Angels Take Red Sox For 5-Game Ride In Divisional Series; Fall Short

Major League Baseball Playoff Prediction

The Angels finally make it into the Divisional Series, beating out Oakland by a game for the West title. Yes, we know that Los Angeles's record has shown their strength for quite a while now, but the Athletics only this past weekend fell below the level of the Angels. Even though the A's series win against Florida was impressive, the Angels were even more so as they swept Philly in Pennsylvania.

By pure run differential, Oakland is by far superior at 1.226 runs scored per 1 run allowed to Los Angeles at 1.043 runs scored. The basic Pythagorean final record prediction places the A's at 93 wins (current record of .547 plus .592 over the remaining games) and the Angels at 91 wins (.605 now plus .519 the rest of the way), giving Oakland the AL West championship. However - and this is a big however - Oakland's play against strength of schedule and just plain win-loss record does not bear out the prediction that they can win 93 games in 2008. Baseball Playoffs Now employs a "gravitate towards the mean" filter to punish teams who have excellent run differentials but mediocre win-loss records, and to reward teams who have poor differentials but mediocre records.

Adding each team's propensity to actually win games - and not just score runs - Oakland loses 4 wins and Los Angeles loses 1 win, placing the A's at 89 wins and the Angels at 90. Hence, Los Angeles wins the division and the right to lose to Boston in the first round of the playoffs.

American League Divisional Series
No. 1 seed BOS over no. 3 seed LAA in 5 games.
No. 2 seed CHW over no. 4 seed TAM in 5 games.

National League Divisional Series
No. 1 seed CHC over no. 3 seed ARI in 3 games.
No. 2 seed PHI over no. 4 seed STL in 5 games.

American League Championship Series
No. 1 seed BOS over no. 2 seed CHW in 6 games.

National League Championship Series
No. 1 seed CHC over no. 2 seed PHI in 5 games.

*** World Series Projection***
*** No. 1 seed BOS over no. 1 seed CHC in 7 games. ***

New Playoff Pace Rankings -- Current Odds For October

To determine division championship pace, we project the final records of every team in baseball, then figure out who's in front and how far behind every other team is. The same is true for the wild card predictions, just with the projected division leaders removed.

These numbers do not mean that Boston, Chicago WS, and Oakland have a 100% chance of making the playoffs. Rather, the 1.0000 ratings mean that they hold the strongest projected records (and therefore best predicted chance) and everyone else is measured relative to them.

AL Division Championship Pace
1 - BOS - 1.0000 (98 - 64)
1 - CHW - 1.0000 (93 - 69)
1 - OAK - 1.0000 (89 - 73)
4 - LAA - 0.9029 (86 - 76)
5 - TEX - 0.6967 (80 - 82)
6 - TAM - 0.5921 (91 - 71)
7 - DET - 0.4128 (80 - 82)
8 - CLE - 0.3897 (80 - 82)
9 - MIN - 0.3766 (80 - 82)
10 - NYY - 0.3163 (86 - 76)
11 - TOR - 0.0275 (81 - 81)
12 - SEA - 0.0000 (58 - 104)
12 - KAN - 0.0000 (72 - 90)
12 - BAL - 0.0000 (80 - 82)


AL Wild Card Pace
1 - TAM - 1.0000 (91 - 71)
2 - LAA - 0.8522 (86 - 76)
3 - NYY - 0.8473 (86 - 76)
4 - TOR - 0.6873 (81 - 81)
5 - DET - 0.6760 (80 - 82)
6 - BAL - 0.6721 (80 - 82)
7 - CLE - 0.6609 (80 - 82)
8 - TEX - 0.6576 (80 - 82)
9 - MIN - 0.6523 (80 - 82)
10 - KAN - 0.4056 (72 - 90)
11 - SEA - 0.0000 (58 - 104)


