Or, what to do with yourself now that the basketball season is over.
Now that the NBA season has ended and the Boston Celtics have been crowned champions, I find myself with little interest in pro sports. Baseball has long been my least favorite of the three major professional sports, even when my beloved Colorado Rockies came out of nowhere last year to claim the National League pennant. Their amazing win streak last year got me thinking, though - should we have seen this coming? Is there a way that we could have accurately predicted this?
Of course, the answer is yes. Just like I did for the NCAA tournament, I created a metric to gauge an MLB team's strength. And just like the SPI, I used scoring differential as the primary method of determining power. Like I argued before, scoring differential is a more reliable tool for determining a team's overall strength than wins and losses. A team winning a majority of its games by extremely slim margins isn't necessarily a good team. More likely, it's a lucky team having a lot of things go its way, which you'd expect to level off. A team with a high scoring margin - even over subpar teams - can be reasonably expected to be a quality team. Scoring differential also factors out two weaknesses that are hidden by a win-loss record - great offense and lousy defense, and vice versa. A team with great offense but no defense could score 12 runs a game, only to give up 11. That gives them a low scoring differential. Likewise, a team that has no offense but a fantastic defense maybe scores one run a game while giving up zero. Again, low scoring differential.
I compiled some data on the 30 MLB teams (home record, road record, and scoring differential) and created a simple formula. (I'm not telling you the coefficients I used. You want a formula, go make your own.) I then added 100 to each score to keep teams from going negative, and also because a score of 102.915 seems cooler than one of 2.915. ESPN.com keeps great records, so compiling all the data was pretty simple. And once I finished it, the results were, unsurprisingly, not what common wisdom would have told you.
The entire sports world has been crowing about how amazing the Tampa Bay Rays have been this year, and they're right. They've come off ten consecutive losing seasons to post the current best record in the league. That's pretty impressive. But I think it's wrong to crown them the best team in the league based on that alone. They've scored 70 more runs than they've allowed this year for an average margin of victory of 0.787 runs per game. That's pretty good - fifth in the league. But since four teams have a better differential, four teams find themselves above Tampa Bay in the standings - Philadelphia, Boston, and both Chicago teams. In fact, the Chicago Cubs have scored 36 more runs in their differential than Tampa, putting them easily in the top spot.
There's even more we can learn from this metric. Conventional wisdom holds that the American League is far better than the National League right now. A look at my metric (I hesitate to call this one the SPI as well, but I haven't got a better name for it) shows that seven of the top ten teams in the league are from the AL. Pretty compelling. We can also learn that there are some underachieving teams in the league, and some overachievers. By looking at the SPI, you can tell how many games a team should be expecting to win based on their scoring differential. (You can extrapolate that to see how many games they should win over an entire season, but that's not accurate, as it fails to take into account trades and injuries.) Based on that, we see teams like Atlanta (currently 43-48) sitting well beneath their ability. The SPI has them six games higher, with an expected win-loss record of 49-42 and cracking the top ten. (ESPN.com's Power Rankings have them currently at 21. At the same time, you have teams like the L.A. Angels, which ESPN lists at number 3. With a record of 52-36, they look like a strong contender. However, the SPI pegs them at 48-42, with a barely positive run differential of 24.
The difference, probably, is that the SPI measures a team's potential, while most commentators measure performance. And true, we ought to be concerned with what a team is actually doing rather than what they could be doing, but with half the season left, I think measuring a team's potential still has some use. And if you're complaining to yourself about my writing another sports statistics article, then too bad, because this is my blog and I can write whatever I want unless the editors fire me.
Showing posts with label SPI. Show all posts
Showing posts with label SPI. Show all posts
Wednesday, July 9, 2008
Sunday, March 23, 2008
SPI Update, 23 March
An exciting weekend, but not for this writer.
