The scoring explosion is even further out of hand. I joined a new league last week in Auburn, MA. I had a great look with my pin down Major 52 (thanks Larry Litchstein!) and was in the process of shooting 773 (update – in week two I went -1, that is I shot 772). My book average last year was 219, which means that based on 90% of 240, I get 19 pins of handicap. My opponent asked how I got so much handicap, and I told him my 219 was because my other league used different patterns throughout the year, including one quarter with a Challenge Series Pattern (1:3.61 ratio) – like a Sport shot. Since I didn’t bowl on the usual walled up house shot all year (like this league did, which is why they had to move the handicap base up to 240), my average was more reasonable. The truth is if my look stays like it is you could easily argue I shouldn’t have had any handicap from the beginning.
There’s no system to adjust averages. So what’s wrong with the current handicap system? There’s no adjustment for what pattern(s) you bowled on and in which house you bowled in. There’s no reason why my 219 average in my last league shouldn’t translate to at least 235 or higher on this walled up shot.
Many bowlers are bowling on an easy shot and think they are better than they are. The bowling scoring explosion is worse than ever There’s been plenty of blame assigned to the ABC/USBC on this front, so I won’t pile on. Like alcoholism, the first step to recovery is to ADMIT YOU HAVE A PROBLEM. We must first let people know how easy the lanes they are bowling on actually are, compared to, say, a PBA animal pattern, the USBC Sport shot, the Kegel Challenge patterns, or any other more challenging shot.
What pattern were the scores bowled on? We need to get the USBC to add only one very important piece of data to league and tournament scores as they are captured: the pattern the score was bowled on. If this were captured, statistics could be analyzed for scores bowled on that pattern for each house. That could be compared scores bowled on other patterns at that and other houses. You could even go back in time for leagues that had the same patterns out in previous years to jump start the analysis.
Out of this analysis could come a “normalized” average, that is, an average that allows us to compare everyone in the country in exactly the same way based on talent, not lane conditions. We could also figure out what is “par” – that is, return to the idea that a true scratch score in bowling is 200 and compare the bowler’s talent against par with the pattern taken out of the equation. True scratch bowlers will average 200 or higher after their averages are normalized, just as true scratch golfers shoot par or better.
Pattern to Par (PTP) conversion. To adjust a bowler’s average relative to par an average multiplier is needed. Let’s call it the PTP – Pattern to Par. Again, par in bowling is supposed to be 200. The PTP would be applied to an average and it would “normalize” that average relative to a par of 200.
Example. Let’s say a scratch (par) bowler averages 220 on the “Easy Street” pattern, a walled up house shot. Let’s say the same scratch bowler averages 185 on a USBC Sport pattern – one of the tougher patterns out there. Statistics have shown that the PTPs for those two patterns might look something like this:
Pattern To Par (PTP):
Easy Street PTP: .91
USBC Sport Shot PTP: 1.08
We then take the bowler’s average and multiply it by the PTP. So on Easy Street, the 220 average * PTP (.91) = 200. For the Sport pattern, the 185 average * PTP (1.08) = 200.
Real world example. Let’s say a bowler averages 212 on Easy Street. That bowler’s average compared to par is 193 (212 * .91). If the bowler wants to be a “scratch” bowler, s/he needs to practice and improve enough to average at least 220 on the Easy Street shot.
Par average to pattern. Now let’s say our 212 bowler bowls on a Sport shot. What would s/he be expected to average? We need a way to take the bowler’s normalized average and convert it to the average expected for the Sport shot. To calculate this, we simply divide the bowler’s normalized average by the PTP. So, our 212 bowler, who’s actual average compared to par is 193, now needs to have that 193 divided by the Sport pattern PTP, or 1.08. 193 / 1.08 = 178, so the bowler would be expected to average 178 on the sport shot.
Now let’s tell the bowler their true averages. “178? I’m better than that – I average 212!” No, you are actually a 193 bowler compared to a 200 par and you should expect to only average 178 on the Sport shot where par is 185. You need to practice!
One more example. Let’s say our bowler wants to bowl on the Route 66 pattern, one of the Kegel Challenge patterns. Route 66 is easier than the Sport shot, but harder than Easy Street. For Route 66 let’s say the “par” average is 195, making the PTP 1.03 (200/195). Again, the PTP needs to be determined by analyzing scores across the country and the world. As above, the bowler’s 212 average first goes to a normalized 193 (212 * the Easy Street PTP of .91), then is divided by the Route 66 PTP of 1.03 to arrive at an expected average of 187. The 212 bowler’s average gets adjusted to 187 for Route 66.
Keep it fair! This system would make handicap tournaments much fairer. It would let bowlers know where they stand relative to par, and where they stand relative to other bowlers from other houses on different patterns. It would provide a credible answer to my opponent when they question why I am getting 21 pins when I should get just a few pins if any. EVERYONE WILL FIND OUT HOW GOOD THEY REALLY ARE.
Is the USBC up to this challenge? The USBC is the ONLY institution that can implement this system. They have a view of scores on all patterns in houses across the entire country. Ideally, the system would be implemented across the globe so all bowlers of all abilities anywhere in the world could find out how good they really are.
The USBC tried to address the scoring explosion with the Sport shot. The good news is that they have an average conversion chart that converts Sport shot averages to “normal” averages and back again. The bad news is that there is no way they had enough data to properly populate such a chart. One must know the PTPs for patterns and houses across the country before such a conversion chart can be created with any kind of accuracy.
So how about it USBC – are you ready to take the first step in fixing the scoring explosion? Who’s ready to take up the call with me to the USBC to implement this system?