# Archive for the 'Pro-Football-Reference.com' Category

## SRS Calculation Details

3rd March 2015

One of the more common subjects for queries we receive at Sports-Reference is our SRS (Simple Rating System) figures. For some background, the first of our sites to add SRS was Pro-Football-Reference, when Doug Drinen added it to the site in 2006 and provided this excellent primer. The important thing to know is that SRS is a rating that takes into account average point differential and strength of schedule. For instance, the 2006-07 Spurs won games by an average of 8.43 points per game and played a schedule with opponents that were 0.08 points worse than average, giving them an SRS of 8.35. This means they were 8.35 points better than an average team. An average team would have an SRS of 0.0. The calculation can be complicated, but the premise is simple and it produces easily interpreted results.

However, there are some variations in the way we calculate SRS across our various sites. We'll break down these differences below.

Pro-Football-Reference.com SRS: PFR's SRS is unique in that a home-field advantage is included as a part of the calculation because of the short schedule compared to the other sports (we don't want a team to look relatively weak at the halfway point because they've only played 3 of their first 8 at home, for instance). This HFA fluctuates yearly based on game results, but it is generally somewhere between 2 and 3 points (2006 being an outlier, as you'll see). Below is a look at the HFA numbers we have used since 2001. If you'd like to calculate these HFAs yourself, just sum up every team's home point differential and then divide by the total number of games played across the league that season. This data can easily be found in the Play Index for each season:

• 2001: 2.0081
• 2002: 2.2461
• 2003: 3.5547
• 2004: 2.5078
• 2005: 3.6484
• 2006: 0.8477
• 2007: 2.8672
• 2008: 2.5586
• 2009: 2.2070
• 2010: 1.8945
• 2011: 3.2656
• 2012: 2.4336
• 2013: 3.1055
• 2014: 2.4883

College Football SRS: Our CFB SRS does not contain a home-field advantage element, but it does have some other quirks. Most importantly, we have capped the margin of victory considered for the formula. Due to the number of mismatches seen in college football, the maximum point differential a team can be credited with in a game is 24. We also credit all wins as a minimum of plus-7 margin of victory (so if you win by 1 point, it's treated the same as a 7-point win). The same logic is applied to losses, as well. One other wrinkle for CFB is that all non-major opponents are included as one team for the sake of the ratings.

College Basketball SRS: SRS for college hoops is straight forward (no HFA & no adjusted MOV), but one item to note is that games against non-major opponents are not counted in our calculations.

MLB, NBA & NHL: All of these SRS calculations are straight forward with no adjustments for HFA and no capping of MOV. It should be noted, however, that no special consideration is given for extra-innings, overtimes or shootouts, either.

We'll close with a quick rundown of the various merits and weaknesses of SRS, from Drinen's original 2006 post. These bullet points were created to describe the system used for NFL SRS, but many of the strengths and weaknesses can applied to the other sports, as well:

• The numbers it spits out are easy to interpret - if Team A's rating is 3 bigger than Team B's, this means that the system thinks Team A is 3 points better than Team B. With most ranking algorithms, the numbers that come out have no real meaning that can be translated into an English sentence. With this system, the units are easy to understand.
• It is a predictive system rather than a retrodictive system - this is a very important distinction. You can use these ratings to answer the question: which team is stronger? I.e. which team is more likely to win a game tomorrow? Or you can use them to answer the question: which of these teams accomplished more in the past? Some systems answer the first questions more accurately; they are called predictive systems. Others answer the latter question more accurately; they are called retrodictive systems. As it turns out, this is a pretty good predictive system. For the reasons described below, it is not a good retrodictive system.
• It weights all games equally - every football fan knows that the Colts' week 17 game against Arizona was a meaningless exhibition, but the algorithm gives it the same weight as all the rest of the games.
• It weights all points equally, and therefore ignores wins and losses - take a look at the Colts season. If you take away 10 points in week 3 and give them back 10 points in week 4, you've just changed their record, but you haven't changed their rating at all. If you take away 10 points in week 3 and give back 20 points in week 4, you have made their record worse but their rating better. Most football fans put a high premium on the few points that move you from a 3-point loss to a 3-point win and almost no weight on the many points that move you from a 20-point win to a 50-point win.
• It is easily impressed by blowout victories - this system thinks a 50-point win and a 10-point loss is preferable to two 14-point wins. Most fans would disagree with that assessment.
• It is slightly biased toward offensive-minded teams - because it considers point margins instead of point ratios, it treats a 50-30 win as more impressive than a 17-0 win. Again, this is an assessment that most fans would disagree with.
• This should go without saying, but - I'll say it anyway. The system does not take into account injuries, weather conditions, yardage gained, the importance of the game, whether it was a Monday Night game or not, whether the quarterback's grandmother was sick, or anything else besides points scored and points allowed.