Weekends like this one are exciting to watch. Underdogs come up with big upsets, powerhouses are shocked, and endless buzz is created. It's a lot of fun. It's a little less fun, however, when you've trumpeted up your foolproof prediction method and get to watch it all fall to pieces. Let's review:
West Virginia 73, Duke 67. Duke was rated a full two and a half points higher in the SPI - high enough to earn them a spot in the finals in my bracket. West Virginia ruined my life again this year, knocking Duke out in the second round. They knocked off UConn a few years back in the second round as a 7 seed. I'm not too keen on those Mountaineers.
Stanford 82, Marquette 81. One point the other way and we aren't having this discussion. I went out of my way to talk about how overrated Stanford is and how underrated Marquette is. So much for that.
Realistically, those are the only two big upsets I had. I have 12 of the 16 remaining teams correct so far (only wrong on Washington State, Villanova, Stanford, and West Virginia), but the teams that I lost had a big impact. It's rough. It just goes to show you that there isn't a foolproof way to predict something as inherently chaotic as the NCAA basketball tournament. I'm still doing better than the wife (35-13 to her 33-15), but I'd be surprised if she doesn't end up outperforming me. Next year, when you see my article come up about my failsafe predictions for March Madness, cut straight to the chase and ask who my wife has winning it all. (She picked Tennessee, incidentally.)
AP Photo - Chuck Burton
Weekends like this one are exciting to watch. Underdogs come up with big upsets, powerhouses are shocked, and endless buzz is created. It's a lot of fun. It's a little less fun, however, when you've trumpeted up your foolproof prediction method and get to watch it all fall to pieces. Let's review:
West Virginia 73, Duke 67. Duke was rated a full two and a half points higher in the SPI - high enough to earn them a spot in the finals in my bracket. West Virginia ruined my life again this year, knocking Duke out in the second round. They knocked off UConn a few years back in the second round as a 7 seed. I'm not too keen on those Mountaineers.
Stanford 82, Marquette 81. One point the other way and we aren't having this discussion. I went out of my way to talk about how overrated Stanford is and how underrated Marquette is. So much for that.
Realistically, those are the only two big upsets I had. I have 12 of the 16 remaining teams correct so far (only wrong on Washington State, Villanova, Stanford, and West Virginia), but the teams that I lost had a big impact. It's rough. It just goes to show you that there isn't a foolproof way to predict something as inherently chaotic as the NCAA basketball tournament. I'm still doing better than the wife (35-13 to her 33-15), but I'd be surprised if she doesn't end up outperforming me. Next year, when you see my article come up about my failsafe predictions for March Madness, cut straight to the chase and ask who my wife has winning it all. (She picked Tennessee, incidentally.)
AP Photo - Chuck Burton
Friday, March 21, 2008
SPI Update, 21 March
Lots of upsets, and big ones, too.
This is the downside of going public with a bracket you think is really good - when it takes a nose dive, everyone finds out. There were four big upsets today, and my metric only got two of them right. And even that's debatable. Let's look at the numbers.
Western Kentucky 101, Drake 99. The SPI had #14 Western Kentucky (112.4489) narrowly beating #16 Drake (112.0300). It wasn't an easy choice. Still, it's hard to argue with a scoring differential of 14.8 over your last ten games, even if they come against Sun Belt competition. I had complete faith in the SPI for this one. (That means I spent the entire overtime glued to my computer, watching the score update every few seconds and screaming when Drake pulled ahead with seconds to play.)
San Diego 70, Connecticut 69. This one floored me. San Diego is one of the worst teams to make the field (104.4046, #59 SPI) and UConn is, while not top-tier, pretty solid (110.1566, #24 SPI). I thought this one was a no-brainer. And somehow, San Diego kept it close the whole time and pulled out a squeaker in overtime. Just goes to show you that no statistics-driven metric is perfect.