NL Division Championship Pace
1 - PHI - 1.0000 (91 - 71)
1 - CHC - 1.0000 (98 - 64)
1 - ARI - 1.0000 (83 - 79)
4 - ATL - 0.7696 (84 - 78)
5 - FLA - 0.7400 (83 - 79)
6 - LAD - 0.7047 (79 - 83)
7 - NYM - 0.6523 (81 - 81)
8 - STL - 0.4673 (85 - 77)
9 - MIL - 0.3341 (82 - 80)
10 - SFO - 0.1759 (71 - 91)
11 - PIT - 0.1084 (77 - 85)
12 - COL - 0.0754 (69 - 93)
13 - HOU - 0.0297 (75 - 87)
14 - SDG - 0.0000 (68 - 94)
14 - CIN - 0.0000 (74 - 88)
14 - WAS - 0.0000 (62 - 100)


NL Wild Card Pace
1 - STL - 1.0000 (85 - 77)
2 - ATL - 0.9516 (84 - 78)
3 - FLA - 0.9149 (83 - 79)
4 - MIL - 0.8596 (82 - 80)
5 - NYM - 0.8066 (81 - 81)
6 - LAD - 0.7102 (79 - 83)
7 - PIT - 0.6218 (77 - 85)
8 - HOU - 0.5388 (75 - 87)
9 - CIN - 0.5075 (74 - 88)
10 - SFO - 0.3631 (71 - 91)
11 - COL - 0.2971 (69 - 93)
12 - SDG - 0.2476 (68 - 94)
13 - WAS - 0.0000 (62 - 100)

Yankees, Indians Teams To Watch -- Brewers Slipping

Teams on the Rise
1 NYY
2 CLE

Teams on the Fall
1 MIL

The Teams to Watch ranking is something of an über-metric within Baseball Playoffs Now. First we strip out all teams in 1st, 5th, and 6th places in the division. There is no reason that a 1st place team should be a team on the rise, since everyone already knows they are pretty good. Likewise, there is no reason that a 5th or 6th place team should be a team on the fall, since it's common knowledge that club is having a rough season.

For the same reasons, we strip out the top 8 teams by win-loss percentage for teams on the rise, and the bottom 8 teams by WL% for teams on the fall.

There are four important indicators in Teams to Watch that signal a team's direction: run differential, overall ranking, overall ranking versus win-loss percentage, and trends over the past 10 games. The first two make sure of a team's quality, the third - also known as overrated/underrated teams - is sort of a hidden measure of how a team is doing against public perception, and the fourth keeps this formula current.

Teams on the Rise must have above-average numbers in every single one of those measures, and Teams on the Fall must have below-average numbers in all of those indicators. Only one to five teams qualify for each label at any one time, and we present the top three to you.

The Milwaukee Brewers are 12th in win-loss percentage with a 36-33 record (.522), earning third place in the second-toughest division in baseball. Last month the Brew Crew stunk up the joint and plummeted to last in the division, but a recent surge put them right back in the running. After an interleague fight with old AL Central foe Minnesota, however, Milwaukee is beginning to need life support. Their vital signs:

- 0.957 runs scored for every 1 allowed
- #15 overall ranking, with a rating of 49.6% (relative to the Cubs at 100% and the Mariners at 0%)
- an overrated team, with their 12th-place win-loss percentage too good for their 15th-place ranking
- below-average record over the last 10 games (losing a series at home to the Twins and only going 3-3 against Colorado and Houston, two teams in fifth place)

On the other hand, the Yankees are 10th in win-loss percentage (37-33, .529) and 3rd in the AL East, with promising indicators: 1.055 runs scored for every 1 allowed, #8 overall (combined with a 10th-place win-loss percentage to make them an underrated team), and excellent 7-3 last 10 games (second-best in baseball).

Likewise, the Indians are 20th in WL% (33-37, .471) and 3rd in the AL Central. They score 1.076 runs for every 1 allowed, are #13 overall (much better than their win-loss percentage ranking), and are 8th in baseball over the last 10 games (6-4, with 2-2 away and 4-2 home).

It's also worth noting that the Yankees and Indians are in the top half of the strength of schedule rankings. Since the overall ranking indicator takes into account an infinite strength of schedule, the quality of opponents is a somewhat-large factor in the Teams to Watch measure.