## Hiring: Analytics Consultant, Posted Feb 27, 2015

27th February 2015

Posted in Announcement, Baseball-Reference.com, Basketball-Reference.com, CBB at Sports Reference, CFB at Sports Reference, expire21d, Hockey-Reference.com, Olympics at S-R, Pro-Football-Reference.com, Statgeekery | Comments Off on Hiring: Analytics Consultant, Posted Feb 27, 2015

## Find Players Older Than You Are

17th February 2015

With the retirement of Jason Giambi I've seen some talk from people that there are now no longer any MLB players older than them. Since I'm never one to pass up on the opportunity to make a relatively useless tool, I've added a quick Pro Football Reference page to find active NFL players as old or older than you are. Basically, we just need to hope that Adam Vinatieri keeps kicking.

## Sports Reference Welcomes Adam Wodon to Our Staff

9th February 2015

Adam Wodon has joined Sports Reference today as a Managing Director for Hockey Reference. Adam will be working out of our Philadelphia office as our staff size has now risen to six. Adam brings a great deal of development experience and hockey knowledge to Sports Reference. Adam is the founder and managing editor of College Hockey News. Adam is an Isles fan through and through and also supports the Mets, Jets, and Nets making him the first diehard National League fan on staff. Adam is also on twitter at (@chn_AdamWodon).

Hans VanSlooten (@CantPitch) who had been working on the hockey site for the last 14 months will be taking over primary day-to-day development of Baseball-Reference.com.

## Explore PFR’s Super Bowl Section

23rd January 2015

If you haven't seen the Super Bowl Section of our site yet, you should head over and check it out right now, because we think it's pretty awesome. Here are some of the features you'll find once you get there:

And best of all is the Super Bowl Play Finder tool. It's similar to the Play Index Game Play Finder tool, but limits your searches strictly to Super Bowls and allows you to search through every play of all 48 previous games. Some examples:

Our Player Game Finder and Team Game Finder are also unique tools for Super Bowl research. You can use them to find things like every 100-yard rusher in Super Bowl history, the largest point spreads in Super Bowl history or the highest over/unders. You can also identify trends such as the record of the team leading after one quarter (26-11), at halftime (36-10) and through three quarters of play (39-8).

So go ahead and try the Super Bowl Section right now -- it's free, easy to use, and best of all, with it you'll be able to dominate anyone who challenges you in Super Bowl trivia.

UPDATE: We have also added a Super Bowl filter to our Drive Finder, which allows users to find things such as the longest drives in any Super Bowl since 1998 or the fastest Super Bowl touchdown drives since 1998.

## Punt Statistics Added to Team Game Finder

9th January 2015

Just wanted to quickly note that we have added Punts, Punting Yards & Yards per Punt to the Team Game Finder in the Play Index. The data is complete back to 1950, but is spotty before that. We apologize to Doug Drinen for adding more punting stats, but encourage users to enjoy the new queries.

Posted in Announcement, Features, Play Index, Pro-Football-Reference.com, Uncategorized | Comments Off on Punt Statistics Added to Team Game Finder

## 2015 First Round Picks Up

16th December 2014

The 2014 playoff standings, this may give you some hope. We list the average weighted career AV of a player picked at that spot as of the 2007 draft (so that it's not brought down by recent draft picks who haven't had time to amass career numbers). For instance the #7 overall pick has an average weighted career AV of 39, which is about equivalent to LeRoy Hill. You'll also find a link to all of the seventh overall picks so you can hope your team picks more towards the Champ Bailey end of the spectrum and less towards the Troy Williamson end.

Posted in Announcement, Pro-Football-Reference.com | Comments Off on 2015 First Round Picks Up

## First Downs Added to Team Game Finder

26th November 2014

We just wanted to quickly note that we have added First Downs (for & against) as a search criteria in the Team Game Finder. Additionally, we have added breakdowns for First Downs by rushing, passing & penalties since 1999 (total First Downs are complete back to 1940). Here's a few examples of these new searches:

These searches are just the tip of the iceberg here and we encourage users to dig in.

## Touches Added to Play Index

5th November 2014

You often hear about dangerous workloads for NFL running backs and the struggles many have had after particularly taxing seasons. But, particularly in this era, the running game is only part of the equation for backs (though we won't opine on whether or not receptions are less taxing than rushes). Many of them are 3-down players heavily involved in the passing game. With that in mind, we've added "touches" as a searchable statistical category in the Play Index. For our purposes, we have defined "touches" as the sum of rushes, receptions, kick returns & punt returns. While Larry Johnson may famously hold the record for rush attempts in a season with 416, James Wilder has the record for touches with 492 in 1984. The most touches in a game we have in our data (since 1960) is 48 by LaDainian Tomlinson & Wilder.

As I write, the 2014 leader in touches is DeMarco Murray, with 255 through 9 games. That puts him on pace for 453 touches this season, which would be tied with Eddie George for 3rd most in NFL history and 14 more than Emmitt Smith ever had in a season.

Posted in Announcement, Data, Play Index, Pro-Football-Reference.com | Comments Off on Touches Added to Play Index

## Combined Points Added to Team Game Finder

4th November 2014

Thanks to a recommendation from user Jon P, we have added "combined points" as a search and filter option in the Team Game Finder.

You can now search for games in which the 2 teams combined for 100+ points or the highest scoring games since the merger. Or, if you can stomach it, you can even find games with twice as many turnovers as points.