82.0
30. Derek Anderson, CLE: 75.4
31. Peyton Manning, IND: 73.1
32. Charlie Frye (in for Hasselbeck), SEA: 71.5

Top 5 teams by rushing yards:
1. Washington Redskins: 178.3
2. Atlanta Falcons: 171.8
3. Baltimore Ravens: 165.3
4. Oakland Raiders: 160.8
5. Seattle Seahawks: 160.6
Bottom 5:
28. Philadelphia Eagles: 75.3
29. New Orleans Saints: 72.7
30. Cincinnati Bengals: 63.4
31. Indianapolis Colts: 47.4
32. Detroit Lions: 46.5

Top 5 offenses by Points Scored:
1. Minnesota Vikings: 30.8
2. Denver Broncos: 30.2
3. San Diego Chargers: 29.0
4. Washington Redskins: 27.6
5. New York Giants: 27.5
Bottom 5:
28. Carolina Panthers: 19.8
29. Detroit Lions: 18.8
30. Indianapolis Colts: 18.4
31. St. Louis Rams: 18.4
32. Cleveland Browns: 17.8

Top 5 Defenses by Yards Allowed:
1. New York Giants: 229.7
2. Baltimore Ravens: 234.4
3. New York Jets: 260.6
4. Minnesota Vikings: 278.4
5. Washington Redskins: 280.2
Bottom 5:
28. Seattle Seahawks: 350.5
29. Detroit Lions: 355.6
30. Denver Broncos: 357.5
31. Houston Texans: 367.0
32. St. Louis Rams: 395.0

That's enough for now. Any opinions?

Week 4: Results

Here's are the picks from week 4. Not great. It was a good week for the spread (58.3%) and o/u (75%), neither of which I posted. I'm going to put up everything from week 5 forward.

MIN at TEN -3
Winner: TEN, 74%

DEN -9.5 at KC
Winner: DEN, 67%

SF at NO -6
Winner: SF, 65%

ARI at NYJ -1.5
Winner: NYJ, 54%

GB at TB -1
Winner: TB, 52%

ATL at CAR -7
Winner: ATL, 65%

HOU at JAX -7
Winner: JAX, 54%

CLE at CIN -3.5
Winner: CIN, 78%

SD -7.5 at OAK
Winner: SD, 52%

BUF -8 at STL
Winner: BUF, 82%

WAS at DAL -10.5
Winner: DAL, 60%

PHI -3 at CHI
Winner: PHI, 57%

BAL at PIT -5
Winner: BAL, 55%

Straight	%	Wins	Games	Win %
	50-59	4	6	66.7%
	60-69	0	4	0.0%
	70-79	1	2	50.0%
	80-89	1	1	100.0%
	90-100	0	0	---
	Total	6	13	46.2%

Week 2 Predictions

I'm going to withhold the total predictions for this week, but I'll put up the winners and spreads. This week's predictions are going to sound ridiculous. I was actually thinking about waiting another week before putting them up, but I went back and looked at the simulation of last season's week 2 to see how they compared. In both weeks 2 there were many picks of huge underdogs, but that week actually turned out to be a very good one. I won't give out that week's exact numbers because I don't want heightened expectations. Remember, use these at your own risk. If you're in a suicide / survivor pool and you see that SF wins 79% when they're a 7 point dog, use some discretion. Bear in mind it's the beginning of the season, so the picks may not be as reliable because of a lack of data. That said, here we go...

If the confidence is 50%, I'll just write EVEN.

NYG -8.5 at STL
Winner: NYG, 76%
Spread: EVEN

IND -2 at MIN
Winner: MIN, 54%
Spread: MIN +2, 58%

NO -1 at WAS
Winner: NO, 61%
Spread: NO -1, 60%

CHI at CAR -3
Winner: CAR, 51%
Spread: CHI +3, 61%

BUF at JAX -5
Winner: BUF, 64%
Spread: BUF +5, 77%

TEN at CIN -1
Winner: TEN, 79%
Spread: TEN +1, 80%

GB -3.5 at DET
Winner: DET, 59%
Spread: DET +3.5, 64%

OAK at KC -3.5
Winner: KC, 81%
Spread: KC -3.5, 72%

SF at SEA -6.5
Winner: SF, 79%
Spread: SF +6.5, 89%

ATL at TB -7
Winner: ATL, 80%
Spread: ATL +7, 92%

SD -1 at DEN
Winner: DEN, 74%
Spread: DEN +1, 75%

BAL at HOU -4.5
Winner: BAL, 70%
Spread: BAL +4.5, 80%

NE at NYJ -1.5
Winner: NYJ, 53%
Spread: EVEN

MIA at ARI -6.5
Winner: ARI, 57%
Spread: MIA +6.5, 61%

PIT -6 at CLE
Winner: PIT, 91%
Spread: PIT -6, 79%

PHI at DAL -7
Winner: PHI, 65%
Spread: PHI +7, 84%

Simulating Teams vs. Simulating Players

Due to popular demand, I'll be writing a weekly article about various aspects of model building, money management strategy, or whatever questions anyone has. So if you're curious about something specific, speak up. This first article deals with the difference between simulating games using a team model versus an individual player model.


"Keep it simple, stupid" - Confucius

One of the most important decisions to make when simulating a sport is whether to simulate a game using team stats or to break it down further and use individual player stats. A convincing argument can be made for either method. If you've read anything about NFLSim's background, you know that the simulation uses team stats and not player stats. Here's a comparison of the two methods, in a football context:

Keep in mind that this is just one way to build a model; if you're building your own, use whatever method fits you.