Rays, Jays Fight Toughest Schedules In Baseball

Strength of schedule is calculated by adding wins and losses of each team's opponents, with allowances for home field advantage (currently 14.32%) and history (recent games weighted a bit more than earlier games). Toronto, Baltimore, Kansas City, Seattle, and Cincinnati are around the bottom of their divisions, so it's easy to see why they have tough schedules. But other teams are not so obvious. Tampa Bay is 2nd in the AL East yet has played the toughest schedule in baseball. Not only is the East is the top division by far, but the Rays have played a brutal out-of-division schedule including the Angels, White Sox, and Cardinals. Schedule is an important reason that the Rays are #4 overall and the Blue Jays are #9 overall, even though they are second and last in their division, respectively.

Major League Baseball Strength of Schedule Rankings
1 - TAM
2 - TOR
3 - BAL
4 - SEA
5 - KAN
6 - MIN
7 - CIN
8 - OAK
9 - BOS
10 - NYY
11 - DET
12 - CLE
13 - PIT
14 - LAA
15 - CHW
16 - TEX
17 - HOU
18 - WAS
19 - MIL
20 - COL
21 - ATL
22 - NYM
23 - LAD
24 - SFO
25 - FLA
26 - SDG
27 - PHI
28 - CHC
29 - STL
30 - ARI

New Final Record Prediction Method

Baseball Playoffs Now is all about good power ratings, and how those ratings can predict future performance. We've been using the Pythagorean method to predict future records (runs scored / (runs scored + runs allowed)) and it's been working well. But as a Phillies blog pointed out, a team's win pace has "absolutely nothing" to do with RS/RA. The win pace is simply the team's current winning percentage. Using runs scored and runs allowed is a good way to differentiate teams with similar records, and historically, real-world team records approach their Pythagorean records.

But using pure run differentials is no longer our method, since it ignores a full half of the power ratings. Our ratings are equal parts of wins/losses against infinite strength of schedule and runs scored/allowed against infinite strength of schedule. Therefore, our Final Record Predictions will reflect both of them.

The records below began as Pythagorean records, and you can see the pure Pyth predictions at today's earlier post. After seeing where run differentials place a team, however, we add or subtract games based on a team's simple propensity to win or lose games (ignoring all runs). So Boston stays at 99 wins since it ranks first in baseball with its pure win/loss record against its schedule. But Philadelphia falls 6 games, from 99 wins to 93 wins, because of its 68% W/L rating compared to Boston.

MLB Final Record Predictions
1 - CHC : 103 - 59
2 - BOS : 99 - 63
3 - PHI : 93 - 69
4 - CHW : 90 - 72
5 - TAM : 90 - 72
6 - OAK : 89 - 73
7 - STL : 88 - 74
8 - LAA : 87 - 75
9 - NYY : 84 - 78
10 - ARI : 83 - 79
11 - ATL : 83 - 79
12 - TOR : 82 - 80
13 - FLA : 82 - 80
14 - CLE : 82 - 80
15 - MIL : 81 - 81
16 - NYM : 81 - 81
17 - TEX : 80 - 82
18 - DET : 80 - 82
19 - BAL : 79 - 83
20 - PIT : 79 - 83
21 - MIN : 78 - 84
22 - LAD : 77 - 85
23 - CIN : 76 - 86
24 - HOU : 76 - 86
25 - SFO : 72 - 90
26 - SDG : 71 - 91
27 - KAN : 69 - 93
28 - COL : 68 - 94
29 - WAS : 65 - 97
30 - SEA : 60 - 102

Cubs Win World Series in 7; Playoff Prediction Methods Explained

Major League Baseball Playoff Prediction

I'd like to shed some light on how Baseball Playoffs Now predicts the postseason. Our final record predictions generate division placements and the wild card team, based on a history-weighted pythagorean method. Once we know the playoff teams, we turn to a completely different statistic to figure out who are the better teams.

Our Power Rankings are compiled using both pure wins/losses and runs scored/allowed in two separate algorithms, both rated against an infinite strength of schedule matrix. But run differential is the best single predictor of upcoming performance, so Baseball Playoffs Now weights that factor much more heavily when creating a special stat called Playoff Ratings. The only use for this statistic is picking winners in our playoff predictions; we don't publish it as Power Rankings because it is skewed too far away from wins and losses.

Using Eric Seidman's Home Field Advantage article to determine HFA, we give a (small) home field advantage to the proper teams' ratings. The winner of the series is therefore simply the team with the higher rating.