Siena 83, Vanderbilt 62. I liked Siena in this matchup and was so confident I didn't expect anything other than a Siena blowout. I got it, but a quick look at the SPI chart surprised me. Vanderbilt was ranked considerably higher than Siena in pretty much every category. Look at the numbers:
SPI Vanderbilt 108.0898 Siena 106.6667
SOS Vanderbilt .5644 Siena .5143
Scoring differential Vanderbilt 7.2 Siena 5.9
Not really sure why I was so confident there, but I picked the upset and got it. Weird.
Villanova 75, Clemson 69. Here's one where I was just dead wrong. Seriously. How could I have seen #25 Clemson (109.8635) losing to #58 Villanova (104.6078)? The mind boggles. I just don't get this one.
Overall, the SPI performed significantly worse today, only going 9-7 for a total of 24-8. Not a good day. For comparison, my wife's bracket is 25-9. Also, she wishes to inform the loyal readers of the Worb that her bracket was not solely determined by name recognition, but by an elaborate process consisting of looking at both the team's seed and their win-loss record. I thought you should know out of duty to accuracy (which means I had to tell you on penalty of no sex until I'm 75).
This is the downside of going public with a bracket you think is really good - when it takes a nose dive, everyone finds out. There were four big upsets today, and my metric only got two of them right. And even that's debatable. Let's look at the numbers.
Western Kentucky 101, Drake 99. The SPI had #14 Western Kentucky (112.4489) narrowly beating #16 Drake (112.0300). It wasn't an easy choice. Still, it's hard to argue with a scoring differential of 14.8 over your last ten games, even if they come against Sun Belt competition. I had complete faith in the SPI for this one. (That means I spent the entire overtime glued to my computer, watching the score update every few seconds and screaming when Drake pulled ahead with seconds to play.)
San Diego 70, Connecticut 69. This one floored me. San Diego is one of the worst teams to make the field (104.4046, #59 SPI) and UConn is, while not top-tier, pretty solid (110.1566, #24 SPI). I thought this one was a no-brainer. And somehow, San Diego kept it close the whole time and pulled out a squeaker in overtime. Just goes to show you that no statistics-driven metric is perfect.
Siena 83, Vanderbilt 62. I liked Siena in this matchup and was so confident I didn't expect anything other than a Siena blowout. I got it, but a quick look at the SPI chart surprised me. Vanderbilt was ranked considerably higher than Siena in pretty much every category. Look at the numbers:
SPI Vanderbilt 108.0898 Siena 106.6667
SOS Vanderbilt .5644 Siena .5143
Scoring differential Vanderbilt 7.2 Siena 5.9
Not really sure why I was so confident there, but I picked the upset and got it. Weird.
Villanova 75, Clemson 69. Here's one where I was just dead wrong. Seriously. How could I have seen #25 Clemson (109.8635) losing to #58 Villanova (104.6078)? The mind boggles. I just don't get this one.
Overall, the SPI performed significantly worse today, only going 9-7 for a total of 24-8. Not a good day. For comparison, my wife's bracket is 25-9. Also, she wishes to inform the loyal readers of the Worb that her bracket was not solely determined by name recognition, but by an elaborate process consisting of looking at both the team's seed and their win-loss record. I thought you should know out of duty to accuracy (which means I had to tell you on penalty of no sex until I'm 75).
Thursday, March 20, 2008
SPI Update, 20 March
Only one significant upset on the first day of the tournament.
There were some nail-biters, but my bracket is nearly perfect after day one of play. Here's a rundown of the three misfires I had:
UNLV 71, Kent State 58. The SPI had this one right, actually. #41 UNLV rates 107.2224 compared to #43 Kent State's 106.7044. When the scores are that close, though, I look to the last ten games, and Kent State had a much higher scoring differential. I yielded, and I picked the upset. I paid for it, too.
Pittsburgh 82, Oral Roberts 63. Same problem here. #37 Pittsburgh rates 107.7219 to #39 Oral Roberts' 107.3852. That's even closer than the first matchup. Oral Roberts had nearly eight points higher in the scoring differential category, though, so I went with the big upset. Now I just have to hope Pitt doesn't go on a huge run. They shouldn't, though, since Michigan State (their next opponent) has an SPI of over 109.