1) From the viewpoint of a novice programmer, using team stats is really easy. There are a dozen different websites with consolidated, uniform, and sortable information. www.nfl.com and www.espn.com for example. Once you've acquired the data, you can easily manipulate it into the form that works for your program. The team stats can be incorporated into the simulation from a single web page. Grabbing an individual's stats takes a little more effort and problem solving. The difficulty lies in the automation of the process. Getting the program to find each team's website then find the player specific data you're looking for, can be tricky.

It doesn't sound much more difficult, but if you decide to use player statistics, you'll have to really work on your organizational skills. Remember, you'll have to retrieve and organize data from every position (with backups and second strings, etc.) from every team, i.e. DAL: QB Tony Romo, Brad Johnson, Richard Bartel; RB Marion Barber, Felix Jones, Tony Romo; WR .... .... .... You get the idea. All of this extra information that you use means you need a lot more computing power and a lot more patience.

2) Injuries? Substitutions? Trades? Here is where it may seem that simulation at the player level has an advantage over simulation at the team level. Surely when you account for individual changes, you'll get better accuracy, right? Well...maybe. Let's talk about team stats first. Team stats, at the very basic level do not take into account injuries, substitutions, trades or anything of the sort. Team simulations operate under the assumption that the team is a single, static object, which generates stats as the weeks go by, regardless of the players that make it up. From a programming standpoint, this makes things really easy because you don't have to worry about writing code to distinguish between different players and their respective stats, you just use a single set of statistics for the entire simulation.

From the player perspective: by accounting for major changes, you might be able to improve your accuracy. How do you reconcile in-game changes? The Cowboys consistently used Julius Jones and Marion Barber in the same game, so you have to figure out who runs each play in the simulation. The best method I can think of is finding how many attempts per game each RB has and proportion the plays in the simulation accordingly. When you consider every player for every team, this becomes pretty daunting.

Now let's assume there's an injury. If the Patriots have built up a set of passing statistics with Brady as the QB, those statistics are going to be pretty damn good, and they'll carry through to the next games. After 14 weeks, Brady gets injured and is out for the season. This is where a player simulation has its advantage; by using the great team stats that the Patriots had generated to simulate the subsequent games, you misrepresent the Patriots' skill as being greater than it actually is. Therefore, the next games will be inaccurate. When you use replace Brady with his backup, everything might work out. The tricky part is assigning averages or attributes to a player with no experience. You can figure out for yourself. Other provisions can be made when using team's stats if an injury occurs, like a assigning a general injury multiplier to the affected statistics. Trades can be treated in the same manner as injuries; both a player swap.

When deciding whether to write a simulation using team statistics or player statistics, the important factors to consider are: programming ability, patience, and free time. If you're an expert programmer with experience integrating web data with your respective programming language or if you've got a real drive to get the program done, consider using player stats. Otherwise, use team stats.

If you're wondering about how team accuracy compares with player accuracy, compare Black Box Sports and Accuscore. Black Box Sports' NFLSim uses team statistics for play-by-play simulations, Accuscore assigns attributes to individual players for their play-by-play simulation. This is the first full season for Black Box Sports, so we'll see who wins.

Welcome Back

Hey guys,

Football season's right around the corner, finally. It's almost time to have some fun with these predictions. Officially, the first week I'll simulate is week 2 (Sept. 14). I need data for the simulation and unfortunately preseason numbers don't work. Although, if anyone's curious, I suppose I can run a few sim's for sh!ts 'n giggles.

Write a comment with your fantasy matchup; specify the home team (or neutral) and let me know if you want me to use numbers from the end of the '07 season or preseason.

More updates will follow as the 2008 NFL season approaches.

p.s. I got a shiny new laptop that runs the program 4x as fast as my old crappy laptop (craptop). This means that I can run even more simulations for each game, making the predictions even more accurate!

Results through week 7

Yes, I'm only at week 7. I'm putting NFLSim away for a couple weeks to focus on basketball... nbablackbox.blogspot.com, where I'm 204-51 (80.0%), when picking the winner of the game. (no spread). 178-123(59.1%) with the spread. But just like football, when you're picking with that kind of accuracy, you can make money with the moneyline. Soccer is also in the works, and the backtest results are very, very promising; a sport where the only main bet is 'who will win'. Perfect. Don't think I've forgotten about baseball! Once enough stats have accumulated I'll try my hardest to do better than the 1000's of guys who've come before me. And you can bet that I will! (pun intended)

Since there are so many numbers, I'm going to skip the details and just post the main stats. If you want the details...I don't know why you would... just send me an email. This is for weeks 2-7, 87 games in all.

Win		Games	Wins	Win %
	50-59	41	30	73.2%
	60-69	22	17	77.3%
	70-79	17	10	58.8%
	80-89	7	6	85.7%
	90-100	0	0	#DIV/0!
	Total	87	63	72.4%
Spread		Games	Wins	Win %
	50-59	35	15	42.9%
	60-69	29	18	62.1%
	70-79	20	12	60.0%
	80-89	3	2	66.7%
	90-100	0	0	#DIV/0!
	Total	87	47	54.0%
Over		Games	Wins	Win %
	50-59	17	13	76.5%
	60-69	26	13	50.0%
	70-79	27	15	55.6%
	80-89	15	9	60.0%
	90-100	2	2	100.0%
	Total	87	52	59.8%

Thats pretty good. Win: 72.4%, Spread: 54%, O/U: 59.8%
Really, it was just one bad week that brought the numbers down, unfortunately bad weeks are unavoidable and if anyone tells you otherwise, they're trying to scam you.

That's it for now. You can find me at nbablackbox.blogspot.com, mlbblackbox.blogspot.com, and soccerblackbox.blogspot.com. The latter 2 are under construction- soccer will feature the main leagues from England, France, Germany, Italy, and Spain. It will be up sooner than MLB, probably sometime this week.


Good luck, all! Be responsible, don't be greedy, and don't get scammed.