Mathematics, backed up by Seidman's data, also returns the probabilities that a series will extend to 3, 4, or 5 games (in the case of the Divisional Series) or 4, 5, 6, or 7 games (in the case of the League Championship and World Series):

The math: (coin flip for winner [or use historical data, but there is only a very small difference] ^ number of games in series) x number of possible outcomes in which the series lasts that long

Divisional Series:
3 games = 0.5^3 x 2 = 25%
4 games = 0.5^4 x 4 = 25%
5 games = 0.5^5 x 16 = 50%

League/World Series:
4 games = 0.5^4 x 2 = 12.5%
5 games = 0.5^5 x 8 = 25%
6 games = 0.5^6 x 20 = 31.25%
7 games = 0.5^7 x 40 = 31.25%

Using these numbers, we use some fuzzy math to generate the least-scientific prediction of this entire site: series lengths. We figure out the greatest difference in Playoff Rating between teams in the playoffs, then figure out about where the two teams in each series lie in that range. Plugging that percentage into the probabilities above, we can approximate series lengths.

And voilà!

American League Divisional Series
No. 1 seed CHW over no. 4 seed TAM in 5 games.
No. 2 seed BOS over no. 3 seed OAK in 5 games.

National League Divisional Series
No. 1 seed CHC over no. 3 seed ARI in 3 games.
No. 2 seed PHI over no. 4 seed STL in 4 games.

American League Championship Series
No. 1 seed CHW over no. 2 seed BOS in 6 games.

National League Championship Series
No. 1 seed CHC over no. 2 seed PHI in 5 games.

*** World Series ***
*** No. 1 seed CHC over no. 1 seed CHW in 7 games. ***

Symptom: Uneven Play; Disease: Unbalanced Club

Our illuminating new Balance Ranking measures how much teams rely on certain parts of the season. If homestands or away series are the primary cause of a team's record, they fall in this ranking. In the same manner, if divisional play or out-of-division play figures too highly in what makes a squad tick, then we penalize them. The highest-rated teams are those who have perfect balance between home and away records, and in-division and out-of-division records.

The Balance Rankings are no measure of success, as the Kansas City Royals (#1 in the list) can tell you. Yet playing the #2 White Sox or #3 Athletics will become much more scary, knowing that they can win anytime, anywhere. On the other hand, a non AL-Central team playing Minnesota in the Twin Cities can take heart.

Below we detail the symptoms of each team's "unbalance disease." And kudos to the Royals, who apparently figured out a way to lose to everyone everywhere, making them the most balanced team today.

Balance Rankings
1 - KAN
2 - CHW
3 - OAK
4 - SEA
5 - HOU
6 - SDG
7 - CLE - too dependent on homestands
8 - TOR
9 - LAD - too dependent on own division
10 - ARI - too dependent on own division
11 - COL
12 - PIT - not good enough at home
13 - BAL - not good enough in own division
14 - PHI - too dependent on homestands
15 - NYY - not good enough in own division
16 - MIL - too dependent on homestands - too dependent on own division
17 - NYM - not good enough in own division
18 - TEX - too dependent on own division
19 - TAM - too dependent on homestands - too dependent on own division
20 - CIN - too dependent on homestands
21 - LAA - not good enough at home
22 - ATL - too dependent on homestands
23 - DET - not good enough in own division
24 - FLA - not good enough at home - too dependent on own division
25 - SFO - not good enough at home - too dependent on own division
26 - CHC - too dependent on homestands - not good enough in own division
27 - BOS - too dependent on homestands
28 - WAS - not good enough at home - not good enough in own division
29 - STL - not good enough at home - not good enough in own division
30 - MIN - not good enough at home - too dependent on own division

Methods and Statistics Explained: Part II

Part II: Computer Modeling

There is little more controversial in sports than the proper method to determine strength of schedule. Luckily, most leagues use pure wins and losses to determine entrance into playoffs and the seeds therein. In college sports, the sheer number of teams and wide range of schedule difficulties prohibit the win-loss percentage from being the sole criterion to determine the best teams.

Major League Baseball proper won't need strength of schedule any time soon. But for those of us concerned with predicting future performance, especially playoff performance, knowing a team's strength against its schedule is of paramount importance, since it differentiates teams so clearly.