Texas A&M 67, BYU 62. Anyone watching this game knows that it was close. #17 BYU had a much better SPI (111.7292 compared to 109.0498), but I forgot to apply the smell test here. BYU plays in the Mountain West Conference. Their biggest win was over Louisville, yes, but it was a team riddled with injuries. I should have known better. It's just hard to pick against your alma mater.
So through the first day, the SPI is 15-1. My bracket is 13-3, but that's just because I'm an idiot and ignored my own system. For the record, my wife, who more of less filled out her bracket on name recognition (I love you, honey), is standing at 14-2, only missing BYU-Texas A&M and USC-Kansas State. That's a little humbling.
There were some nail-biters, but my bracket is nearly perfect after day one of play. Here's a rundown of the three misfires I had:
UNLV 71, Kent State 58. The SPI had this one right, actually. #41 UNLV rates 107.2224 compared to #43 Kent State's 106.7044. When the scores are that close, though, I look to the last ten games, and Kent State had a much higher scoring differential. I yielded, and I picked the upset. I paid for it, too.
Pittsburgh 82, Oral Roberts 63. Same problem here. #37 Pittsburgh rates 107.7219 to #39 Oral Roberts' 107.3852. That's even closer than the first matchup. Oral Roberts had nearly eight points higher in the scoring differential category, though, so I went with the big upset. Now I just have to hope Pitt doesn't go on a huge run. They shouldn't, though, since Michigan State (their next opponent) has an SPI of over 109.
Texas A&M 67, BYU 62. Anyone watching this game knows that it was close. #17 BYU had a much better SPI (111.7292 compared to 109.0498), but I forgot to apply the smell test here. BYU plays in the Mountain West Conference. Their biggest win was over Louisville, yes, but it was a team riddled with injuries. I should have known better. It's just hard to pick against your alma mater.
So through the first day, the SPI is 15-1. My bracket is 13-3, but that's just because I'm an idiot and ignored my own system. For the record, my wife, who more of less filled out her bracket on name recognition (I love you, honey), is standing at 14-2, only missing BYU-Texas A&M and USC-Kansas State. That's a little humbling.
Tuesday, March 18, 2008
SPI Update, 18 March
Mount St. Mary's 69, Coppin State 60.
I promised regular updates, and I'm here to provide the first. The play-in game was tonight, and on Monday I said that I expected Mount St. Mary's to win over Coppin State. The score is in, and the Mountaineers won by nine points. It was pretty close for most of the contest, but Mount St. Mary's pulled away in the clutch. Aficionados of the SPI will remember that the Mountaineers have a significantly higher rating than the Eagles. Mount St. Mary's boasts an SPI rating of 103.8015 compared to Coppin State's 97.3570. A difference of six and a half points is not to be ignored. Thus far, things are looking good.
For the record, Mount St. Mary's next opponent, North Carolina, has an SPI rating of 117.2178. If a six and a half point difference is huge, then a thirteen and a half point difference is even more so. Stay tuned.
I promised regular updates, and I'm here to provide the first. The play-in game was tonight, and on Monday I said that I expected Mount St. Mary's to win over Coppin State. The score is in, and the Mountaineers won by nine points. It was pretty close for most of the contest, but Mount St. Mary's pulled away in the clutch. Aficionados of the SPI will remember that the Mountaineers have a significantly higher rating than the Eagles. Mount St. Mary's boasts an SPI rating of 103.8015 compared to Coppin State's 97.3570. A difference of six and a half points is not to be ignored. Thus far, things are looking good.
For the record, Mount St. Mary's next opponent, North Carolina, has an SPI rating of 117.2178. If a six and a half point difference is huge, then a thirteen and a half point difference is even more so. Stay tuned.
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