A key concept to understand is retrodictive ratings versus predictive ratings. Retrodictive ratings only care about wins and losses, and pretty accurately show which teams have won the most based on the difficulty of their schedule (which is also figured out based only on wins and losses).

Predictive ratings, on the other hand, care only about runs scored and allowed. This run ratio is an accurate measure of how well a team will perform in the future, and ignores whether a team actually won the ballgame. A team's difficulty of schedule is calculated using run ratios of opponents and not wins/losses.

It's clear that both of these methods have a good deal of value for rating teams, and that neither should be used exclusively. Statisticians like Jeff Sagarin synthesize retrodiction and prediction to create a meaningful halfway-point between past and future performance, and Baseball Playoffs Now follows this example.

Rating Method

The algorithm for rating a team is very simple:

Home Team Rating + Home Field Advantage - Away Team Rating = average difference between the two teams over the entire season

The difficulty, of course, is that teams perform differently from one day to the next, and from one opponent to the next. There is no perfect rating for any team that explains exactly what happened during any given ballgame. The Padres can beat the Dodgers by 5 today and lose by 3 tomorrow, while the Dodgers beat the Giants twice by 7, and the Giants beat the Padres by 5 and lose by 2.

There is an optimal point somewhere between all of the scores that describes the average performance of San Diego, San Francisco, and Los Angeles against each other. The computer's goal is to find that point and minimize the error. Baseball Playoffs Now's algorithm constantly adjusts each team's rating (which then ripples out throughout Major League Baseball, since every team is connected to every other team through a formula for every game) and finds the point at which there is the least MLB-wide error. At that point, we have the optimal ratings for today.

Running this system twice (once with run ratios, once with wins/losses only), we create two ratings for each team: predictive and retrodictive. Synthesizing them creates an important part of Baseball Playoffs Now's overall rating for each team. You can see below the difference between today's predictive and retrodictive ratings for each team. I have starred teams with 8 or more rank differences between the two ratings.

Computer Models (predictive = run ratios, retrodictive = wins/losses)
ARI - predictive # 8 - retrodictive # 13
ATL - predictive # 6 - retrodictive # 14 *****
BAL - predictive # 18 - retrodictive # 11
BOS - predictive # 7 - retrodictive # 2
CHC - predictive # 1 - retrodictive # 7
CHW - predictive # 3 - retrodictive # 4
CIN - predictive # 24 - retrodictive # 22
CLE - predictive # 11 - retrodictive # 23 *****
COL - predictive # 28 - retrodictive # 28
DET - predictive # 20 - retrodictive # 26
FLA - predictive # 17 - retrodictive # 9 *****
HOU - predictive # 14 - retrodictive # 8
KAN - predictive # 26 - retrodictive # 24
LAA - predictive # 10 - retrodictive # 3
LAD - predictive # 16 - retrodictive # 19
MIL - predictive # 23 - retrodictive # 18
MIN - predictive # 22 - retrodictive # 16
NYM - predictive # 13 - retrodictive # 21 *****
NYY - predictive # 15 - retrodictive # 17
OAK - predictive # 2 - retrodictive # 6
PHI - predictive # 4 - retrodictive # 12 *****
PIT - predictive # 19 - retrodictive # 20
SDG - predictive # 30 - retrodictive # 30
SEA - predictive # 29 - retrodictive # 29
SFO - predictive # 27 - retrodictive # 27
STL - predictive # 12 - retrodictive # 10
TAM - predictive # 5 - retrodictive # 1
TEX - predictive # 21 - retrodictive # 15
TOR - predictive # 9 - retrodictive # 5
WAS - predictive # 25 - retrodictive # 25

Chicago Cubs Win 103 Games in 2008

To predict the final record of all baseball teams, we use a modified Smyth/Patriot method to find the most probable number of wins in the remainder of the season based on previous runs scored - runs allowed ratios.

That is, the Milwaukee Brewers currently have a .471 win-loss record over 51 games (or 31.48% of the season). Their history-adjusted run ratio is 0.887 runs scored for every 1 run allowed (223.578 runs scored to 251.930 runs allowed), to which Smyth/Patriot returns an expected future win/loss record of .444.

51 prior games of .471 baseball plus 111 future games of .444 baseball equals a final record of .452, or 73 wins out of 162 ball games.

This is one of the few not completely homegrown statistics on Baseball Playoffs Now, and this site is indebted to Bill James and the later Smyth/Patriot adjustments for their work.

MLB Final Record Predictions
1 - CHC - 103 - 59
2 - ARI - 98 - 64
3 - OAK - 95 - 67
4 - ATL - 95 - 67
5 - TAM - 94 - 68
6 - PHI - 94 - 68
7 - CHW - 94 - 68
8 - BOS - 93 - 69
9 - STL - 91 - 71
10 - FLA - 90 - 72
11 - LAA - 88 - 74
12 - TOR - 86 - 76
13 - LAD - 85 - 77
14 - HOU - 85 - 77
15 - CLE - 81 - 81
16 - NYY - 79 - 83
17 - NYM - 79 - 83
18 - BAL - 79 - 83
19 - TEX - 78 - 84
20 - MIN - 77 - 85
21 - PIT - 75 - 87
22 - DET - 73 - 89
23 - MIL - 73 - 89
24 - CIN - 72 - 90
25 - WAS - 67 - 95
26 - SFO - 63 - 99
27 - KAN - 63 - 99
28 - COL - 63 - 99
29 - SEA - 59 - 103
30 - SDG - 58 - 104

Methods and Statistics Explained

Baseball Playoffs Now's Methods and Statistics series explains how we get the results we do - and especially why our mathematical interpretations differ from public stats posted on sites like ESPN's MLB standings or stats pages.

Part I: History

History - or the concept of "fading memory" in stats - is used in almost every application on this site. Baseball Playoffs Now firmly believes that August play is more important than April play when predicting playoff contenders or outcomes. Most commentators deal with a team's Last 10 Games because that is an easy statistic to track, and we offer standings over that same period as a comparative value. However, unlike those commentators, we do not see a team's record broken into two categories: Last 10 Games (most important) and Ancient History (least important).

Baseball Playoffs Now has created a unique algorithm to rate each game in the season with a historical value, a coefficient which is included in most every formula we use. This historical coefficient is quite simple: if today's game were the Brewers' 11th game of the season, then game 6 - the game directly in the middle of the season so far - would have a value of 1.0 (that is, no change whatsoever). Game 1 would have a value around 0.97 and Game 11 would have a value around 1.03. These bottom and top values (0.97 and 1.03) begin to separate as more games are played.

After yesterday's games, the season so far for all teams has lasted 687 games, an average of 45.8 games per team. That means that Game 1 of this season is rated 85.8% as important as the middle game and Game 46 of this season (from yesterday) is rated 114.2% as important as the middle game.

Now, history becomes important when we look at statistics like runs scored and runs allowed. The Yankees have scored 181 runs and allowed 209 runs to score this season. But multiplying each of their game scores by that game's history value allows us to see the Yankee trend: their historically-weighted run ratio is 178.6 runs scored to 209.2 runs allowed. The interpretation is clear: New York has been doing worse recently than if you looked at their season overall. And this realization that New York is on a slide must be taken into account when making predictions and rankings.

Our Last 10 Games stat also bears the marks of history; we do not weight the last 10 games equally but rather give them their normal history weight on the same sliding scale with every other game. The absolute best way to look at a team's recent play is to look at the season as a whole, with every game weighted for its historical importance. But in order to make comparisons with the well-known Last 10 stat, we also offer a look at a team's season cut off at 10 games and rank the teams on that measure as well.

So if you're checking our run ratios and wondering why we just quoted Atlanta at 1.310 runs scored for every 1 allowed (when their 217 runs scored and 166 runs allowed clearly shows a ratio of 1.307), it means that Atlanta's excellent recent play has bumped up their weighted run ratio by a slight amount. It doesn't sound like a lot, but the difference between the #4 Red Sox at 1.195 and #5 White Sox at 1.190 is only 0.005 runs. Statistics calculated over many low-scoring games show very small differences between teams; this is why a value for history is so important, because it clearly illuminates the better team (by one measure) between nominally equal clubs.